FINANCIAL STABILITY REVIEW No. 27, September 2016 FINANCIAL STABILITY REVIEW No. 27, September 2016

Mitigating Systemic Risk and Strengthening Intermediation to Maintain Financial System Stability MACROPRUDENTIAL POLICY DEPARTMENT FINANCIAL STABILITY REVIEW No. 27, September 2016

Director Publisher : Erwin Rijanto Filianingsih Hendarta Yati Kurniati Dwityapoetra S. Besar Jl. MH Thamrin No.2, Coordinator and Editor Indonesia Retno Ponco Windarti – Yanti Setiawan – Rozidyanti - Herriman Budi Subangun – Reska Prasetya – Minar Iwan Setiawan

The preparation of the Financial Stability Review is one of the avenues through Drafting Team which Bank Indoensia achieves its mission ”to safeguard the stability of the by M. Firdaus Muttaqin, Kurniawan Agung, Ita Rulina, Indra Gunawan, Arlyana Abubakar, Ndari Suryaningsih, Cicilia maintaining monetary and financial system stability for sustainable national economic development”. A. Harun, Khairani Syafitri, Risa Fadila, Lisa Rienellda, Bayu Adi Gunawan, Heny Sulistyaningsih, Hero Wonida, Sigit Setiawan, Ardhi Santoso H.M., Arifatul Khorida, Justina Adamanti, Maulana Harris Muhajir, Zulfia Fathma, FSR is published biannually with the objectives : Sagita Rachmanira, Afaf Munawwarah, Arisyi Fariza Raz, Anindhita Kemala D., Apsari Anindita N.P, Dhanita • To improve public insight in terms of understanding financial system stability Fauziah Ulfa, Rieska Indah Astuti, Teguh Arifyanto, Amalia Insan Kamil, Randy Cavendish, Harris Dwi Putra, • To evaluate protential risks to financial system stability Pita Pratita, Syachman Perdymer, Rio Khasananda, Illinia Ayudhia Riyadi, Widyastuti Noviandri, Rifki Ismail, • To analyze the developments of and issues within the financial system Yono Haryono, Diana Yumanita, Jhordy K. Nazar, Fadhil, Kartina Eka Darmawanti, Meliana Rizka, Fiona Rebecca • To offer policy recommendations to promote and maintain financial system stabilty Hutagaol, Agus Seno Aji, Rolan Erikson Samosir, Agustina Damayanti, Indra Gunawan Sutarto, Dahnila Dahlan, RR. Diva Amelia Putri, Irman Robinson, Wahyu Widianti, Inrayanto Ariandos, Fransiskus Xaverius Tyas Prasa

Information and Orders: OTHER DEPARTMENT CONTRIBUTION ON SELECTED ANALYSIS This edition is published in September 2016 and is based on data and information available as of June 2016, Economic and Department unless stated otherwise. Financial System Surveillance Department SME Development Department The PDF format is downloaded from https://www.bi.go.id Statistics Department Source : Bank Indonesia, unless stated otherwise Payment System Policy and Oversight Department For inquiries, comment and feedback please contact : Payment System Management Department Financial Market Development Department Bank Indonesia Macroprudential Policy Department PRODUCTION AND DISSEMINATION TEAM Jl. MH Thamrin No.2, Jakarta, Indonesia Saprudin, Satrio Prasojo, Vergina Hapsari, I Made Yogi Email : [email protected] “Mitigating Systemic Risk and Strengthening Intermediation to Maintain Financial System Stability”

MACROPRUDENTIAL POLICY DEPARTMENT CONTENTS

Foreword xv Executive Summary xvii

1. Financial System Stability 3 1.1 Global and Regional Financial Market Risks 5 1.2 Domestic Financial Market Risks 7 1.3 Financial System Stability in Indonesia 10 1.4 Domestic Financial Imbalances 13 Box 1.1. Tax Amnesty 19 Box 1.2. Analysis of Financial Imbalances based on the National Financial Account and Balance Sheet (NFA & BS) 22 Box 1.3. Impact of the Brexit on the Indonesian Economy 25

2. The Financial Markets 31 2.1. The Role of Financial Markets as Sources of Economic Financing 33 2.2. Risks on the Financial Markets 37 2.3. Assessment of Islamic Financial Market Conditions and Risks 52 Box 2.1. Foreign Currency Structured Product Transactions against the Rupiah as Call 60 Spread Options Box 2.2. Waqf-based Sukuk to Empower Waqf Assets 63 Box 2.3. Strengthening JIBOR as the Price Reference Rate on the Markets 68

3. Households And The Corporate Sector 71 3.1. Household Sector Assessment 73 3.2. Corporate Sector Assessment 80 Box 3.1. Regional Financial Surveillance (RFS) Implementation Framework at Domestic Bank Indonesia Representative Offices 93 Box 3.2. Bank Indonesia Household Balance Sheet Survey 96

4. and Nonbank Financial Institutions 99 4.1. The Banking Industry 108 4.2. The Nonbank Financial Industry 135 4.3. Islamic Banks 143 Boks 4.1. Awarding Banks that Support Micro, Small and Medium Enterprises (MSME) Boks 4.2. Liquidity Coverage Ratio (LCR) 150 153

5. Strengthening Financial System Infrastructure 151 5.1. Payment System Performance 153 5.2. Payment System Transaction Performance 154 5.3. Payment System Indicators 156 5.4. Payment System Risks and Mitigation Efforts 157 5.5. Digital Financial Services and Financial Inclusion 159 Box. 5.1. Disbursement of Noncash Social Assistance Funds 163

ii 6. Bank Indonesia Policy Response to Support 167 Financial System Stability 6.1. Assessment of the LTV/FTV (loan-to-value/financing-to-value) Ratios for Property Loans and Downpayments on Automotive Loans 170 6.2. Assessment of the RR-loan to funding ratio (RR-LFR) and adjustments to the checking account services to meet the MSME loan requirement 173 6.3. Setting the Countercyclical Capital Buffer (CCB) Rate at 0% 176 6.4. Policy Coordination between Bank Indonesia and the Other Authorities 180 Box 6.1. Transmission of the BI 7-Day (Reverse) Repo Rate to Bank Interest Rates 182 Box 6.2. Financial Sector Assessment Program: Maintaining Global Financial Stability 187 Box 6.3. Financial Market Development and Deepening Coordination Forum (FK-PPPK) 190

Article 1 194 Systemic Risk Measurement Framework 195

Article 2 212 Financial Network Stability in Indonesia’s Banking System 213

iii LIST OF TABLE

1. Financial System Stability Table 3.6 Corporate Credit by Economic Sector 86 Table 3.7 Credit to Major Export Commodities 87 Table 1.1 Global Economic Outlook 5 Table 3.8 Restructured External Debt by Economic 90 Table 1.2 Total Hedging against External Debt and 17 Sector in May 2016 Compliance in Semester I – 2016 Table 3.9 Positive and Negative Tone External Debt 91 Box Table 1.1 Tax Amnesties in Various Countries 19 Restructuring

Box Table 3.2.1 Household Classification based on 97 Spending 2. The Financial Markets

4. Banks and Nonbank Financial Institutions Table 2.1 Bank and Nonbank Financing (Rp, 33 trillions) Table 4.1 LA/NCD by BUKU Bank Group 103 Table 2.2 Sources of Funds by Bank Total 36 Table 4.2 Additional Liquid Assets 103 Table 2.3 Source of Bank Funds by Volume 36 in Quarter II – 2016

Table 2.4 A Comparison of Average NDF Spread in 43 Table 4.3 LDR by BUKU Bank Group 104 the Region Table 4.4 Annual Deposit Growth by Bank Group 105 Table 2.5 Composition of SBN Holdings 44 Table 4.5 SBN Holdings by Institution 107 Table 2.6 10-Year SBN Yields in the Region (%) 46 Table 4.6 Share of Total Deposits by Island 107 Table 2.7 10-Year SBN Yield Volatility in the Region 46 (%) Table 4.7 GDP Growth by Economic Sector 109

Table 2.8 Corporate Bond Holdings 47 Table 4.8 Market Share of Credit in Indonesia 110 based on Project Location Table 2.9 Foreign Stock Holdings by Business 49 Group (Rp, trillions) Table 4.9 Credit Growth by Bank Group 110

Table 2.10 Foreign Stock Holdings by Economic 49 Table 4.10 Growth and Market Share of MSME 112 Sector (Units, billions) Credit by BUKU Bank Group

Table 2.11 Index Volatility by Sector 50 Table 4.11 Gross NPL by Region 115

Table 2.12 Issuers of Islamic Stocks 57 Table 4.12 Gross NPL Ratio by Bank Group 115

Table 4.13 Total Downgraded Bonds (Pefindo 115 Table 2.13 Islamic Mutual Funds 58 Rating)

Table 4.14 Deposit Rates by BUKU Bank Group 117

Table 4.15 Lending Rates by BUKU Bank Group 117 3. Households and The Corporate Sector Table 4.16 SBN Holding Value by Bank Group 119

Table 3.1 DSR Composition based on Monthly 76 Table 4.17 Share of SBN Holdings by Bank Group 120 Income Table 4.18 Total Downgraded Bonds (Pefindo 122 Table 3.2 Composition of Savings based on 76 Rating) Monthly Income Table 4.19 Banking Industry Profit/Loss (Rp, trillions) 123 Table 3.3 Personal Loans by Type 78 Table 4.20 Breakdown of Income Accounts 123 Table 3.4 Corporate Financial Performance 83 Indicators by Sector Table 4.21 Breakdown of Expense Accounts 123

Table 3.5 Corporate Financial Performance 84 Table 4.22 CAR by Bank Group 125 Indicators by Major Export Commodity Sector Table 4.23 Bank Interconnectedness with the 133 Finance Industry

iv Table 4.24 Interconnectedness between the 134 Banking Sector and Insurance Industry

Table 4.25 Interconnectedness between the 135 Banking Sector and Insurance Industry

Table 4.26 Insurance Industry Assets and Financial 136 Performance

Table 4.27 Capital Adequacy of Public Listed 136 Insurance Companies

Table 4.28 Financing Risk by Region 140

5. Strengthening Financial System Infrastructure

Table 5.1 BI-RTGS, BI-SSSS and SKNBI, Card-Based 154 Instruments and Electronic Money

Table 5.2 Ten Large Banks with Most 158 Counterparties

Table 5.3 Total Individual and Business DFS Agents 160 in Semester I – 2016

6. Bank Indonesia Policy Response to Support Financial System Stability

Table 6.1 LTV/FTV Ratios for Banks to Meet 170 Prevailing NPL/NPF Requirements for Total Credit or Financing

Table 6.2 Property Credit, Housing Loans, Flat/ 171 Apartment Loans

Table 6.3 NPL Growth of Property Loans for 172 Houses and Flats/Apartments

Table 6.4 NPL Growth of Property Loans for Flats/ 173 Apartments

Article 2

Article Table 2.1 Bank Balance Sheets under Symmetrical 215 Conditions

Article Table 2.2 Result on t-test from 2008 and 2014 216

Article Table 2.3 Correlation of Bank Assets, Interbank 219 Placements and Interbank Liabilities (2014)

v LIST OF GRAPH AND FIGURE

1. Financial System Stability Box Figure 1.3.2 Voting Results by Region 25 Box Figure 1.3.1 UK GDP Per Capita 26 Graph 1.1 Brent Oil Price Performance 6 Box Figure 1.3.2 UK Trade Performance 26 Graph 1.2 Commodity Price Indexes for CPO, 6 Rubber and Coal Box Figure 1.3.3 Direct Investment Inflows to UK 26

Graph 1.3 CDS in Advanced Countries and the 6 Box Figure 1.3.4 GBP and EUR Performance in 2016 27 Region Box Figure 1.3.5 FTSE 100 and Stoxx Europe 27 Graph 1.4 JCI and Global Indexes 6 Performance in 2016

Graph 1.5 VIX Index 6 Box Figure 1.3.6 Changes in Currencies in Asia (23rd 27 June 2016 vs 24th June 2016 Graph 1.6 Inflation and GDP Growth 7 Box Figure 1.3.7 Intraday Rupiah Exchange Rate 28 Graph 1.7 Balance of Payments (BOP) in 2015 7 Movements

Graph 1.8 Rupiah Exchange Rate 9 Box Figure 1.3.8 Changes in Stocks in Asia (23rd June 28 2016 vs 24th June 2016) Graph 1.9 Rupiah Appreciation and Depreciation 9 against the US Dollar Box Figure 1.3.9 Changes in Yields in Asia (23rd June 28 2016 vs 24th June 2016) Graph 1.10 Annual Rupiah Volatility 9 Box Figure 1.3.10 SBN Yield in Indonesia in 2016 28 Graph 1.11 Net Flows of Non-Resident Capital 9 Box Figure 1.3.11 JPY and USD Movements 29 Graph 1.12 Financial System Stability Index 11 Box Figure 1.3.12 Major Export Destinations from 29 Graph 1.13 Financial Institution Stability Index 11 Indonesia

Graph 1.14 Financial Market Stability Index 12 Box Figure 1.3.13 Gold Price (23-24th June 2016) 29

Graph 1.15 Banking Systemic Risk Index 12 Box Figure 1.3.14 FDI Inflows to Indonesia from UK 29

Graph 1.16 Composite Stock Price Indexes in 12 Several Countries

Graph 1.17 Asset Share of Financial Institutions 12 2. The Financial Markets

Graph 1.18 The Financial Cycle and Bank Lending 14 Procyclicality Graph 2.1 IPO and Rights Issue Volume on the 34 Stock Market Graph 1.19 External Debt Composition by Debtor 16 to GDP Graph 2.2 Value of Bond Issuances 34

Graph 1.20 Nonbank Private External Debt based 16 Graph 2.3 Comparison of Corporate Bond 34 on Original Maturity Yield Curve and Average Interest Rates on Working Capital Loans and Graph 1.21 Debt Service Ratio (DSR) 16 Investment Loans

Graph 1.22 Non-Resident SBN Holdings 18 Graph 2.4 Nominal Outstanding MTN dan NCD 34

Graph 1.23 Non-Resident Stock Holdings 18 Graph 2.5 Outstanding Mature MTN and NCD 35

Graph 1.24 Non-Resident and Resident SBI 18 Graph 2.6 Nominal Issueance MTN dan NCD 35 Holdings Graph 2.7 Financial Market Volatility 37 Graph 1.25 Stock Prices and Transaction Volume 18 Graph 2.8 Non-Resident Flows: Stocks, SBN 37 Graph 1.26 SBN Prices and Transaction Volume 18 and SBI

Box Figure 1.1.1 Tax Reporting Mechanism and 20 Graph 2.9 O/N Rupiah Interbank Rate 38 Instruments Graph 2.10 O/N Rupiah Interbank Rate Volatility 38 Box Figure 1.2.1 Net Intersectoral Transactions 23 Graph 2.11 Rupiah Interbank Money Market 39 Box Figure 1.2.2 Gross Exposure between Sectors 24

Box Figure 1.3.1 UK Referendum Voting Results 25 vi Graph 2.12 Rupiah Interbank Transaction 39 Graph 2.40 JCI and LQ45 Capitalisation 50 Distribution Graph 2.41 JCI Share Trade Frequency 50 Graph 2.13 Foreign Exchange Interbank Money 40 Market Performance Graph 2.42 Position of Mutual Funds 51

Graph 2.14 O/N Foreign Exchange Interbank Rate 40 Graph 2.43 NAV of Mutual Funds by Type 51

Graph 2.15 Foreign Exchange Interbank Rate 40 Graph 2.44 NAV Volatility of Mutual Funds 51 Volatility Graph 2.45 Growth of Mutual Funds (yoy 51 Graph 2.16 Foreign Exchange Interbank 40 Transactional Behaviour Graph 2.46 Risk Profile of Mutual Fund Products 51

Graph 2.17 Interbank Repo Transactions 41 Graph 2.47 Average NAV of Closed-End and 52 Open-Ended Funds Graph 2.18 Lending Facility Transactions 41 Graph 2.48 Islamic Interbank Money Market and 53 Graph 2.19 Rupiah Exchange Rate 42 Islamic Bank Indonesia Certificate

Graph 2.20 Rupiah Volatility 42 Graph 2.49 Islamic Interbank Money Market 53 Performance and Yield of Graph 2.21 Foreign Exchange Market Risk 42 Mudharabah Premium Investment Certificates (SIMA)

Graph 2.22 Domestic Foreign Exchange Market 43 Graph 2.50 Nominal SBSN and Market price 53 Composition Graph 2.51 Market Price and Repo Rate 53 Graph 2.23 Composition of SBN Holdings (June 44 2012 – June 2016) Graph 2.52 SBSN Issuances (2008 – 2016) 54

Graph 2.24 Net Foreign Flows to SBN and IDMA 44 Graph 2.53 Outstanding SBSN (2008 – 2016) 55

Graph 2.25 SBN Yield Curve 45 Graph 2.54 SBSN Maturity Profile 55

Graph 2.26 Rebased SBN Yield by Tenor 45 Graph 2.55 SBSN Distribution by Type 56

Graph 2.27 SBN Yield Volatility by Tenor 45 Graph 2.56 SBSN Distribution by Tenor 56

Graph 2.28 SBN and Corporate Bond Transaction 45 Graph 2.57 SBSN Distribution by Currency 56 Turnover Graph 2.58 SBSN Distribution by Tradability 56 Graph 2.29 SBN to GDP Ratio 45 Graph 2.59 Corporate Sukuk Performance 57 Graph 2.30 Rebased 10-Year SBN Yield in several 46 Emerging Market Economies (EME) Graph 2.60 Growth of Islamic Stock Issuers 58

Graph 2.31 Net Foreign Flows to Corporate 47 Graph 2.61 Jakarta Islamic Index (JII) 58 Bonds and Holdings Graph 2.62 Jakarta Islamic Index Volatility 58

Graph 2.32 Corporate Bond Yield Curve 47 Graph 2.63 Islamic Mutual Funds 59

Graph 2.33 Corporate Bond Yield Volatility by 47 Graph Box 2.1.1 Turnover on the Domestic Foreign 60 Tenor Exchange Market

Graph 2.34 Corporate Bond Issuers by Sector 47 Box Graph 2.1.2 Hedging Costs (1-Month Swap 61 Graph 2.35 Regional Stock Price Indexes 48 Premium): A Comparison of Several Countries Graph 2.36 Stock Price Volatility 48 Box Graph 2.1.3 Call Spread Option Transaction 61 Graph 2.37 Foreign Capital Inflows to Regional 48 Mechanism Stock Markets Box Graph 2.2.1 Less Productive Waqf Asset 63 Graph 2.38 Net Foreign Trade on the Stock 48 Management Market and JCI

Graph 2.39 Stock Market Turnover 50

vii LIST OF GRAPH AND FIGURE

Box Graph 2.2.2 Real Economic and Islamic Financial 65 Graph 3.22 Distressed Corporate Performance 86 Market Conditions against GDP Z-Score

Box Graph 2.2.3 Waqf-Based Sukuk (SOE) 66 Graph 3.23 Corporate Credit by BUKU Bank 86 Group Box Graph 2.3.1 Benefits of the Transactable 68 Mechanism by Contributor Banks Graph 3.24 Corporate Deposits 87

Graph 3.25 Corporate Deposits by BUKU Bank 88 Group 3. Households and The Corporate Sector Graph 3.26 External Debt Structure in Indonesia 88

Graph 3.1 Contribution of Household 73 Graph 3.27 Private External Debt Structure and 89 Consumption to GDP Growth

Graph 3.2 Real Sales Growth 73 Graph 3.28 Restructured Non-Financial Corporate 90 External Debt Graph 3.3 Consumer Confidence Index (CCI), 74 Current Economic Condition Index Graph 3.29 Outstanding Restructured External 90 (CECI) and Consumer Expectation Debt (USD, billions) Index (CEI) Graph 3.30 Share of Outstanding Restructured 90 Graph 3.4 Three-Month Price Expectations Index 74 External Debt to Total Restructured (PEI) External Debt (%)

Graph 3.5 Six-Month Price Expectations Index 74 Graph 3.31 Principal and Interest Payments 92 (PEI) on Positive and Negative Tone Restructured External Debt Graph 3.6 Allocation of Household Spending 74 Grafik 3.32 Planned Interest and Principal 92 Graph 3.7 Composition and Growth of Deposits 77 Payments on Positive and Negative Tone Restructured External Debt Graph 3.8 Composition and Growth of 78 Household Deposits Box Figure 3.1 Regional Financial Surveillance 93 Implementation Framework Graph 3.9 Composition of Bank Credit 78 Box Figure 3.2 Business Processes of RFS 94 Graph 3.10 Household Credit Growth by Loan 79 Implementation Type

Graph 3.11 Growth and NPL of Household 79 Consumer Loans

Graph 3.12 NPL of Household Loans by Type 79 4. Banks and Nonbank Financial Institutions

Graph 3.13 Composition of Household Consumer 80 Graph 4.1 Bank Liquidity Ratios 102 Loans Graph 4.2 Bank Liquid Assets 102 Graph 3.14 Global Commodity Prices 81 Graph 4.3 Liquidity Growth in the Economy and 103 Graph 3.15 Actual and Projected Corporate 81 Bank Liquidity Ratios Activity Graph 4.4 Government Net Expansion 103 Graph 3.16 Production Capacity Utilisation 81 Graph 4.5 Annual Deposit and Credit Growth 103 Graph 3.17 Key Indicators of Corporate Financial 83 Performance Graph 4.6 Lending Standards 104

Graph 3.18 Financial Performance of Publicly 84 Graph 4.7 Intermediation Interest Rates 104 Listed Non-Financial Corporations Graph 4.8 Realisation of Bank and Capital 105 Graph 3.19 Corporate Financial Performance 84 Market Financing Indicators by Major Export Commodit Graph 4.9 Comparison of Banking Rates and 105 Graph 3.20 Corporate Repayment Capacity 85 Corporate Bonds

Graph 3.21 Corporate Performance based on the 86 Graph 4.10 Annual Deposit Growth 105 Altman Graph 4.11 Deposit Rates 106 viii Graph 4.12 Deposit Growth by Type 106 Graph 4.42 BOPO Efficiency Ratio by Bank Group 124 (%) Graph 4.13 Average Rate on 1-Month Rupiah 106 Term Deposits by Bank Group Graph 4.43 CIR Ratio by Bank Group (%) 124

Graph 4.14 Composition of Bank Deposits 106 Graph 4.44 Bank CAR (%) 125

Graph 4.15 Deposits by Holder 107 Graph 4.45 Ratio of Tier 1 Capital (%) 125

Graph 4.16 Bank Credit Growth 108 Graph 4.46 Return on Assets (ROA) by Bank 126 Group (%) Graph 4.17 Credit Growth by Loan Type 108 Graph 4.47 Market Risk Scenario (SBN Prices) 126 Graph 4.18 Market Share of Different Loans 108 Graph 4.48 Risk Scenarios 127 Graph 4.19 Credit Growth by Economic Sector 109 Graph 4.49 Currency Risk Scenarios 127 Graph 4.20 Lending Rates by Bank Group 110 Graph 4.50 Results of the Aggregate Stress Tests 128 Graph 4.21 MSME Credit 111 Graph 4.51 Stress Tests by Bank Group (PSG 128 Graph 4.22 MSME Credit Growth in Five 111 Scenario) Economic Sectors Graph 4.52 Graph Stress Tests by Bank Group (VS 128 Graph 4.23 Net Expansion of MSME Loans at 112 Scenario) Commercial Banks Graph 4.53 Finance Company Assets and 129 Graph 4.24 Net Expansion of MSME Loans at 112 Financing BUKU 4 Banks Graph 4.54 Finance Company Financing by 129 Graph 4.25 Net Expansion of MSME Loans at 112 Business Activity BUKU 1 & 2 Banks Graph 4.55 Financing by Currency 130 Graph 4.26 NPL Ratio 113 Graph 4.56 NPF Ratio of Finance Companies 130 Graph 4.27 Gross NPL Ratio by Economic Sector 114 Graph 4.57 Funding and Financing Growth 131 Graph 4.28 Gross NPL Ratio by Loan Type 114 Graph 4.58 Sources of Funds 131 Graph 4.29 Gross NPL by Region 115 Graph 4.59 Share of FC Financing based on 131 Graph 4.30 Gross NPL Ratio of MSME Loans by 116 Lending Rate Business Scale Graph 4.60 External Debt at Finance Companies 132 Graph 4.31 Lending and Deposit Rates 116 Graph 4.61 ROA, ROE and BOPO of Finance 132 Graph 4.32 Lending and Deposit Rates 117 Companies

Graph 4.33 Total NOP and NOP Ratio by Bank 118 Graph 4.62 Insurance Industry Asset Share 133 Group Graph 4.63 Insurance Industry Assets and 133 Graph 4.34 SBN Yield Volatility 119 Investments

Graph 4.35 Growth of Banking Industry Foreign 121 Graph 4.64 Gross Premiums and Claims 134 Loans Graph 4.65 Insurance Indicators 134 Graph 4.36 Foreign Loans in Indonesia 121 Graph 4.66 Current Assets to Current Liabilities 134 Graph 4.37 Foreign Loans by Borrower 121 Ratio

Graph 4.38 Private Foreign Loans 121 Graph 4.67 Insurance Industry External Debt 135

Graph 4.39 Maturity Profile of Long-Term Foreign 121 Graph 4.68 Weighted Average Rupiah Deposit 135 Loans in the Banking Industry Rate of BUKU 1 Banks

Graph 4.40 Maturity Composition of Long-Term 121 Graph 4.69 Asset Composition of Public Listed 136 Foreign Loans Insurance Companies

Graph 4.41 Return on Assets (ROA) by Bank 122 Graph 4.70 Banking Industry Procyclicality 137 Group (%)

ix LIST OF GRAPH AND FIGURE

Graph 4.71 Asset Share of the Islamic Banking 138 Graph 5.7 Total E-Money Account Holders at 161 Industry DFS Agents

Graph 4.72 Deposits 138

Graph 4.73 Deposit Share 138 6. Bank Indonesia Policy Response to Support Graph 4.74 Deposit Composition of Islamic Banks 139 Financial System Stability

Graph 4.75 Financing Performance 139 Graph 6.1 Performance of Housing Loans 171

Graph 4.76 Financing Share 139 Grafik 6.2 Housing Loan Growth 171

Graph 4.77 FDR of Islamic Banks 140 Graph 6.3 NPL of Housing Loans 172

Graph 4.78 Financing by Type 140 Graph 6.4 NPL of Loans for Flats/Apartments 172

Graph 4.79 Financing Risk at Islamic Banks 140 Graph 6.5 Bank Intermediation 174

Graph 4.80 Gross NPF by Economic Sector 140 Graph 6.6 MSME Credit Growth and NPL 175

Graph 4.81 Liquidity Comparison 141 Graph 6.7 MSME Loans 175

Graph 4.82 Liquidity at Islamic Banks 141 Graph 6.8 Looser Monetary Policy, Bank 175 Graph 4.83 Capital Adequacy Ratio 142 Liquidity and Credit Growth

Graph 4.84 BOPO Efficiency Ratio 142 Graph 6.9 Ceiling and Floor of the RR-Loan to 176 Funding Ratio (RR-LFR) Graph 4.85 Financing Share 142 Graph 6.10 Credit-to-GDP Gap 176 Graph 4.86 Stress Test NPL Increase 143 Graph 6.11 CCB Rate per the Leading Indicator 176 Graph 4.87 Takaful Industry Assets 143 Graph 6.12 Financial Cycle and Business Cycle 177 Graph 4.88 Takaful Industry Investments 143 Graph 6.13 Real GDP Growth 178 Box Figure 4.1.1 Stages of Award Assessment 146 Graph 6.14 Inflation (yoy) 178 Graph Boks 4.2.1 A Comparison Between e-LCR and 149 h-LCR Graph 6.15 USD/IDR Exchange Rate 178 Graph 6.16 Private External Debt in Rupiah (yoy) 178

Graph 6.17 Annual Credit Growth 179 5. Strengthening Financial System Infrastructure Graph 6.18 Annual Deposit Growth 179 Graph 6.19 Non-Performing Loans (%) 179 Graph 5.1 Turnover Ratio by Bank Group 156 Graph 6.20 Return on Assets (%) 179 Graph 5.2 Queued Transactions 157 Graph 6.21 Capital Adequacy Ratio (%) 180 Graph 5.3 Indonesia Financial Inclusion 159 Composite Index (IKKI) Graph 6.22 JCI Volatility 180

Figure 5.1 DFS Agents in Indonesia 160 Box Graph 6.1.1 The development of interest rate 182 policy and the operational target of Graph 5.4 Total DFS Agents in 2016 160 monetary policy

Graph 5.5 Respective Shares of E-Money 161 Box Graph 6.1.2 Interest Rate Corridor 185 Transactions at DFS Agents in Semester I – 2016 Box Graph 6.1.3 Interest Rate Term Structure (TS) 185

Graph 5.6 E-Money Float at DFS Agents 161

x Box Figure 6.3.1 FK-PPPK Organisational Structure 191

Article 1

Article Figure 1.1 Phases of Systemic Risk 197

Article Figure 1.2 Systemic Risk Transmission 198

Article Figure 1.3 Systemic Risk Measurement 201 Framework

Article Figure 1.4 Systemic Risk Formation 204

Article Figure 1.5 Interaction between the Shock and 205 Vulnerability

Article Figure 1.6 Financial Cycle Phases 206

Article 2

Article Graph 2.1 Network Structure 214

Article Graph 2.2 Total Banks, Total Branches and Total 218 Banks by Core Capital in Indonesia from 2006-2012

Article Graph 2.3 Capital Adequacy Ratio (CAR) by 218 Bank Group

Article Graph 2.4 RTGS Transactions (2005-2015) 219

Article Graph 2.5 Interbank Offered Rate (2008-2015) 219

Article Graph 2.6 Financial Network of Banks in 220 Indonesia (2008 and 2014)

xi LIST OF ABBREVIATIONS

ABIF : ASEAN Banking Integration D-SIB : Domestic Systemically Framework Important Banks AFS : Available for Sale DSR : Debt Service Ratio AKSI : Arsitektur Keuangan Syariah DP : Down Payment Indonesia EAPP : Expanded Asset Purchase APMK : Card-Based Payment Program Instruments ECB : European AS : United States EM : Emerging Market ASEAN : Association of Southest Asian FA Financial Account Nations : FDI : Foreign Direct Investment ATM : Automated Teller Machine FKSSK : Financial System Stability ATMR : Risk-Weighted Assets Coordination Forum BBM : Fossil Fuels FLI : Intraday Liquidity Facility BCBS : Basel Committee on Banking FSB Financial Stability Board Supervision : : The Group of Twenty BIS : Bank for International Settlement GDP : Gross Domestic Product BI-RTGS : Bank Indonesia Real Time GNNT : Non-cash National Movement Gross Settlement GWM : Reserve Requirement (RR) BI-SSSS : Bank Indonesia Scripless HTM Hold to Maturity Securities Settlement System : IDMA Inter-dealer Market BOJ : Bank of Japan : Association BOPO : Efficiency Ratio of Operating IEK Consumer Expectation Index Costs to Operating Revenue : (CEI) BPD : Regional Banks IHK : Consumer Price Index (CPI) BPR : Rural Banks IHSG : Jakarta Composite Index (IDX bps : Basis point Composite) BUKU : Commercial Bank Groups IKK : Consumer Confidence Index based on Business Activity (CCI) CAR : Capital Adequacy Ratio IKNB : Nonbank Financial Institution CCB : Countercyclical Capital Buffer IMF : International Monetary Fund CDS : Credit Default Swap ISIK : Financial Intitution Stability Index CIR : Cost to Income Ratio ISPK : Financial Market Stability CPO : Crude Palm Oil Index DER : Debt to Equity Ratio ISSK : Indonesia Financial Stability DPK : Third Party Deposits Index

xii JPSK : Financial System Safety Net PDB : Gross Domestic Product KI : Investment Credit PDN : Net Open Position KK : Credit Consumer PIN : Personal Identification Number KMK : Working Capital Credit PLN : Offshore Loan KPA : Mortgage Facilities for Apartments PMK : Crisis Management Protocol KPMM : Minimum Capital Adequacy PP : Finance Company Requirement PUAB : Interbank Money Market KPR : Mortgage Facilites for Houses QAB : Qualified ASEAN Banks LCR : Liquidity Coverage Ratio RBB : Bank Business Plan LDR : Loan to Deposit Ratio ROA : Return on Asset LKD : Digital Financial Services ROE : Return on Equity LTV : Loan to Value SBDK : Prime Lending Rate LPS : Indonesia Deposite Insurance SBI Bank Indonesia Certicates Corporation : SBN Tradeable Government L/R : Profit/Loss : Securities Minerba : Mineral and Coal Mining SBT Net Weighted Balance MInerba) Act : SD Certificate of Term Deposit MTM : Marked to market (MTM) : SKDU Business Survey NAB : Net Asset Value (NAV) : SKNBI Bank Indonesia – National NCD : Negotiable Certificate of : Clearing System Deposit SNRT Household Survey NFA : Net Foreign Asset : SUN Government Bonds NFL : Net Foreign Liabilities : TDL Basic Electricity Rate NII : Net Interest Income : TOR Turn Over Ratio NIM : Net Interest Margin : TPT Textiles and Textile Products NPF : Non Performing Financing : ULN External Debt NPI : Indonesia Balance of Payment : UMKM Micro, Small and Medium NPL : Non Performing Loan : Enterprise (MSMEs) OJK : Indonesia Financial Services WEO World Economic Outlook Authority : OTC : Over the Counter PBOC : Peoples’ (PBOC) PD : Probability of Default

xiii xiv FOREWORD

As a routine semesterly publication, the Financial assessment of the first semester of 2016 showed that Stability Review represents a form of public financial system stability was successfully maintained accountability in terms of Bank Indonesia task despite limited global economic growth and early signs implementation and authority in the area of of improvement in the domestic economy. Financial macroprudential supervision and regulation. The FSR system stability was supported by capital resilience contains an assessment of financial system conditions and increased liquidity in the banking industry, and risks, as well as the triggers of financial system combined with gains on financial markets, although instability from a macroprudential perspective. A total credit and deposit growth continued to decelerate. of 27 editions of the Financial Stability Review (FSR) The nonbank financial industry and household have now been published, which Bank Indonesia sector were also observed to gain momentum, while expects to build public understanding concerning optimism prevailed in the corporate sector despite a the importance of macroprudential policy and Bank general slowdown. Indonesia’s macroprudential role, thereby enhancing the effectiveness of the policies pursued. The secure, efficient and reliable payment system, as an integral part of financial system infrastructure that Through the execution of its duties as the supports monetary stability and facilitates economic macroprudential authority, Bank Indonesia formulates activities, further bolstered financial system stability. macroprudential policy to complement monetary Payment system reliability helped optimise public policy in response to increasingly complex economic access to and use of financial services, indicated by dynamics, fraught with vulnerabilities, when increased uptake of digital financial services (DFS) overcoming problems in the financial cycle. To that and gains in the financial inclusion index, in line with end, macroprudential policy aims to mitigate potential greater public utilisation of bank branches, ATM systemic risk, or potential instability, from spillovers in machines, DFS agents and bank accounts, while the part or all of the financial system due to interactions value of deposits and loans also increased. between several factors, including size, business complexity, interconnectedness between institutions Notwithstanding, Bank Indonesia also noted the high and/or markets as well as excessive behaviour by risk of financial imbalances. Although the domestic financial institutions when following the financial economic recovery continued, the financial cycle cycle. remained in a contractionary phase, congruent with slower credit growth, limited fiscal space, growing The macroprudential policy direction pursued by foreign holdings on domestic financial markets and Bank Indonesia has proven effective in maintaining massive, unhedged corporate external debt. financial system stability. Bank Indonesia’s economic

xv FINANCIAL STABILITY REVIEW No. 27, September 2016

To create more space for recovery and domestic In closing, the FSR is expected to build public economic growth, Bank Indonesia has carefully understanding concerning the importance of honed its macroprudential policy. Accordingly, Bank macroprudential policy to maintain financial system Indonesia adjusted the loan (financing) to value ratio stability (FSS) and how Bank Indonesia formulates and (LTV/FTV) and loan to funding ratio (LFR) pegged to institutes such policy. Furthermore, I hope that the FSR the reserve requirement in order to prevent a further can function as an effective media to communicate credit slump. The various macroprudential policy the implementation of Bank Indonesia’s tasks and measures were reinforced by other policies, including jurisdiction in terms of maintaining financial system a countercyclical buffer of 0% and policy coordination stability. Suggestions, comments and constructive between financial sector authorities, either bilaterally criticisms are warmly welcomed to enhance future or through the Financial System Stability Committee. editions of the Financial Stability Review (FSR).

Jakarta, September 2016 Governor of Bank Indonesia

Agus D. W. Martowardojo

xvi EXECUTIVE SUMMARY

Financial system stability improved during the first half intermediation growth and ultimately exacerbated of 2016 despite the large risks originating from global credit risk and diminished bank efficiency. Meanwhile, and domestic economic moderation. Greater financial global conditions, coupled with deteriorating system stability was evidenced by improvements in corporate, household and banking performance the Financial System Stability Index (FSSI) and Banking reduced government revenues, thus limiting fiscal Systemic Risk Index (BSRI), and supported by a solid space. Less fiscal space, together with nonbank capital base and adequate liquidity in the banking financial industry policy to increase the portion of industry as well as solid financial market performance. government securities (SBN) to a certain percentage, Nonetheless, escalating credit risk along with less bank further undermined deposits and heightened risks at intermediation and efficiency demanded constant certain banks. vigilance. Domestic financial market performance improved, Sluggish global economic growth and soft international primarily supported by an influx of foreign capital to commodity prices undermined domestic economic financial assets, thus improving domestic performance growth. The combination of factors weakened and containing the risks. Consequently, sources of household and corporate performance in nearly funds through the capital market expanded despite all sectors. Consequently, the corporate sector was slower credit growth. The deluge of non-resident less inclined to borrow and save, which slowed bank capital inflows to Indonesia was also linked to less risk

xvii FINANCIAL STABILITY REVIEW No. 27, September 2016

on global financial markets as global uncertainty eased second quarter of 2016, consistent with controlled in line with greater clarity of US policy normalisation inflation, a narrower balance of payments (BOP) deficit and the relatively limited impact of the Brexit. and export growth, as well as rupiah appreciation. Economic growth in the second quarter was supported Global economic growth failed to gain traction in by consumption and investment as public purchasing the first semester of 2016, especially in advanced power improved and the government introduced fiscal countries. The US economy achieved lower-than- stimuli. In the government sector, consumption and expected growth on the back of weak investment investment continued to accelerate despite relatively data. The European economy decelerated, which was limited sources of revenue. compounded by the Brexit referendum. Meanwhile, China’s economy remained beset by private sector Against a backdrop of economic gains, domestic issues, including production at overcapacity and financial imbalances remained. The financial cycle a highly indebted corporate sector. Conversely, continued to contract due to procyclical bank lending emerging market economies (EME) began to show that stifled the bank intermediation function. The risk signs of improvement. The prices of several major of limited future fiscal space also intensified in line with global commodities began to rebound, albeit limitedly, the Government’s fiscal stimulus policy amidst limited due to less supply, for instance oil production in the US sources of government revenue. Nonetheless, the large and other countries declined. flow of foreign capital to domestic financial markets expanded foreign holdings of government securities Risks on global financial markets eased in comparison (SBN) and stocks, which contained the risk of a sudden to the second semester of 2015 due to less uncertainty capital reversal. In addition, many corporations concerning the next FFR hike by the Federal Reserve failed to hedge large debts, leaving them exposed along with the limited impact of the Brexit. Congruent to currency risk. The Government, Bank Indonesia with the sluggish global economy, however, several and other financial authorities strived to unwind the countries maintained an accommodative monetary imbalances through various policy measures. A Tax policy stance. The Fed failed to raise its policy rate, Amnesty was introduced at the end of June 2016, which is now not expected until the end of 2016. which is expected to ease fiscal risk and boost sources Despite heightened market risk towards the middle of of economic financing. Furthermore, Bank Indonesia the year because of the Brexit, only a limited impact also honed its monetary and macroprudential policy on financial market volatility was observed. Less risk mix and deepened the financial markets to mitigate on global financial markets was also evidenced by a the various risks. VIX decline and gains on regional bourses, including the Philippines, Thailand, Vietnam and Indonesia. As global financial market sentiment improved, pressures on domestic financial markets eased The domestic economy began to rebound in the compared to conditions in the previous semester. reporting period despite ongoing global economic Less risk was most notable on the rupiah interbank moderation. Momentum began to accelerate in the money market, foreign exchange market, stock market

xviii and bond market, including government bonds and corporate bond yield volatility was observed to decline corporate bonds. Nevertheless, potential risks in the from 8.94% to 6.10%. form of higher interest rates and volatility on the foreign currency interbank money market required Risks also eased on the stock market as the Jakarta careful observation. Composite Index (JCI) rallied and price volatility decreased as an aggregate and by sector. The Less risk on the rupiah interbank money market consumption, mining and property sectors booked the was reflected in lower interest rates for all tenors. most significant increase of non-resident holdings. In The interbank rate decline was attributed to greater the first semester of 2016, a net inflow of non-resident bank liquidity after the reserve requirement was capital, totalling Rp15.38 trillion, entered the domestic eased and Bank Indonesia lowered its policy rate. stock market. Notwithstanding, the policy to lower interest rates actually heightened rupiah interbank money market In harmony with conventional financial sector volatility. performance, the Islamic financial markets also performed well, primarily the government sukuk On the foreign exchange market, risk dissipated as market and stock market. The positive perception uncertainty eased on global financial markets and held by investors concerning the promising domestic investor perceptions of the promising domestic economic outlook, including the Islamic sector, was economic outlook improved. Consequently, non- evidenced by less volatility and a rally on the Islamic resident capital flows surged to domestic financial stock price index. In addition, low global interest markets, leading to rupiah appreciation and less rates increased incentives for the Government and foreign exchange market volatility. corporate sector to issue sukuk in the first semester of 2016. Meanwhile, lower interest rates and transaction Risks on the SBN market also subsided, reflecting a volume on the Islamic interbank money market bump in the IDMA Index and lower yields, especially (PUAS) were solid indicators of less risk on the Islamic on shorter tenors. Such conditions were indicative of financial markets. mitigated economic risks in Indonesia, which lowered the risk premiums requested by investors. In the first Household and corporate sector performance showed semester of 2016, non-resident SBN holdings increased early signs of improvement despite continuing to to Rp85.47 trillion. Outstanding government SBN decelerate. Stronger economic growth in the second through new issuances in the first semester, catalysed quarter of 2016 left households and the corporate sector trade on the secondary market, hence lowering the increasingly upbeat on future economic conditions. turnover ratio compared to the previous period. Such optimism was confirmed by several surveys conducted by Bank Indonesia. Household optimism Congruent with SBN market performance, risks on the was reflected in the Real Sales Index and Consumer corporate bond market also eased, reflecting lower Confidence Index (CCI), which both improved on the yields for bonds of all ratings. Furthermore, average previous semester. Meanwhile, corporate optimism

xix FINANCIAL STABILITY REVIEW No. 27, September 2016

was confirmed by the Doing Business Survey, which to the corporate sector. In addition, growth of bank revealed an increase in business activities. loans allocated to the corporate sector remained high at 12.13%, compared to just 8.89% for total credit Optimism surrounding economic growth did not growth. Moreover, the gross NPL ratio for the corporate translate into household performance because sector also increased from 2.71% at the end of 2015 consumption was influenced more strongly by seasonal to 3.56% as corporate repayment capacity dwindled. factors during the approach to Eid-ul-Fitr. Household Consequently, an increase was noted in terms of propensity to consume increased in the reporting restructuring offshore corporate loans. Meanwhile, semester, while the portion of household spending corporate deposits also decelerated, from 11.4% in used to repay loans decreased in line with fewer new the second semester of 2015 to 9.95%, consistent with loans extended to the household sector. Personal efforts to pay off and/or repay corporate loans early. (individual) loans, as a proxy of household loans, decelerated from 8.04% (yoy) in the first semester of Sluggish corporate performance had an impact on the 2016 to 7.92% (yoy) in the second. Meanwhile, deposit banking industry, but stability was maintained on a growth among households accelerated as households solid capital base, well above the minimum threshold, were more inclined to save. Household credit risk coupled with increased liquidity despite heightened (NPL) began to increase again in line with seasonal credit risk and slower intermediation growth. Bank trends, reaching 1.75% in the second semester of liquidity was reflected in the liquid assets to deposits 2016 from 1.55% in the previous period and relatively ratio, which increased from 93.44% to 97.40% as the stable from one year earlier. government expanded its accounts at the beginning of the year, the primary reserve requirement was Corporate performance continued to slow. Persistent loosened and credit growth decelerated. global economic moderation eroded demand for exports, therefore, the recent rebound in international Prudent bank lending in the reporting semester, commodity prices failed to have the desired impact against a backdrop of economic moderation and on corporate performance. Declining corporate slower growth of risk-weighted assets (RWA), pushed performance was offset, however, by domestic demand up the Capital Adequacy Ratio (CAR) from 21.39% to as the national economy began to accelerate in the 22.56%. The high level of capital maintained by the second quarter of 2016. The favourable effects were banks increased compliance to Basel III, specifically insufficient though to improve corporate performance. the capital conservation buffer, the countercyclical Several indicators of corporate performance worsened, capital buffer and the capital surcharge for systemically including productivity, profitability, solvency, liquidity important banks, which became effective at the and the debt-to-equity ratio (DER). beginning of 2016.

Waning corporate performance demanded increased Bank intermediation continued to decelerate on vigilance due to the growing portion of loans extended weak demand in line with deteriorating corporate

1 Corporate performance is based on the financial statements of public listed companies through to the second quarter of 2016. xx performance that undermined demand for new loans. the reporting semester. Furthermore, the cost-to- On the supply side, banks were less inclined to lend income ratio (CIR) declined from 59.47% to 56.20% by imposing more stringent lending standards due to in the first semester of 2016 as net interest income rising non-performing loans (NPL). In the first semester and non-interest income outstripped non-interest of 2016, credit growth stood at 8.89% (yoy), down expenses. Disparate CIR and BOPO trends showed from 10.45% (yoy) in the previous semester. Bucking that declining bank efficiency was more the result of the overall trend of credit growth, loans extended interest activity. to micro, small and medium enterprises (MSMEs) accelerated from 8.0% (yoy) to 8.3% (yoy) in the same Congruous with the slowdown reported in the period due to greater allocation of microfinance (KUR) conventional banking industry, Islamic banking subsidised by the Government. Deposit growth in sector growth also experienced a deeper decline, the banking industry also slowed from 7.26% (yoy) accompanied by rising financing risk that began to to 5.90% (yoy) on weaker corporate performance, a erode profitability and capital. Notwithstanding, shift in the deposits of the nonbank financial industry Islamic banks maintained adequate liquidity. to government securities (SBN) as well as a decline in local government funds held in the banking industry. The nonbank financial industry performed positively A further decline in deposit growth at the end of the but growth remained low. Financing from finance first semester of 2016 also coincided with seasonal companies began to recover in line with the increase withdrawals of Currency Outside Banks (COB) for in funding. Furthermore, the insurance industry also Ramadan. In terms of credit risk, the upward gross began to rebound, reflecting growth of assets and NPL trend persisted, rising to 3.05% from 2.46% in the investment. In terms of risk, however, non-performing first semester of 2015 and from 2.49% in the second financing (NPF) at finance companies did increase, semester of 2015. Credit risk increased as repayment while business risk in the insurance industry was capacity decreased, coupled with low incomes. noted to dissipate, indicated by an increase in the ratio By economic sector, the most significant spike in of premiums to claims. non-performing loans (NPL) affected the mining, transportation and telecommunications as well as Concerning financial system infrastructure, the manufacturing sectors. payment system was secure, reliable and efficient during the reporting period, which helped to maintain Despite slower credit growth and higher cost reserves monetary and financial system stability as well as in the banking industry due to rising NPL, banks facilitate economic activities. Such conditions reflect maintained profitability, with the ROA stable at the success of Bank Indonesia policy to constantly 2.31%, by increasing the net interest margin (NIM). enhance payment system performance. The BI- Nonetheless, bank efficiency deteriorated due to rising operated payment system contained low settlement operating and reserve costs. Consequently, the BOPO and liquidity risks, met the reliability and availability efficiency ratio worsened from 81.49% to 82.23% in targets and provided payment infrastructure for retail

xxi FINANCIAL STABILITY REVIEW No. 27, September 2016

services and large-value transactions. Meanwhile, the and second semester of 2015 revealed that potential industry-operated payment system experienced a rise systemic risk in the BI-RTGS system increased in the of noncash payment instruments, while reliability was first semester of 2016 but was still below that recorded maintained. one year earlier.

Solid performance was inextricably linked to Bank Public access and utilisation of financial services in Indonesia policies and regulations to mitigate risk and Indonesia tended to increase in the reporting period, enhance operational performance, while developing indicated by a higher Financial Inclusion Index and payment system infrastructure and conducting uptake of digital financial services (DFS). DFS uptake supervision. In the first semester of 2016, Bank was reflected by a growing number of agents, coupled Indonesia released Central Bank Money (CeBM) for with more e-money transactions through those agents settlement of securities transactions on the capital in line with greater public utilisation of bank branches, market, introduced electronic and online demand ATM machines, DFS agents and bank accounts, while deposit management services for strategic partners the value of deposits and loans also increased. (the government, banks, international institutions and other institutions) known as the Bank Indonesia Bank Indonesia maintained accommodative and Government Electronic Banking System (BIG-eB) and countercyclical macroprudential policy during the developed the second generation, Phase II, National first semester of 2016 in order to stimulate bank Clearing System (SKNBI) with a bulk payment feature. intermediation and, thus, support economic growth while prioritising systemic risk mitigation. Based on Payment system risk was well mitigated, including a Bank Indonesia assessment, the LTV ratio and RR- settlement risk, liquidity risk, operational risk and LFR policy issued in the first semester of 2016 staved systemic risk. Low settlement risk was evidenced by off a further decline in the growth of new loans. the low value and volume of unsettled transactions Furthermore, credit growth, specifically property in the Bank Indonesia – Real Time Gross Settlement loans, began to rebound but remained limited due to (BI-RTGS) system. Similarly, no banks requested the a time lag in the transmission of policies. Intraday Liquidity Facility (ILF) during the reporting period, which was indicative of low liquidity risk, while To create economic growth momentum, the the Business Continuity Plan (BCP) helped the banks aforementioned policies were accompanied by further to mitigate and control operational risks by providing adjustments to the LTV/FTV ratios, while honing the a back-up system to replace the main system in its RR-loan to funding ratio (RR-LFR). In addition, Bank entirety. Systemic risk was observed to increase but Indonesia reiterated the 0% CCB due to the ongoing remained at a low level. Systemic risk is measured in contractionary financial cycle, macroeconomic factors terms of interconnectedness in the BI-RTGS system by as well as bank and market assets. counting the number of counterparties of each RTGS participant. A comparison of 10 banks with the largest Maintaining financial system stability, Bank Indonesia number of counterparties in the first semester of 2016 strengthened coordination with the Government and

xxii other relevant authorities bilaterally and through the Financial System Stability Committee. Coordination was also strengthened through promulgation of Act No. 9 of 2015 concerning Financial System Crisis Prevention and Handling, which became effective on 15th April 2016. The macroprudential policy represents part of the overall policy mix instituted by Bank Indonesia, including lowering the BI Rate and reformulating the Bank Indonesia policy rate transmitted to bank interest rates. Regarding the payment system and circulation of currency, Central Bank Money (CeBM) was introduced for transaction settlement on the capital market to support financial market deepening, the National Clearing System (SKNBI) was developed further and digital financial services (DFS) were expanded and socialised to the public.

xxiii

Financial system stability improved during the first semester of 2016 despite large global and domestic risks. The Financial System Stability Index (FSSI) improved to 0.95, primarily as risks eased on global financial markets and the banks maintained a solid capital base. The global economy posted moderate gains despite lower-than-expected growth in advanced economies and low international commodity prices, even after starting a modest rebound. Furthermore, shocks on global financial markets from the Brexit referendum in the UK were mild. Additionally, market risk dissipated in the reporting period as uncertainty surrounding the next FFR hike eased.

Against a backdrop of stronger national economic growth, domestic financial imbalances persisted in the form of a contractionary financial cycle, procyclical bank lending and increasingly limited fiscal space. In addition, non-residents maintained large holdings on domestic financial markets, which strengthened the markets but heightened the risk of a sudden capital reversal.

FINANCIAL SYSTEM 1STABILITY FINANCIAL STABILITY REVIEW No. 27, September 2016

ISSK Financial system stability improved in the first semester of 2016 despite large global and domestic risks

Domestic Economic Conditions: • Economy beginning to rebound in the second quarter of 2016; • Inflation controlled; Global Conditions: • BOP deficit • Persistently sluggish global economic growth; improving; • Economic growth beginning to accelerate in emerging market economies (EME); • Rupiah appreciation • Persistently low international commodity prices despite several commodities starting and solid financial to rebound; markets. • FFR hike expected sometime in the second semester of 2016; • Mild Brexit impact.

Nonbank Private $ Rp Limited Fiscal Space External Debt

Domestic Financial Imbalances

Non-Resident Procyclical SSB Holdings Bank Lending

Financial System Stability Remains Solid

2.0

0.93

0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

FSSI Crisis

4 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

1.1. Global and Regional The sluggish global economic recovery compelled Financial Market Risks several countries to maintain a loose monetary policy stance. The Federal Reserve has postponed raising Global and regional economic growth remained the Federal Funds Rate (FFR) any further because US limited during the first half of 2016, while global economic data, thus far, is not yet solid. The timing financial market risks eased despite a temporary spike of the FFR hike is now not expected until the second in volatility. Global economic growth did not improve semester of 2016 and of a smaller magnitude. In in line with lower-than-expected growth reported in addition, several countries applied negative interest the United States along with limited growth in China rates, including the Bank of Japan (BOJ), Riksbank and Europe (Table 1.1). Investment was the main drag and the Swiss National Bank. On the other hand, the on US growth, while Europe was overshadowed by impact of the Brexit referendum, which overshadowed the Brexit referendum in the UK that eroded market the economy of Europe, was relatively transient. confidence. On the other hand, public investment in Consequently, uncertainty on global financial markets China failed to catalyse the indebted private sector eased in the first semester of 2016 (Graph 1.2). operating at overcapacity.

Table 1.1. Global Economy Outlook

Global Economy Outlook 2015 2016 IMF Consensus Forecast BI Consensus Forecast BI Realisasi IMF Oct Dec Dec Jul May Global 3.1 3.2 3.1 3.1 3.1 3.2 3.1 Amerika Serikat 2.6 2.4 2.6 2.5 2.2 1.9 2.0 Eropa 1.5 1.5 1.5 1.5 1.6 1.5 1.5 Jepang 0.6 0.6 0.6 0.6 0.3 0.5 0.5 Tiongkok 6.8 6.9 6.8 6.9 6.6 6.3 6.5 India 7.3 7.5 7.3 7.3 7.4 7.6 7.5

Sumber: Bloomberg

International commodity prices began to rebound Consistent with easing uncertainty, global stock despite the sluggish global economic recovery. The markets also rallied despite growth remaining in world oil price increased but remained low. The price of negative territory. A lower VIX index was indicative of Brent at the end of the first semester of 2016 increased less uncertainty in the first semester of 2016, while to USD48.6 per barrel after supply disruptions were the stock markets in several developing countries, reported in several countries and US production was including the Philippines, Thailand, Vietnam and reduced (Graph 1.1). Congruently, CPO and coal prices Indonesia reversed the negative growth recorded in also increased on supply factors and more expensive the previous semester. substitutes for CPO, while coal prices benefitted from China curbing supply.

5 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 1.1. Brent Oil Price Performance Graph 1.2. Commodity Price Indexes for CPO, Rubber and Coal

USS/barel 70 Rebased 1/1/13 140 65 USD Appreciation

60 120

55 100 Brexit 50 Increased OPEC Production 80 45

40 Iran Nuclear 60 Deal 35 Repeat OPEC 40 Quota Fixed CPO Rubber Coal 30 Yuan Devaluation Iran Exports 20 25 Expected to Increase 20 0 Oct-1 Oct-1 Oct-1 Apr-1 Apr-1 Apr-1 Apr-1 Jul-13 Jul-14 Jul-15 Jul 15 Jan-16 Jan-13 Jan-15 Jan-15 Jun-16 Jan 15 Jan 16 Jun 15 Jun 16 Oct 15 Feb 15 Feb 16 Apr 15 Sep 15 Apr 16 Mei 15 Mei 16 Dec 15 Nov 15 Mar 15 Mar 16 Aug 15

BRENT SPOT Monthly Average Source: Bloomberg Source: Bloomberg

Graph 1.3. CDS in Advanced Countries and the Region

Thailand

Philippines

Jun-16 Malaysia Dec-15 Indonesia

China

Turkey

Germany

Brazil

100 200 300 400 500 600

Source: Bloomberg

Graph 1.4. JCI and Global Indexes Graph 1.5. VIX Index

45 World FOMC : EM Asia 40 25bps FFR Hike US (Dow Jones) Japan (Nikkei) 35 England (FTSE) India (SENSEX) 30 Hong Kong (Hangseng) 25 Sanghai (SHCOMP) Strait Times (STI) 20 Kuala Lumpur (KLCI) Philipines 15 Thailand (SET) Vietnam 10 Indonesia (JCI)

% 1-Jul 1-Jan 1-Jun 1-Jun 1-Oct 1-Feb 1-Sep 1-Apr 1-Apr 1-Dec 1-Nov 1-Mar 1-Aug 1-May -25 -20 -15 -10 -5 0 5,0 10 15 20 1-May Semester II 2015 Semester I 2016

Source: Bloomberg Source: Bloomberg

6 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

account deficit reduced from 2.39% of GDP in the 1.2. Domestic Financial Market Risks fourth quarter of 2015 to just 2.02% of GDP in the second quarter of 2016. Meanwhile, the capital and financial account surplus was bolstered by the positive Domestic economic risks eased during the first half of perception of investors concerning the promising 2016. Macroeconomic stability was maintained, with domestic economic outlook, including sentiment low inflation, a narrower current account deficit and linked to the tax amnesty, and less uncertain global a stable but appreciating exchange rate. Furthermore, financial markets (Graph 1.6). less global risk also supported efforts to mitigate risks in the domestic economy. Inflation was controlled within The rupiah was stable and tracked an appreciating the target corridor for 2016, namely 4±1%. Accordingly, trend due to the perceived favourable domestic inflation at the end of the first semester of 2016 was economic outlook in line with monetary policy recorded at 3.45% (yoy), accelerating modestly from easing, fiscal stimuli, sentiment surrounding the tax 3.35% (yoy) at the end of the first semester of 2015. amnesty as well as the accelerated implementation Low core inflation, stemming from limited domestic of economic policy packages and infrastructure demand, rupiah appreciation and anchored inflation projects. Furthermore, less uncertain global financial expectations, helped to control headline inflation markets due to the postponement of the FFR hike within the target corridor. Furthermore, inflationary by the Federal Reserve and minimal fallout from the pressures on volatile foods (VF) and administered Brexit maintained a net inflow of foreign capital to prices (AP) were also controlled. domestic financial markets. Consequently, the rupiah appreciated throughout the first semester of 2016. The balance of payments (BOP) recorded a surplus Point to point, the rupiah strengthened 2.74% (ptp) to at the end of the first semester of 2016, supported close at a level of Rp13,213 per USD at the end of the by a narrower current account deficit and growing first semester of 2016. In addition, rupiah volatility at capital and financial account surplus. The current the end of the reporting period was lower than that

Graph 1.6. Inflation and GDP Growth Graph 1.7. Balance of Payments (BOP) in 2015

7 % % 10 20,000 Miliar dolar AS % 0 9 -0.5 6 15,000 8 -1 5 7 10,000 -2 4 6 5,000 -2.5 5 3 0 4 -3

2 3 -5,000 -3.5 2 -10,000 -4 1 1 -15,000 -4.5 0 0 01 02 03 04 01 02 03 04 01 02 03 04 01 02 Jan Mar May Jun Sep Nov Jan Mar May Jun Sep Nov Jan Mar May Jun Sep Nov Jan Mar May Jun 2013 2014 2015 2016 2013 2014 2015 2016 Capital and Financial Account Current Account GDP Growth Inflation (rhs) Current Account (% of GDP) (rhs)

Source: Bank Indonesia Source: Bank Indonesia

7 FINANCIAL STABILITY REVIEW No. 27, September 2016

reported in several peer countries, including South ul-Fitr celebrations were also a boon to household Africa (rand), Brazil (real), Malaysia (ringgit), Turkey consumption. Meanwhile, the government was (lira) and South Korea (won). more inclined to spend, thus boosting consumption in the second quarter of 2016. On the other hand, Economic growth moderated in Indonesia during despite limited investment growth in general, non- the first quarter of 2016, which exacerbated risk. construction investment began to recover on growing The economic slowdown was attributed to limited domestic demand. Furthermore, government government consumption and investment growth. investment in infrastructure projects remained Government consumption slowed due to seasonal strong. Externally, export performance improved due factors, namely limited spending at the beginning of to several commodities but a shallower contraction the year. Meanwhile, investment activities remained persisted overall. weak despite efforts to accelerate government infrastructure projects. In contrast, robust household At the end of the first semester of 2016, enforcement consumption growth was maintained on low prices. of the Tax Amnesty1 curbed concerns over fiscal Externally, exports of several commodities showed risks. Limited state revenues, against a backdrop of early signs of improvement, which raised the increased government spending, stoked concerns performance of exports overall despite the ongoing over the consistency of fiscal stimuli. Implementation contraction. of the Tax Amnesty, however, is expected to enhance fiscal capacity to finance development programs. Economic risks began to disperse as the economy In addition, the amnesty should bolster national rebounded in the second quarter of 2016. National economic liquidity to fund productive economic economic growth accelerated on the back of activities at home. Supporting such conditions, Bank consumption and investment, coupled with monetary Indonesia will continue to deepen financial markets and macroprudential policy easing along with by expanding investment and hedging products, fiscal stimuli. Household consumption accelerated strengthening monetary management and urging the as public purchasing power improved in line with real sector to optimise repatriated funds. controlled inflation. In addition, preparations for Eid-

1 Act No. 11 of 2016 concerning the Tax Amnesty

8 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 1.8 Rupiah Exchange Rate Graph 1.9 Rupiah Appreciation and Depreciation against the US Dollar YTD 2016* VS 2015 14200 IDR/USD Monthly Average Quarterly Average Point to point Average

7.07 14000 BRL -9.82 1.33 ZAR -17.20 13800 4.72 MYR -4.70 2.74 IDR -0.18 13600 13525 -0.59 KRW -4.30 1.64 13400 13313 THB -3.39 2.24 EUR 0.57 13200 13213 0.05 PHP -2.88 -1.60 Data s.d. 30 Jun 2016 INR data s.d. 30 Jun 2016 13000 -4.59 0.16 TRY -6.69 4-Jan 6-Jun 1-Feb 9-Feb 7-Apr 1-Mar 8-Mar 9-May 11-Jan 18-Jan 25-Jan 13-Jun 20-Jun 27-Jun 16-Feb 23-Feb 14-Apr 21-Apr 28-Apr 16-Mar 23-Mar 31-Mar 16-May 23-May 30-May -20.00 -15.00 -10.00 -5.00 0.00 5.00 10.00 Source: Bloomberg Source : Bloomberg

Graph 1.10 Annual Rupiah Volatility Graph 1.11 Net Flows of Non-Resident Capital

USD mn Stock SUN SBI IDR/USD (RHS) IDR/USD 30 % 4000 15,000 3000 14,000 2015 2000 25 13,000 1000 YTD 2016 0 12,000 Average YTD 2016 -1000 20 11,000 -2000 10,000 Data s.d. 30 Jun 2016 -3000 15 -4000 9,000 Jun 16 Jun 15 Jun 14 Jun 13 Oct 15 Oct 14 Oct 13 Feb 13 Feb 16 Feb 15 Feb 14 Apr 16 Apr 15 Aor 14 Apr 13 Dec 15 Dec 14 Dec 13 Aug 15 Aug 14 Aug 13 10 Source: Bank Indonesia, BEI, Bloomberg

5 Jan- Feb- Mar- Apr- Mei- Jun- YTD- QQ2-15 Q3-15 Q4-15 2015 Q1-16 Q2-16 -16 16 16 16 16 16 16

0 Stock -1.252 -1.201 -325 -2.345 -167 304 175 313 22 -14 660 669 982 ZAR BRL MYR TRY KRW IDR SGD PHP THB INR SUN 2.260 -453 2.598 7.608 1.301 721 1.276 3.298 1.180 -358 1.848 2.671 5.969

SBI 181 -193 1 -135 0 22 46 68 259 -272 262 250 318

Source: Bank Indonesia Total 1.189 -1.847 2.274 5.127 1.134 1.047 1.498 3.679 1.462 -643 2.771 3.589 5.051

Source: Bank Indonesia

9 FINANCIAL STABILITY REVIEW No. 27, September 2016

BSRI stood at a level of 1.67, which is well below the 1.3. Financial System Stability crisis threshold of 3.8. BSRI remained stable within the in Indonesia normal zone due to less liquidity risk, capital risk, SBN risk and currency risk, while credit risk was observed Financial system stability in Indonesia improved during to escalate. Risk identified by the BSRI was congruent the first half of 2016 as domestic and global financial with that indicated by the FSSI. market risks eased. Consequently, the Financial System Stability Index (FSSI) remained in the normal The sluggish global economy, combined with less zone at 0.95 (threshold of 2.0), down from 1102 at risk on global financial markets and the domestic the end of the second semester of 2015. Financial economic recovery underpinned financial system system stability was maintained on a solid capital momentum. The transmission of less risk through base, increasing liquidity and maintained financial the trade channel experienced a lag due to weak markets despite heightened credit risk and lower bank demand and limited commodity price gains, which efficiency. stifled commodity-oriented corporate performance. Ultimately, such conditions spilled over to undermine The Financial System Stability Index (FSSI) is a bank intermediation and elevate credit risk, while composite of the Financial Institution Stability Index simultaneously placing pressures on government (FISI)3 and Financial Market Stability Index (FMSI)4. FISI finances, primarily in terms of state revenues, which indicated an increase of risk, while the FMSI improved. limited fiscal space. The higher FISI was prompted by decelerating intermediation growth, escalating credit risk and The impact of financial system momentum through lower efficiency. Nonetheless, stronger bank capital the financial markets was felt in the stock market, and liquidity offset the FISI increase. FMSI tracked an bond market and the rupiah exchange rate. Positive improving trend, however, due to less liquidity risk on sentiment was further bolstered by expectations financial markets, lower bond yields and stock market regarding implementation of the Tax Amnesty, which volatility as well as a decline of credit default swaps was expected to expand sources of financing for the (CDS) and smaller ratio of external debt to GDP. domestic economy. The temporary and limited impact of the Brexit referendum, coupled with the estimated In addition to the FSSI, the Banking Systemic Risk Index postponement of the FFR hike, which mitigated risks (BSRI) is another indicator used to identify systemic on global financial markets, also led to less risk on risk in the financial system. BSRI shows the magnitude domestic financial markets. Such conditions triggered of the banking sector’s contribution to systemic risk a deluge of capital inflows to the domestic economy in the financial system on an individual bank basis. during the first half of 2016. BSRI is a composite index consisting of several sub- indexes, namely credit risk, liquidity risk, currency risk, On the stock market, the Jakarta Composite Index SBN risk and capital risk. In the first semester of 2016, (JCI) rallied 9.22% on the previous period to close at a

2 Bank Indonesia revisited the Financial System Stability Index (FSSI) in the first semester of 2016, specifically the components of the Financial Market Stability Index (FMSI). The FSSI value prior to the revisit at the end of the second semester of 2015 was 0.93. 3 The components of FISI include a pressure indicator, intermediation indicator and an efficiency of financial institutions indicator, particularly banks. 4 FMSI is a composite of various financial market indicators, namely the money market, bond market, stock market, foreign exchange market, credit default swaps (CDS) and external.

10 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

level of 5,016.6, mirroring the prevailing trend of most Bank intermediation continued to decelerate, with bourses in the region. Positive sentiment prompted credit and deposit growth slowing respectively. non-resident investors to book a net buy on the stock Declining bank intermediation was also linked to market totalling Rp13 trillion in the first semester of reduced corporate repayment capacity along with 2016. The SBN market also followed suit, with the less business expansion and investment activity, IDMA index climbing from 93.33 to 101.77 and foreign which eroded corporate performance. Credit growth investors booking a net inflow of Rp85.5 trillion. further decelerated to a level of 8.89% (yoy) in the Furthermore, the exchange rate appreciated 4.35% first semester of 2016 from 10.45% at the endof from Rp13,175 per USD at the end of December 2015 2015. Additionally, slower credit growth was also to Rp13,210 at the end of June 2016. accompanied by increasing credit risk, as reflected by an increase in gross non-performing loans (NPL) Banking sector stability was maintained due to solid from 2.49% in the second semester of 2015 to 3.05% capital and adequate liquidity despite intermediation in the reporting period. Deposit growth also tracked a decelerating as performance deteriorated. The Capital downward trend, decelerating from 7.26% at the end of Adequacy Ratio (CAR) stood at 22.29% at the end of 2015 to 5.90% in the first semester of 2016, due to the the first semester of 2016, up from 21.16% at yearend impact of the nonbank financial industry mandatorily 2015. The CAR bump was in line with slower credit converting a portion of funds to government securities growth, which impacted risk-weighted assets (RWA) (SBN), bank policy to reduce expensive funds and and led to additional capital at several large banks, currency withdrawals during Eid-ul-Fitr. especially state-owned banks. Furthermore, bank liquidity was also observed to increase, despite large- In terms of efficiency, the BOPO efficiency ratio scale withdrawals of currency during the approach to decreased on the previous semester from 84.47% Eid-ul-Fitr, as the government expanded its accounts, to 82.20% because of improvements to the spread Bank Indonesia loosened the primary RR and limited margin stemming from a decline in the cost of funds credit growth remained in the first semester. Bank that outstripped the credit decline. On the other hand, liquidity was also evidenced by the liquid assets to banks maintained stable profitability, with the return deposits ratio, which increased from 19.44% to 20.3% on assets (ROA) recorded at 2.26% in December 2015 in the reporting period. and again in June 2016.

Graph 1.12. Financial System Stability Index Graph 1.13. Financial Institution Stability Index

2.00

2.00

0.00 0.00 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

FSSI Crisis FISI Crisis

Source: Bank Indonesia

11 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 1.14. Financial Market Stability Index Graph 1.15. Banking Systemic Risk Index

4.5

4.0

3.5

3.0 2.0 2.5

2.0 1,67 1.5

1.0

0.5

0,0 0.0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV IV II

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 FSSI Crisis BSRI 1% percentile Source: Bank Indonesia Source: Bank Indonesia

Graph 1.16. Composite Stock Price Indexes in Several Countries

180 230

210 160 190 140 170

120 150

100 130 110 80 90 60 70

40 50 Jan-13 Jul-13 Feb-14 Sep-14 Apr-15 Nov-15 Jun-16 Jan-13 Jul-13 Feb-14 Sep-14 Apr-15 Nov-15 Jun-16

Hong Kong China South Korea Indonesia Malaysia

Source: Bloomberg

Graph 1.17. Asset Share of Financial Institutions

2.67% 5.88% Commercial Banks Guarantee Companies 10.59% Rural Banks Pawn Brokers

2.54% Islamic Banks Indonesia Eximbank

Insurance Companies Sarana Multi Finance (SMF)

Pension Funds Islamic Microfinance Institutions

Finance Companies KSP/USP

74.93% Venture Capital Firms

Source: Financial Services Authority (OJK)

12 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

a moderate recovery at the end of the second quarter. 1.4. Domestic Financial Imbalances Low bank intermediation was the result of aggregate demand, reflected by sluggish economic growth, despite increasing in the second quarter from 4.91% to Domestic financial imbalances deepened in the 5.18% (yoy). first half of 2016 despite contagion risk from China easing. The contractionary phase of the Procyclical bank lending was also confirmed by financial cycle also deepened due to slower bank adjustments to the bank balance sheet through more intermediation growth. Credit and deposit growth stringent lending requirements and prudent lending, both decelerated in line with weak private sector supported by loan restructuring and write-offs to stem demand and sluggish GDP growth in the first the decline of credit growth. Nonetheless, declining loan semester. Furthermore, increased government quality eroded bank profitability throughout the first spending failed to stimulate demand for new loans. semester of 2016. Furthermore, declining loan quality Against a backdrop of increasingly limited sources compelled the banks to become more selective when of revenue, increased government spending lending and to focus on certain quality economic sectors reduced future fiscal space. Notwithstanding, and borrowers. Such conditions were compounded enforcement of the Tax Amnesty on 1st July 2016 by weak households and corporations, which were reignited optimism on the fiscal side. subsequently reluctant to invest and prioritised debt repayment and operating costs. In general, the Imbalances also originated from large non-resident problems facing borrowers acting simultaneously as holdings of securities on domestic financial markets. producers and consumers will influence the financing chain in the real sector. In the reporting semester, positive sentiment due to the tax amnesty triggered an influx of foreign inflows as a source of economic financing. The 1.4.2. Limitations to Fiscal Space non-resident holdings could, however, exacerbate The state budget recorded a growing deficit in the market risk and liquidity risk in the financial sector first semester of 2016 in line with lower revenues and in the event of a capital reversal. In addition, the increased government spending. Nevertheless, the high portion of private external debt has left the state budget deficit remained under control, supported sector exposed to global factors. The financial by various government efforts to increase revenues imbalances influenced the speed and magnitude of and reduce spending. Therefore, the Tax Amnesty was the spillover effect of global and domestic factors enacted in the first semester of 2016 to boost state on financial system stability. revenues.

1.4.1. Procyclical Bank Lending and the Financial The realisation of state revenues in the first semester of Cycle Contraction 2016 reached 35.5% of the target for 2016 compared The financial cycle in Indonesia remained ina to 37.9% one year earlier. Lower budget realisation contractionary phase at the end of the second semester was due primarily to less excise receipts, oil and gas of 2016 due primarily to weaker credit growth despite income tax revenues as well as non-tax revenues as

13 FINANCIAL STABILITY REVIEW No. 27, September 2016

a result of suboptimal domestic economic growth, 1.4.3. Increasing Nonbank Corporate External Debt global economic moderation that squeezed export and Risk import activities, low global crude oil prices, dwindling Indonesia’s external debt position continued to demand from advanced countries and low international accelerate, with growth increasing from 5.99% (yoy) to commodity prices, especially coal. 6.28% (yoy) in the reporting period. Congruently, the ratio of external debt to GDP also increased, accelerating The government was more inclined to spend during the from 36.05% in the second semester of 2015 to 36.82%, reporting period, while revenues remained limited. The which heightened sensitivity to rupiah depreciation. realisation of government spending in the first semester of 2016 reached 41.5% of the ceiling per the 2016 state Based on borrower group, private external debt budget, exceeding the 37.9% posted one year earlier. continued to exceed that of the public sector, with Greater spending realisation was the result of increased a nominal value of USD165,092 billion, equivalent

Graph 1.18. The Financial Cycle and Bank Lending Procyclicality

1998Q2 2007Q2 0.08 0.02 1995Q2Q2 40.0 8.0 0.06 2005Q2Q2 0.02 35.0 7.0 0.04 0.01 30.0 6.0 2013Q3 0.02 0.01 25.0 5.0 0 4.0 - 20.0 2014Q2 (0.02) 1993Q4 1994Q2 1994Q4 1995Q2 1995Q4 1996Q2 1996Q4 1997Q2 1997Q4 1998Q2 1998Q4 1999Q2 1999Q4 2000Q2 2000Q4 2001Q2 2001Q4 2002Q2 2002Q4 2003Q2 2003Q4 2004Q2 2004Q4 2005Q2 2005Q4 2006Q2 2006Q4 2007Q2 2007Q4 2008Q2 2008Q4 2009Q2 2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q4 2015Q2 2015Q4 15.0 3.0 2009Q3Q2 (0.01) (0.04) 10.0 2.0 (0.01) (0.06) 5.0 1.0 (0.01) (0.08) 2000Q2Q2 0.0 0.0 (0.10) (0.01) 1998Q2 2009Q3 200102 200104 200202 200204 200302 200304 200402 200404 200502 200504 200602 200604 200702 200704 200802 200804 200902 200904 201002 201004 201102 201104 201202 201204 201302 201304 201402 201404 201502 201504 201602 Financial Cycle (BPF/lhs) Business Cycle (BPF/lhs) FC Trough Crisis FC Peak GDP Growth (%, rhs) Credit Growth (%, yoy)

Source: Bank Indonesia Source: Bank Indonesia

absorption of central government spending and intense to 50.99% of total external debt at USD323,789. monitoring of the absorption by the State Budget Most private external debt was held by the nonbank Realisation Evaluation and Supervision Team. Spending corporate sector, accounting for USD134,815 billion or was also accelerated through the absorption of budget 81.66% of total private external debt. In comparison, transfers to local governments and village funds, the banking sector accounted for USD30,277 billion or which involved a fundamental change in the structure, 18.34% of the total. classification and scope of local transfers as well as change to the pattern of village fund disbursements, Nonbank private external debt originated from nonbank namely to two per annum. financial institutions and non-financial corporations. Differing from the composition of public external debt,

5 A more detailed discussion on banking conditions is presented in the Chapter on the Assessment of Conditions and Risks in the Banking and Nonbanking Industries. 6 A more detailed discussion on banking conditions is presented in the Chapter on Assessment of Conditions and Risks in the Household and Corporate Sectors.

14 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

growth of nonbank private external debt fell to -2.65% contained a large share of non-resident holdings, (yoy) in the first semester of 2016. Based on original which increased liquidity, deepened the markets and maturity, nonbank private external debt contained increased capital market capitalisation. Conversely, less potential risk because the majority was long term, large non-resident holdings of domestic financial for which growth declined from 6.58% (yoy) at the assets also triggered potential risk of a sudden capital end of 2015 to -4.11% (yoy) in the reporting period. reversal as well as trade fluctuations. The risk of capital In contrast, short-term nonbank private external debt reversal could trigger market sentiment like the UK accelerated from -18.77% (yoy) to 6.08% (yoy) over the Brexit referendum at the end of June 2016, domestic same period. In terms of corporate repayment capacity, economic fundamental factors and global risks from the risk remained high, particularly for commodity-oriented FFR hike. companies, in line with global economic moderation. Accordingly, the debt service ratio (DSR) remained On the SBN market, non-resident holdings accounted comparatively high at 37.28%, despite decreasing for 39% of the total in June 2016. External factors, slightly on the previous period. including relatively contained spillover from the Brexit and the expected delay to the next FFR hike, lowered Hedging is used to mitigate external debt risk but, SBN yields for all tenors in the first semester of 2016. according to the Prudential Principles Activity Report, Sentiment drove an increase of net inflow to the SBN corporations are still not hedging in compliance with market, reaching Rp85.47 trillion in June 2016, which the minimum requirements. Based on the report expanded foreign SBN holdings. conducted in the first semester concerning the hedging ratio for 0-3 months, of the 435 respondents with a In line with the SBN market, the stock market also net foreign currency liability amounting to USD6,727 rallied, as was reported by other countries in the million, as many as 285 respondents failed to meet the region. The Jakarta Composite Index (JCI) rallied 9.22% hedging standards with a shortfall of USD829 million. to close at a level of 5,016.6 at the end of the first Regarding the hedging ratio for 3-6 months, of the semester of 2016. Non-resident investors booked a 227 respondents with a net foreign currency liability net buy of Rp15.38 trillion, up 0.265 on the previous totalling USD3,616 million, 188 respondents failed to semester with holdings accounting for 63.79% of meet the regulations with a shortfall of USD819 million. total stock market capitalisation. Differing from the market structure for government securities (SBN) and 1.4.4. Large Non-Resident Holdings on Domestic stocks with large foreign holdings, the Bank Indonesia Financial Markets Certificates (SBI) market was dominated by domestic Financial markets in Indonesia were stable through to holdings, accounting for 95% in the first semester of the first semester of 2016, with performance improving. 2016 due to holding period requirements. Nonetheless, the structure of the financial markets

15 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 1.19 External Debt Composition by Debtor to GDP

Government + Central Government + Private USD Billion Bank and Private Central Bank USD Billion 180 35 Private 160 30 Bank (rhs) 140 Government + CB Government 25 120 Non Bank Corporation 100 20

80 15 Central Bank (rhs) 60 10 40

20 5

0 0 Jun 12 Jun 13 Jun 14 Jun 15 Jun 12 Jun 13 Jun 14 Jun 15 Jun 12 Jun 13 Jun 14 Jun 15 Jun 09 Jun 10 Jun 11 Jun 09 Jun 10 Jun 11 Jun 09 Jun 10 Jun 11 Jun 08 Jun 08 Jun 08 Dec 13 Dec 14 Dec 15 Dec 16 Dec 13 Dec 14 Dec 15 Dec 16 Dec 13 Dec 14 Dec 15 Dec 16 Dec 08 Dec 09 Dec 10 Dec 11 Dec 08 Dec 09 Dec 10 Dec 11 Dec 08 Dec 09 Dec 10 Dec 11 Dec ‘11 Dec ‘11 Dec ‘11

Source: External Debt Statistics, Bank Indonesia

% % 60 8

50 7

40 36.82 6 30 5 20 5.18 4 10

3 0 6.28

-10 2 Jun ‘04 Jun ‘05 Jun ‘06 Jun ‘07 Jun ‘08 Jun ‘09 Jun ‘10 Jun ‘11 Jun ‘12 Jun ‘13 Jun ‘14 Jun ‘15 Jun ‘16 Sep ‘05 Sep ‘06 Sep ‘07 Sep ‘08 Sep ‘09 Sep ‘10 Sep ‘11 Sep ‘12 Sep ‘13 Sep ‘14 Sep ‘15 Sep ‘04 Dec ‘04 Dec ‘05 Dec ‘06 Dec ‘07 Dec ‘08 Dec ‘09 Dec ‘10 Dec ‘11 Dec ‘12 Dec ‘13 Dec ‘14 Dec ‘15 Mar ‘05 Mar ‘06 Mar ‘07 Mar ‘08 Mar ‘09 Mar ‘10 Mar ‘11 Mar ‘12 Mar ‘13 Mar ‘14 Mar ‘15 Mar ‘16 Mar ‘04

External Debt to GDP (%) External Debt Growth (yoy, rhs) GDP Growth (yoy, rhs)

Source: CEIC and External Debt Statistics, June 2016, Bank Indonesia

Graph 1.20 Nonbank Private External Debt based on Graph 1.21 Debt Service Ratio (DSR) Original Maturity

% USD Miliar % 70 160 40.0 60 37.28% 140 35.0 50 30.0 29.89 120 40 25.0 30 100 20.0 15.0 20 80 10.0 10 60 7.39 5.0 0 40 0.0 -10 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 -20 20 2014 2015 2016 -30 0 Jun Des Jun Des Jun Des Jun Des Jun Des Jun Des Jun Des Jun 2009 2010 2011 2012 2013 2014 2015 2016 Total DSR Tier-1 Public DSR Tier-1 Private DSR

Short Term(rhs) Long Term (rhs) Short-Term External Debt Long-Term External Debt Growth Growth

Source: Bank Indonesia Source: Bank Indonesia

16 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 1.2 Total Hedging against External Debt and Compliance in Semester I – 2016

Net Foreign Shortfall to Currency Hedging Hedging Residual Minimum Hedging (0-3 months) Respondents Liabilities Standards (dalam juta dolar AS) Hedging (Compliance) 150 3.015 754 3.022 7 2.268 a. Financial Institutions 17 132 33 1.289 1.157 1.258 b. Non-Financial Institutions 133 2.883 721 1.733 (1.150) 1.012 Hedging (Non-Compliance) 21 785 196 99 (686) (97) Not Hedging (Non-Compliance) 264 2.927 732 - (2.927) (732) Total 435 6.727 1.682 3.121 (3.606) 1.439

Net Foreign Shortfall to Currency Hedging Hedging Residual Minimum Hedging (3-6 months) Respondents Liabilities Standards (dalam juta dolar AS) Hedging (Compliance) 39 308 77 765 (457) 688 a. Financial Institutions 13 121 30 610 (489) 580 b. Non-Financial Institutions 26 190 48 155 35 107 Hedging (Non-Compliance) 6 88 22 8 80 (14) Not Hedging (Non-Compliance) 182 3.220 805 - 3.220 (805) Total 227 3.616 904 773 2.843 (131)

Source: Bank Indonesia

17 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 1.22 Non-Resident SBN Holdings Graph 1.23 Non-Resident Stock Holdings

1800 Triliun Rupiah 100% 1600 644 90% Non-Resident 559 1400 36.47% Resident 536 80% 1200 461 70% 404 60% 1000 324 1,003 50% 800 283 903 271 820 40% 728 749 600 671 30% 550 606 20% 400 63.53% 10% 200 0% Jul 13 0 Jul 14 Jul 15 Jan 13 Jan 14 Jan 15 Jan 15 Jun 13 Oct 13 Jun 14 Oct 14 Jun 15 Oct 15 Jun 15 Feb 13 Sep 13 Feb 14 Sep 14 Des 14 Feb 15 Sep 15 Feb 15 Apr 14 Apr 15 Apr 15 Apr 13 Dec 13 Dec 15 Nov 13 Nov 14 Nov 15 Mar 13 Mar 14 Mar 15 Mar 15 Aug 13 Aug 14 Aug 15 Dec-12 Jun-13 Dec-13 Jun-13 Dec-14 Jun-14 Dec-15 Jun-16 May 13 May 14 May 15 May 15 Resident Non-Resident Source: Directorate General of Budget Financing and Risk Management (DJPPR), Source: CEIC Ministry of Finance

Graph 1.24 Non-Resident and Resident SBI Holdings

100% 90% 94.70% 80% 70% 60% 50% 40% 30% 20% 10% 0.53% 0% Jul 12 Jul 13 Jul 14 Jul 15 Jan 12 Jan 13 Jan 14 Jan 15 Jan 16 Sep 12 Sep 13 Sep 14 Sep 15 Nov 12 Nov 13 Nov 14 Nov 15 Mar 12 Mar 13 Mar 14 Mar 15 Mar 16 May 12 May 13 May 14 May 15 May 16 Non-Resident Resident

Source: Bank Indonesia

Graph 1.25 Stock Prices and Transaction Volume Graph 1.26 SBN Prices and Transaction Volume

Rp T Rp T 20 5800 50 10.0 15 5600 40 9.0 10 5400 30 5 5200 8.0 20 0 5000 10 7.0 (5) 4800 0 (10) 4600 6.0 (10) (15) 4400 5.0 (20) (20) Non-Resident Net Buy/Sell of Stocks Jakarta Composite 4200 Index (rhs) (25) 4000 (30) 4.0 Non-Resident Net Buy/Sell of SBN 10-Year SBN Yields (rhs) Jul 13 Jul 14 Jul 15 Jan 13 Jan 14 Jan 15 Jan 16 Sep 13 Sep 14 Sep 15 Nov 13 Nov 14 Nov 15 Mar 13 Mar 14 Mar 15 Mar 16 May 13 May 14 May 15 May 16 Jul 13 Jul 14 Jul 15 Jan 13 Jan 14 Jan 15 Jan 16 Sep 13 Sep 14 Sep 15 Nov 13 Nov 14 Nov 15 Mar 13 Mar 14 Mar 15 Mar 16 May 13 May 14 May 15 May 16

Source: Bank Indonesia, , Bloomberg Source: Bank Indonesia, Indonesia Stock Exchange, Bloomberg

18 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box 1.1 Tax Amnesty

The Tax Amnesty is a limited-time opportunity for amnesty should not be repeated in order to avoid taxpayers to pay a redemption fee, in exchange for expectations that increase incentives for taxpayers forgiveness of a tax liability, including interest and to reduce tax compliance. penalties, relating to a previous tax period without fear of prosecution (Baer and LeBorgne, 2008). In The Tax Amnesty in Indonesia addition, the tax amnesty also exempts taxpayers The tax amnesty is not a new idea in Indonesia, from criminal prosecution and further tax audits where a tax amnesty was introduced in 1984. for a defined period (Malherbe, 2010). In general, The policy was considered ineffective, however, the tax amnesty aims to raise tax revenues in due to a lack of accompanying reforms to the tax the near term; increase future tax compliance; administration system. repatriate capital or assets; and transition to a new tax system. The Government also instituted several smaller- scale policies thereafter to raise tax revenues. In Tax amnesty programs have been implemented 2008, for example, the Government reintroduced in numerous countries. The 2011 tax amnesty in its sunset policy to remove administrative penalties Italy successfully absorbed EUR80 billion of an on taxpayers for underpayment of tax and for estimated EUR500 billion. Russia also introduced erroneous completion of tax forms. a tax amnesty in 2007, absorbing USD130 million (Box Table 1.1.1). Congruent with widespread global economic uncertainty, the spillover of which translated into The literature study found that the highest domestic economic moderation, the government level of tax compliance is attained through an saw the need to increase tax revenue by unannounced (sudden) tax amnesty accompanied introducing a tax amnesty in 2016. In addition to by legal enforcement. Nonetheless, the tax providing more fiscal space against a low tax ratio, Box Table 1.1.1 Tax Amnesties in Various Countries

No. Country Year Program Benefit Notes 1 Switzerland Post World War II Repatriation of assets held abroad 50%of deposits returned to Switzerland 2 USA 1993-1997 Tax Amnesty 2.6% increase in tax revenue Repatriation of assets held abroad; €80 billion from an estimated €500 billion 27 amnesties from 1993-2009, 3 Italy 1900-2009 scudo fiscal (Tax Shield) (capital) totalling 58 amnesties since 1900 4 Ireland 1988-1996 Repatriation of assets held abroad $1.5 billion 1998-1996, 3 times 5 Russia 2007 Repatriation of assets held abroad $130 million 2014 Repatriation of assets held abroad 6 Argentina 1995-2003 General Amnesty; blanqueos $3.9 billion 9 amnesties 7 India 1997 General Amnesty $2.5 billion 8 México 2007-2012 General Amnesty Unreported

Source: Centre for Indonesia Taxation Analysis (CITA)

7 Alm, J., McKee, M. and Beck, W. 1993. Amazing Grace: Tax Amnesties and Compliance. National Tax Journal, 43(1): 23-37.

19 FINANCIAL STABILITY REVIEW No. 27, September 2016

Box Figure 1.1.1 Tax Reporting Mechanism and Instruments Special Account Report

Periodic Report of Investment Position

Perception Bank INSTRUMENTS

Debt securities, Sukuk, Stocks GATEWAY

Bank** Mutual Funds, ABS, REIT $ MI** Term Deposits, Demand Deposits, Savings Deposits Special Broker- DJP Perception Bank Account Dealer** Other OJK approved instruments

Custodian Bank Investment Position In the territory of the Republic of Indonesia for three years Proof of Investment

* Opening of Special Account/Customer Information File at Perception Bank approved by the Minister to transfer WP funds

** Special Customer Fund Account (if required) opened by Bank, MI or Broker-Dealer at a Bank approved by the Ministry of Finance as a Gateway

Source: Ministry of Finance

the large potential of illicit funds placed offshore All taxpayers are required to declare and report were also considered that could be used to finance assets and then pay the flat redemption fee national economic development. through the appointed reception banks. There are currently 19 approved reception banks. Taxpayers’ The Tax Amnesty was introduced on 1st July funds are repatriated through the reception banks 2016 through Act No. 11 of 2016 concerning the and placed in investment instruments in Indonesia Tax Amnesty. Pursuant to the new law, the tax for no less than three years through alternative amnesty targets all taxpayers, excluding those: (i) investment gateways. The funds shall be placed in under investigation and whose investigative files a special account and reported to the Directorate have been declared complete by the Attorney General of Tax by the investment gateway General’s Office; (ii) currently involved in judicial institution. The redemption rate is calculated using proceedings; or (iii) serving a sentence handed specific tariffs as follows: down in a taxation case.

July - September 2016 October - December 2016 January - March 2017

Domestic Tax Tariff 2% Tax Tariff 3% Tax Tariff 5%

International

Repatriated: 2% Tariff Repatriated: 3% Tariff Repatriated: 5% Tariff Non-repatriated: 4% Tariff Non-repatriated: 6% Tariff Non-repatriated:

20 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

The Impact of the Tax Amnesty in Indonesia • Anticipate several scenarios that could occur The tax amnesty has several benefits for the when the repatriated funds start to flow back Indonesian economy, particularly in terms of into the country, particularly towards the end tax revenues. Larger tax revenues are expected of 2016. The anticipatory measures include to expand fiscal space to finance development preparing an adequate number of instruments programs. Furthermore, there are potentially large with attractive yields to absorb the tax amnesty sums of repatriated funds, which will boost capital funds as well as measures to manage liquidity flows to Indonesia and increase liquidity to finance and maintain macroeconomic and financial productive economic activities at home. system stability.

On top of the benefits, several risks also demand Bank Indonesia shall strive to support the success vigilance. One risk is that interest in the tax of the tax amnesty by maintaining macroeconomic amnesty will not be as strong as expected, which and financial system stability, while mitigating the would undermine the ability to support fiscal risks that may appear. To that end, Bank Indonesia performance and economic financing. In contrast, will implement the following measures: (i) manage the tax amnesty could be oversubscribed. If the economic and financial system liquidity through investment outlets are unprepared or insufficient an appropriate monetary operations strategy; in number, the inflow of funds will not be used (ii) manage the balance between supply and optimally for economic financing and will merely demand of foreign exchange and strengthen the circulate in the financial system without flowing scope of foreign exchange reserves; (iii) maintain to the real sector. To reduce the impact of accommodative macroprudential policy to increase rapidly rising asset prices and excessive rupiah bank financing; and (iv) accelerate financial market appreciation, the funds must be fully absorbed deepening and promote instruments as investment in order to avoid additional expenses in terms of outlets for tax amnesty funds. managing liquidity in the economy.

Consequently, the government and relevant authorities have prepared a number of measures to manage the impact of the tax amnesty as follows: • Establish a task force and coordination team charged with aligning policies to support tax amnesty implementation.

21 FINANCIAL STABILITY REVIEW No. 27, September 2016

Analysis of Financial Imbalances based on the National Financial Boks 1.2 Account and Balance Sheet (NFA & BS)

In conjunction with relevant institutions, Bank of interaction between economic sectors to Indonesia has prepared the National Financial assess financial system resilience to systemic risk Account and Balance Sheet (NFA & BS) as a primary through interconnectedness and risk transmission component of the G20 recommendations relating between sectors. Fundamentally, intersectoral to the data gap initiative. NFA & BS have the risks can be transmitted through two financing advantage of containing information concerning channels, namely debt and equity. The network the interconnectedness between economic sectors is formed using the intersectoral financial claim as a cross section. Through the NFA & BS, the matrix or from whom-to-whom (wtw) matrix that economy is represented as an integrated system of contain information on the bilateral exposure sectoral balance sheets, consisting of the banking position between economic sectors. Network sector, nonbank financial industry, corporate analysis also illustrates concentration risk and sector, household sector, central government, local interconnectedness risk. government, central bank and external sector. The analysis of financial imbalances indicators for Integrated NFA & BS data is used to analyse financial the first quarter of 2016 revealed that national imbalances between sectors that could trigger a financial system balance was maintained. Risk mismatch in the size or composition of assets and indicators improved for all economic sectors, liabilities in various economic sectors. Information including currency risk, external risk, the leverage on imbalances is obtained through indicators that ratio and solvency. Exposure to currency risk and show risks in a particular sector or indeed risks that external risk was highest in the corporate sector emerge due to interconnectedness in the financial and central government. Departing from the trend system. of other risk indicators, liquidity risk was observed to increase, primarily originating from a decline of Two methods currently under development by assets in the form of savings deposits, including Bank Indonesia are used to analyse the indicators of banking sector and central government deposits financial imbalances on the NFA & BS, namely Risk held at the central bank. Banks withdrew deposits Profile Analysis and Network Analysis. Risk profile held at the central bank in response to the looser analysis can detect mismatches as sources of risk reserve requirement stipulated at the beginning on the NFA & BS, including maturity mismatches, of 2016. Meanwhile, the central government was currency mismatches and capital structure inclined to withdraw deposits held at the central mismatches, which illustrate potential liquidity bank to pay mature government securities (SBN) risk, currency risk, external risk, the leverage ratio and finance development projects. and solvency. Network analysis formulates models

22 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

The position of financing to the external sector activities. The corporate sector continues to rely on recorded a net liability, where the share of external the external sector (38%), households (33%) and debt to total liabilities reached 28.74% and was the banking sector (17%) for its financing. Bank dominated by the central government, accounting financing to the corporate sector grew at 8% (yoy) for 55.92%, while the corporate sector accounted but tracked a downward trend. The household for 39.71% and the nonbank financial industry for sector experienced a net inflow, reversing the net 19.42%. The large value of national net liabilities to outflow or net lending in the previous period due the external sector indicates a funding gap, namely to withdrawals of savings deposits and additional that domestic financial assets are inadequate to bank loans as the demand for liquidity increased. fully cover demand from all economic sectors, Meanwhile, the local government recorded a thus demand for external financing remains high. net inflow due to seasonal placements of local Such conditions are also in line with the negative government funds in the banking sector. value of net national financial assets. Nationally, the share of financial assets is relatively large and Interconnectedness analysis using positional data increasing, while non-financial assets are tracking revealed a general decline of domestic exposure a downward trend. to the external sector, although the value remains relatively high. The corporate sector is the most Analysis of interconnectedness between economic financially exposed, followed by the banking sectors using transaction data showed that the sector. High financial exposure is indicative of

Box Figure 1.2.1 Net Intersectoral Transactions

2015 QI (Rp T) 2015 Q4 (Rp T) 2016 QI (Rp T)

154.76 54.17 67.11 3.45 19.93 13.29 NFC ODC NFC ODC NFC ODC 9.301 46.38 130.62

ROW HH ROW HH ROW HH

56.86 71.93 63.87

CG OFC CG OFC CG OFC 68.23 27.94 87.30 10.81 118.61 37.60

CB LG CB LG CB LG 2.63 12,81 133,16 189.42 42.08 138.90

Net Transaction=Outflow – Inflow NFC=korporasi, HH=rumah tangga, ODC =bank, OFC=IKNB, CG=pempus, CB=bank sentral, LG=Pemda, RoW=eksternal

corporate sector is still experiencing a net inflow potential spillover risk in the case of liquidity or net borrowing with a declining net transaction or solvency pressures. Meanwhile, the highest value on the previous period. Such conditions interconnectedness risk was found between the indicate less financing for the corporate sector that corporate and external sectors as well as the could undermine performance and reduce business banking sector and corporate and household

23 FINANCIAL STABILITY REVIEW No. 27, September 2016

sector. Such risk requires tighter monitoring of the corporate and household sector, particularly the possibility of corporate bankruptcies due to economic moderation and currency depreciation. Box Figure 1.2.2 Gross Exposure between Sectors

Box Figure 1.2.2 Gross Exposure between Sectors

2015 QI (Rp T) 2015 Q4 (Rp T) 2016 QI (Rp T)

13.775 11.182 14.704 11.930 15.412 12.073 NFC ODC NFC ODC NFC ODC

8.566 9.301 9.780

ROW HH ROW HH ROW HH

9.893 10.468 10.420

CG OFC CG OFC CG OFC 4.345 2.720 4.863 2.871 4.981 2.925

CB LG CB LG CB LG 3.551 535 3.639 454 3.565 597

Gross Position=Total Finansial Aset + Total Liabilities NFC=korporasi, HH=rumah tangga, ODC =bank, OFC=IKNB, CG=pempus, CB=bank sentral, LG=Pemda, RoW=eksternal

24 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box 1.3 Impact of the Brexit on the Indonesian Economy

The global economy again made history with the The Brexit referendum recorded the highest UK’s decision to leave the European Union (EU) on turnout since 1951. According to the UK Electoral 24th June 2016, pursuant to the referendum held Commission, registered voters totalled 46 million the day earlier. The referendum closed with 51.9% in 382 voting districts. In other words, voter of the votes for leave and 48.1% for remain (Box turnout was over 80%, surpassing that of the UK Figure 1.3.1). The leave vote triumphed in England General Election in 2015 at 66.1% to record the and Wales with 53.4% and 52.5% of the votes highest participation level since 1951. The process respectively. In contrast, Northern Ireland and of leaving the EU will require time, however, Scotland voted to remain with 55.8% and 62.0% of predicted by some at more than 10 years. Pursuant the votes (Box Figure 1.3.2). to Articles in the European Union Treaty, however, the UK Government has two years to negotiate The referendum was implemented based on the terms of the split. Therefore, the UK will the EU Summit held on 18-19th February 2016, formally leave the EU in 2018. Thereafter, the UK where is was agreed that the UK had the right to will establish the format of new trade agreements choose whether to leave the EU or not. The Brexit with the EU as well as other countries through referendum was initiated by a campaign promise bilateral accords, the European Economic Area or of the Conservative Party, with David Cameron the World Trade Organisation. That process is not stating in 2015 that UK citizens had the right to expected to be completed until 2025. choose whether to remain or leave the EU. The deadline was fixed for the end of Cameron’s tenure The UK economy has performed positively since in 2016. joining the EU in 1972, reflected by rising per capita income (Box Graph 1.3.1) as UK trade increased

Box Figure 1.3.1 UK Referendum Voting Results Box Figure 1.3.2 Voting Results by Region

England 51.9% 48.1% Leave 53.4% Remain 46.6% Leaves Remain 17.420.342 votes 16.141.241 votes Northen Ireland Leave 44,2% Remain 55,8%

Scotland Leave 38,0% Remain 62,0%

Wales Leave 52,5% Remain 47,5%

Source: www.theguardian.com Source: www.theguardian.com

25 FINANCIAL STABILITY REVIEW No. 27, September 2016

with EU member states (Box Graph 1.3.2). Such positive impact of joining the EU was also visible conditions led to greater economic openness in in the financial sector as direct investment flowed the UK, accompanied by an increasingly robust into the UK (Box Graph 1.3.3). Furthermore, access economy based on innovation and the adoption of to the EU single market strengthened the UK’s new technology, while increasing production scale () position as a global financial hub. and enhancing specialisation. Furthermore, the

Box Graph 1.3.1 UK GDP Per Capita Box Graph 1.3.2 UK Trade Performance

Canada UK Italy Japan Germany Ratio of trade volumes 35000 France US to GDP (2010 prices) 100 UK joins Single market

30000 the EU established

80 25000

60 20000 Real GDP per capita

40 15000

10000 20 1950 1970 1990 2010 Year UNITED KINGDOM synthetic UNITED KINGDOM 0 1960 70 80 90 2000 10

Source: Bloomberg, processed Source: Bloomberg, processed

Box Graph 1.3.3 Direct Investment Inflows to UK

2500e+11

2000e+11

1500e+11

1000e+11

5000e+11

1970 1980 1990 2000 2010

UNITED KINGDOM synthetic UNITED KINGDOM Source: Bank Indonesia

26 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Positive economic achievements in the UK through EU caught the markets off-guard and triggered access to the EU single market could potentially be financial shocks in the UK and Europe, in GBP and lost due to the referendum, with the majority of UK EUR (Box Graph 1.3.4), while the FTSE 100 Index citizens voting to leave the EU (Brexit). In the near and Stoxx Europe 600 nosedived (Box Graph 1.3.5). term, the impact of the Brexit will be most visible Notwithstanding, the markets quickly recovered on the financial sector. The subsequent Brexit as investors engaged in profit-taking activities. effect on economic growth, direct investment flows and the UK’s position as a global financial Consistent with movements on financial markets hub will only become clear in the medium-long in the UK and Europe, markets in Asia also slumped term. One important determinant of the transition after the Brexit vote. Most currencies in the region duration are the negotiations between the UK and depreciated on the previous day, with the KRW EU. Article 50 of the Lisbon Treaty stipulates that falling 2.44%, followed by the MYR dropping countries deciding to leave the EU have two years 1.86%. Meanwhile, Indonesia experienced more to negotiate the split. The Brexit vote to leave the limited depreciation of just 0.88% (Box Graph

Box Graph 1.3.4 GBP and EUR Performance in 2016 1.3.6). The rupiah fell to a level of Rp13,450 in the morning session due to widespread market GBPUSD EURUSD 1,50 1,18 uncertainty prior to the final referendum result.

1,48 1,16 The rupiah rebounded shortly thereafter due to 1,46 1,14 1,44 profit-taking and assurance that the UK would 1,42 1,12

1,40 1,10 leave the EU, hence the rupiah closed at Rp13,375

1,40 1,08 (Box Graph 1.3.7). 1,38 1,06 1,36

1,34 1,04 GBP EUR (Rhs) 1,32 1,02 In line with currency depreciation, regional stock markets also slumped. The MSCI Asia Pacific 1-Jan-16 9-Jun-16 1-Mar-16 11-Jan-16 21-Jan-16 31-Jan-16 19-Jun-16 20-Feb-16 10-Feb-16 10-Apr-16 20-Apr-16 30-Apr-16 21-Mar-16 11-Mar-16 31-Mar-16 20 -Feb-16 20-May-16 10-May-16 30-May-16

Source: Bloomberg, processed Index fell 4.3%, while stock price indexes in South Korea and India contracted by -3.09% and -2.72%

Box Graph 1.3.5 FTSE 100 and Stoxx Europe Performance in 2016 Box Graph 1.3.6 Changes in Currencies in Asia (23rd June 2016 vs 24th June 2016) GBPUSD EURUSD

6,600 3,400 KRW -2.44 3,300 6,400 MYR -1.86 6,200 3,200 SGD -1.37 3,100 6,000 3,000 INR -0.96 5,800 2,900 IDR -0.88 5,600 2,800 PHP -0.79 5,400 2,700 5,200 CNY -0.54 FTSE 100 Stoxx Europe (Rhs) 2,600 5,000 2,500 THB % -0.47

(3.00) (2.50) (2.00) (1.50) (1.00) (0.50) (0.00) 1-Jan-16 9-Jun-16 1-Mar-16 11-Jan-16 21-Jan-16 31-Jan-16 19-Jun-16 10-Feb-16 20-Feb-16 10-Apr-16 20-Apr-16 30-Apr-16 11-Mar-16 21-Mar-16 31-Mar-16 20 -Feb-16 10-May-16 20-May-16 30-May-16 Source: Bank Indonesia, Indonesia Stock Exchange, Bloomberg Source: Bank Indonesia, Indonesia Stock Exchange, Bloomberg

27 FINANCIAL STABILITY REVIEW No. 27, September 2016

Box Graph 1.3.7 Intraday Rupiah Exchange Rate Movements Commodity Index experienced a 1.5% decline,

13550 while Brent fell 5.01% in line with the 2.5% drop 13500 in copper and nickel prices on the London Metal 13450 13400 13400 Exchange. 13350

13300 13250 Deteriorating stock and SBN performance drove 13200 13150 investors to seek safe-haven assets, namely the 13100 JPY, USD and gold. The yen appreciated 3.24% to 8:00 8:45 9:30 8:35 9:20 10:20 11:05 11:55 12:40 13:30 14:15 15:05 15:50 10:05 10:50 11:35 12:20 13:05 13:50 14:35 15:20 23-Jun-16 24-Jun-16 102.83, its highest level since 2013. Meanwhile, Source: Bloomberg, processed the USD climbed 1.97% to 95.4 (Box Graph 1.3.11). respectively. The stock market in Indonesia also In addition, the gold price reached USD1,310 per experienced a limited correction of -0.82% (Box ounce, the highest it has been since March 2014 Graph 1.3.8). Simultaneously, regional government (Box Graph 1.3.12). Moving forward, investors will securities (SBN) markets also faced a downturn remain risk-averse with high expectations of an

(Box Graph 1.3.9). Furthermore, the yield of Box Graph 1.3.10 SBN Yield in Indonesia in 2016

government bonds in Indonesia increased 18bps 9.00 to a level of 7.81% (Box Graph 1.3.10). On the 8.80 8.60 commodity markets, the UK’s decision to leave the 8.40 8.20 EU also affected commodity prices. The Bloomberg 8.00 7.81 7.80 Box Graph 1.3.8 Changes in Stocks in Asia (23rd June 2016 vs 24th 7.60 June 2016) 7.40 7.20 Korea -3.09 7.00 India -2.72 1-Jan 1-Jun 9-Jun 4-Feb 4-Apr 9-Mar 1-Mar 6-May 19-Jan 27-Jan 11-Jan 17-Jun 12-Feb 22-Feb 12-Apr 28-Apr 20-Apr 17-Mar 25-Mar 16-May Singapore -2.11 24-May

Thailand -1.70 Source: Bloomberg, processed

China -1.30

Philippines -1.29 uncertain negotiation process as the UK negotiates Indonesia -0.82 its exit from the EU, while exit sentiment spills Malaysia % -0.36

(4.00) (3.00) (2.00) (1.00) (0.00) over to other EU member states. Source: Bloomberg, processed

Box Graph 1.3.9 Changes in Yields in Asia (23rd June 2016 vs 24th The impact of the Brexit on Indonesia through the June 2016) trade channel should be relatively limited. The Korea -0.13 share of Indonesian exports to the UK amounts India 0.00

Malaysia 0.02 to just 1.0% (Box Graph 1.3.13). Nonetheless, the

Indonesia 0.18 knock-on effect of the strained trade relationship

Philippines % 0.36 between the UK and EU should be monitored (0.20) (0.10) 0.00 0.10 0.20 0.30 0.40

Source: Bloomberg, processed closely considering Europe (excluding UK)

28 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box Graph 1.3.11 JPY and USD Movements Box Graph 1.3.12 Gold Price (23-24th June 2016)

110 USDPJPY, Index 1360

1340 105 1320 1300 100 1310 1280

95 1260 1240

90 1220

USDPJPY DXY 1200 85 8:00 8:45 9:30 8:35 9:20 10:20 11:05 11:55 12:40 13:30 14:15 15:05 15:50 10:05 10:50 11:35 12:20 13:05 13:50 14:35 15:20 8:00 9:20 0:00 1:20 2:40 4:00 5:20 6:40 8:00 9:20 10:40 12:00 13:20 14:40 16:00 20:00 21:20 22:40 10:40 12:00 13:20 14:40 16:00 23-Jun-16 24-Jun-16 23-Jun-16 24-Jun-16

Source: Bloomberg, processed Source: Bloomberg, processed

Box Graph 1.3.13 Major Export Destinations from Indonesia Box Graph 1.3.14 FDI Inflows to Indonesia from UK

-10% Europe ex UK; 8.00% 11.4% UK; Others 1.0% -5% 30.8% 0% US; 13.5% -5%

-10% FDI Indonesia dari UK -15% China 9.8% ASEAN -20% 21.9% Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15

May-12 May-13 May-14 May-15 Japan21.9%

Source: TEIC, processed Source: TEIC, processed

accounted for 11.4% of Indonesian exports in 2015. has remained below 10% of the total (Box Graph In terms of investment, the impact has also been 1.3.14). Therefore, the impact of the Brexit on the comparatively limited. Over the past five years, for Indonesian economy has been relatively minimal example, the share of FDI to Indonesia from the UK in general.

29

Global and domestic economic dynamics had a strong influence on domestic financial market performance during the first semester of 2016. In addition to global sentiment from the United States and Europe, sluggish economic performance in China and gains to several international commodity prices affected domestic financial market conditions. Furthermore, domestic financial markets rallied on the positive perception of investors regarding the promising domestic economic outlook in line with maintained macroeconomic conditions and favourable expectations linked to the recently enacted tax amnesty. Positive sentiment prompted an increase in financing sources on financial markets, particularly the bond market.

Like other countries in the region, risks on domestic financial markets eased in the first half of 2016, indicated by lower interbank rates, rupiah appreciation, JCI gains and less volatility on the stock market along with lower SBN yields. In addition, mutual funds performed well in line with the stock market and SBN market momentum.

THE FINANCIAL2 MARKETS FINANCIAL STABILITY REVIEW No. 27, September 2016

Pressures on Domestic Financial Markets eased as Global Sentiment Improved

Money Market

Risks on the money market eased, reflecting low rates on all tenors

Interbank Money Market Pasar Repo O/N Interbank Rate to Suku Bunga menjadi 5.08% 5.28%-6.5% Rp O/N Volatility to Volume Transaksi 69.4% Harian menjadi Daily O/N Transaction Volume to Rp412 miliar Rp15.15 trillion

Foreign Exchange Market Bond Market

Risks dissipated as global uncertainty Market risk tended to subside for bonds, SBN decreased and perception of the domestic and corporate bonds economic outlook improved IDMA Index to Rupiah exchange rate to 101.77 Rp13,795 per USD 10-Year ON yield to $ Rp Volatility to 7.42% 9.54% 10-Year ON Volatility to Government NDF Spread to 9.81% -10.09 points Securities Non-Resident Net Inflow totalling Foreign Exchange Transactions to USD 350.6 billion Rp85.47 trillion

Jakarta Composite Index (JCI) 10-Year Yield (A) to A JCI rally, combined with less volatility, 10.80% demonstrated less risk on the stock market Volatility to 6.10%

JCI to Non-Resident Net Inflow totalling Corporate Bonds 5016.6 Rp0.214 trillion Volatility to Lembaga Keuangan 11.84% Syariah Non-Resident Net Inflow totalling Rp15.38 trilion

Islamic Financial Markets

The Islamic financial markets performed soundly, particularly the government sukuk market and Islamic stock market

SIMA Yield on the Islamic Interbank Islamic Stock Index to Money Market to 694.3 % 5.5 Islamic Stock Index to Islamic Interbank Money Market 15.14% Transaction Volume to Rp628 billion

32 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

from the capital market and finance companies 2.1. The Role of Financial Markets as more than doubled on the previous period despite Sources of Economic Financing slower growth of bank loans. A nominal increase in issuances of corporate bonds and sukuk were The financial markets play an important economic the main contributors, along with a recovery of role in any country. The financial markets offer financing from finance companies, which reversed alternative sources of financing to bank loans the previous contraction. Financing from the for economic players. Like other developing stock market in the form of IPOs and rights issues countries, bank loans remain the dominant decreased slightly, however, on the previous period. source of financing in Indonesia. Nonetheless, the role of financial markets is expected to become On the stock market, IPOs and rights issues increasingly important over time as global and moderated from Rp34.94 trillion to Rp32.81 trillion domestic financial markets and economies become in the reporting period. Despite a decrease in more integrated and economic players demand value, the number of issuers of IPOs and rights more financing. Furthermore, the banking industry issues increased from 20 to 21 in the same period. utilises the financial markets to help manage Strong interest in IPOs and rights issues was liquidity in the near and long term. In general, maintained in the first half of 2016 by positive short-term liquidity management aims to optimise domestic sentiment linked to the Tax Amnesty as

Table 2.1 Bank and Nonbank Financing (Rp, trillions) Rp Triliun 2014 2015 2016 Description Sem I Sem II Sem I Sem II Sem I

A, Bank Loans 175,79 206,15 153,74 230,08 110,17

B, Nonbank Financing 64,78 50,06 67,64 45,99 96,23

B1, Capital Market 51,88 44,78 63,95 52,61 88,60

- IPO and Rights Issue 26,35 21,67 18,59 34,97 32,81

- Corporate Bonds and Sukuk 25,53 23,11 45,36 17,65 55,84

B2, Finance Companies 12,90 5,27 3,69 -6,63 7,58

Total 240,07 256,20 221,38 276,07 206,41

Source: Bank Indonesia and Financial Services Authority (OJK) Notes: Bank loans and nonbank financing disbursed in the reporting period, not positional data. yields through placements on the interbank money well as abundant liquidity on global markets due market, bond market and other money markets. to persistently low rates in advanced countries, the On the other hand, banks use the financial markets expected postponement to the next FFR hike as to support long-term liquidity management by well as search-for-yield behaviour by investors. building a solid capital base through stock issuances and by securing funding through issuances of long- On the bond market, corporate bond and sukuk term bonds. issuances totalled Rp55.84 trillion in the first semester of 2016, representing a three-fold In the first semester of 2016, nonbank financing increase on the Rp17.65 trillion posted in the

33 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 2.1 IPO and Rights Issue Volume on the Stock Market Graph 2.3 Value of Bond Issuances 25 Rp Triliun

45 20

40 Rights Issue IPO Bonds 15 35

30 10 25

20 5 15

10 0 5

0 Jul-14 Jul-15 Jan-14 Jan-15 Jan-16 Jun-14 Jun-15 Jun-16 Oct-14 Oct-15 Feb-14 Feb-15 Feb-16 Apr-14 Apr-15 Apr-16 Sep-14 Sep-15 Dec-14 Dec-15 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16 Aug-14 Aug-15 1 2 3 4 5 6 7 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 May-14 May-15 May-16 Corporate Bonds (Rp, t) Average Yield of 5-Year Corporate 2014 2015 2016 Lending Rate on Investment Bonds (%) Loans (%) Source: Financial Services Authority (OJK), Bank Indonesia, processed Sumber : Financial Services Authority (OJK), Bank Indonesia, processed

second semester of 2015 and up 23% from the corporations with a AAA to A rating could source Rp45.36 trillion registered one year earlier. cheaper funds than from the banking industry. Furthermore, the number of issuers also more than doubled in the reporting period from 18 to 39 due Meanwhile, the market for Negotiable Certificates to the front loading of corporate bond issuances at of Deposit (NCD) remained relatively attractive the beginning of the year as a government strategy. during the first semester of 2016, due to bank Positive sentiment regarding the financial market issuers seeking short-term funds of less than recovery also depressed bond yields, which lowered one year in response to slower deposit growth. the cost of funds of bond issuances. Consequently, Consequently, outstanding NCD increased 34%

Graph 2.2 Comparison of Corporate Bond Yield Curve and Graph 2.4 Value of Outstanding MTN and NCD Average Interest Rates on Working Capital Rp Trilion Loans and Investment Loans % 35,0 16 MTN NCD 15 30,0 14 25,0 13 11.47% 12 20,0 11 15,0 10

9 10,0 8 7 5,0 1 2 3 4 5 6 7 8 9 10 - AAA June 2016 BBB June 2016 Jul-14 A June 2016 Average Rate on WCL and IL Jul-15 Jan-15 Jan-16 Jun-15 Jun-16 Oct-14 Oct-15 Feb-15 Feb-16 Apr-15 Apr-16 Sep-14 Sep-15 Dec-14 Dec-15 Nov-14 Mar-15 Mar-16 Nov-15 Aug-14 Aug-15 May-15 May-16 Source: Bank Indonesia and CEIC Source: CEIC

34 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 2.5 Outstanding Mature MTN and NCD Graph 2.6 Value of MTN and NCD Issuances

Rp Trilion

3,5 Rp Trilion Medium-Term Notes (MTN) 7 3,0 MTN NCD 6 Negotiable Certificates of Deposit (NCD) 2,5 5

2,0 4

3 1,5

2 1,0 1 0,5 0 0,0 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 2015 2016 2016 2017 2018 Source: Indonesian Central Securities Depository (KSEI), processed Source: Indonesian Central Securities Depository (KSEI), processed from Rp9.67 trillion in the second semester of 2015 only 2.8% in the previous period. The surge was to Rp12.96 trillion in the reporting period. attributed to lower corporate bond yields in line with positive global and domestic sentiment and Differing from NCD, the MTN market stagnated reflects the banking sector’s response to slower in the first half of 2016, with outstanding MTN deposit growth over the past few periods, thus falling 4.06% on the position in the previous period requiring bond issuances to ensure long-term to Rp17.89 trillion. The regulation concerning fund availability for the planned credit expansion. continuous bonds was one reason given for MTN In addition to accumulating funds from the bond market stagnation, which facilitated new bonds market, banks also increased funding through IPO at a lower cost, thereby negating the previous and rights issues on the stock market worth Rp8.00 advantages of the MTN market. trillion, which was up on the previous period in terms of value and number of issuers. For the banking industry, the financial markets offer alternative sources of funds to deposits and During the first semester of 2016, a total of 85 alternative outlets. In terms of accumulating funds, banks borrowed from the interbank money market eight banks issued bonds in the first semester of and 98 banks placed funds on the rupiah interbank 2016 to the tune of Rp14.4 trillion, compared to money market, with an average daily volume of one bank in the previous period issuing just Rp500 Rp15.2 trillion, up from Rp13.7 trillion previously. billion. Banks accounted for 25.7% of total bond Transaction volume increased as bank demand issuances in the first semester of 2016, up from for short-term rupiah liquidity grew in line with seasonal trends during Ramadan.

35 FINANCIAL STABILITY REVIEW No. 27, September 2016

Table 2.2 Sources of Funds by Bank Total

Rp Triliun 2012 2013 2014 2015 2016 Description Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Fund Accumulation I. Domestic Borrowing from Rupiah 54 79 74 81 81 76 76 86 85 Interbank Money Market Borrowing from Foreign 51 51 50 48 47 39 40 33 31 Exchange Interbank Money Market Repo to BI/Lending Facility 3 4 3 10 1 7 19 12 Repo by Banks 6 7 7 10 16 16 18 18 10 Bond Markets 7 6 8 3 2 3 6 1 8 - Bonds 2 2 3 1 2 1 1 - - Continuous Bonds 4 4 4 3 1 1 4 7 - Sukuk 1 1 1 1 Stock Market 3 4 7 9 3 3 - 4 6 - IPO 4 2 1 1 - 1 1 - Rights Issues 3 4 3 7 2 2 1 3 5 II. International - USD Bonds 1 1 ------Fund Distribution I. Domestic Lending to Rupiah Interbank 89 95 93 95 94 99 98 100 98 Money Market Lending to Foreign Exchange 48 47 48 49 45 42 39 31 37 Interbank Money Market Deposit Facility 107 105 110 100 107 134 98 114 100 Term Deposit 51 65 39 - - - - - SDBI - - - 43 50 76 79 74 81 SBI 95 86 91 98 98 108 75 74 86 Reverse Repo SUN 38 30 31 25 36 59 37 17 25 SBN 86 86 88 88 91 87 84 95 101

Source: Bank Indonesia, Financial Services Authority (OJK)

Table 2.3 Source of Bank Funds by Volume Rp Triliun 2012 2013 2014 2015 Description Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Fund Accumulation I, Domestic Borrowing from Rupiah Interbank Money Market - Volume 1.066 1.233 1.374 1.241 1.326 891 845 844 941 - Average Daily Volume of 5,0 6,1 6,0 6,0 6,7 7,1 6,8 6,9 7,6 Rupiah Borrowing - Average Daily Volume of 544,2 311,4 224,2 246,0 262,4 291,6 242,7 208,6 271,1 USD Borrowing (millions) Repo to BI/Lending Facility 0,4 1,1 0,5 5,5 - - 11,4 1,0 Repo by Banks 32,7 41,0 31,1 32,3 - - 81,4 29,0 0,4 Bond Markets 6,8 7,1 8,5 3,7 5,0 2,0 11,4 0,5 14,4 - Bonds 0,5 0,3 1,2 1,0 1,3 1,5 0,5 - - Continuous Bonds 5,5 6,8 6,6 3,7 4,0 0,7 9,4 14,3 - Sukuk 0,8 0,7 0,5 0,1 Stock Market 1,9 4,7 4,2 9,4 1,5 2,1 0,6 1,0 8,0 - IPO 1,7 0,6 0,1 0,1 - 0,1 0,6 - Rights Issues 1,9 4,7 2,4 8,8 1,5 2,0 0,6 0,9 7,4 II, International USD Bonds 500 500 Fund Distribution I, Domestik Interbank Money Market - Average Daily Volume of 5.0 6.1 6.0 6.0 6.7 7.1 6.8 6.9 7.6 Rupiah Lending - Average Daily Volume of 544.0 311.4 224.6 247.8 262.8 291.4 242.7 208.6 271.1 USD Lending (millions) Deposit Facility 118.3 81.6 121.1 123.5 125.3 98.5 127.2 112.3 134.6 Term Deposit 88.7 180.9 51.7 - - - - - SDBI - - - 26.5 23.3 102.3 62.4 39.9 66.5 SBI 89.9 79.4 82.1 89.6 98.6 87.0 72.7 31.1 78.8 Reverse Repo SUN 60.3 81.4 73.5 74.6 74.4 88.6 64.1 5.7 11.0 SBN 286.0 282.0 298.0 316.0 338.0 374.0 346.7 350.0 361.5

Source: Bank Indonesia, Financial Services Authority (OJK)

36 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

2.2. Risks on the Financial Markets Favourable investor perceptions held firm until September 2016, with asset prices rising on domestic markets, including the foreign exchange market, stock Risks tended to ease on domestic financial markets market and bond market. On the foreign exchange during the first semester of 2016, supported by market, for instance, the rupiah strengthened against maintained domestic macroeconomic conditions, the USD, even hitting a level below Rp13,000 per rising global commodity prices and relatively stable USD at the end of September. On the stock and SBN global financial markets. Externally, the global markets, however, total capital inflow to both markets economic recovery slowed due to lower-than- amounted to Rp21.43 trillion and Rp24.11 trillion expected growth in the United States; the Brexit in July and August 2016 respectively. Domestically, that overshadowed the economy of Europe and positive sentiment stemmed from the repatriation an indebted corporate sector in China running at of funds linked to the tax amnesty that exceeded overcapacity. Several advanced countries responded expectations, coupled with Bank Indonesia lowering to such conditions by extending low policy rates its policy rate. (Japan, Sweden and Switzerland) and the adverse impact of uncertainty surrounding the normalisation Less risk was observed on domestic financial of US monetary policy was also reduced. In addition, markets, including the rupiah interbank money the international prices of several commodities began market, foreign exchange market, stock market and to pick up in the first semester of the year. At home, bond market (corporate and government bonds), however, sound macroeconomic conditions, indicated reflecting lower volatility compared to the previous by controlled inflation and favourable expectations of period. Less risk was also indicated by rupiah the tax amnesty, improved investor perception of the appreciation, lower risk premiums on the foreign domestic economic outlook, thus prompting an influx exchange market, a JCI rally as well as lower bond of foreign capital to the domestic financial markets in yields. the first semester.

Graph 2.7 Financial Market Volatility Graph 2.8 Non-Resident Flows: Stocks, SBN and SBI

Rupiah Interbank Rp Triliun Money Market Non-Resident Flows to Stocks, SBN and SBI 150

100 Mutual Funds Exchange Rate 50

0

Bonds SBN -50

Sem II 2015 --100 *) Further from the centre indicates higher risk Sem I 2015 Sem I Sem II Sem I Sem II Sem I Stock Sem I 2016 2009 2010 2011 2012 2013 2014 2015 2016

Source: Bloomberg, Note: Further from the centre indicates higher risk Source: Bloomberg, Bank Indonesia, Ministry of Finance

37 FINANCIAL STABILITY REVIEW No. 27, September 2016

2.2.1. Money Market experienced a decline, with the weighted average In general, risks on the money markets, including O/N rate recorded at 5.80% and the average of the uncollateralised and collateralised markets, all tenors at 5.86%. Declining interbank rates eased in comparison to the previous two periods. were, however, accompanied by greater volatility, The increase of transaction volume on the interbank especially at the end of semester I and semester money market, coupled with the relatively II of 2016. Nonetheless, such conditions were stable repo transaction volume, was indicative symptomatic of Bank Indonesia reducing its policy of adequate liquidity in the banking industry. rate rather than heightened risk on the interbank Although interest rate volatility increased on the money market. interbank money market, it was caused more by Bank Indonesia lowering its policy rate rather than Overnight rupiah interbank transaction volume inadequate liquidity conditions. Congruent with increased in the first semester of 2016 from lower interbank rates, rates on repo transactions Rp13.73 trillion in the previous period to Rp15.15 were also observed to come down. trillion. Meanwhile, transaction volume of non- overnight tenors remained relatively stable, 2.2.1.1. Interbank Money Market decreasing slightly from Rp9.68 trillion to Rp9.62 Despite heightened volatility, risks on the interbank trillion. The increase of interbank transactions in money market eased during the first semester of the reporting period was linked to seasonal trends 2016, as indicted by lower interest rates. The in the form of Eid-ul-Fitr and school holidays, which weighted average daily interest rate on the rupiah drove up demand for short-term liquidity that was interbank money market for overnight (O/N) tenors met by the banks through the interbank money fell from 6.02% to 5.08% in the reporting semester. market. Based on prevailing trends, bank behaviour Furthermore, the weighted average daily rate on on the rupiah interbank money market was noted all tenors decreased from 6.21% to 5.30%. Like the to change in the reporting period, specifically BUKU same period of the previous year, interbank rates 2 banks. Previously, BUKU 2 banks had been net

Graph 2.9 O/N Rupiah Interbank Rate Graph 2.10 O/N Rupiah Interbank Rate Volatility

% % % PUAB O/N % 10 5 300 7.5

7.0 4 250 8 6.5

200 6.0 3 6 5.5 150 2 5.0

100 4.5 4 1 4.0 50 3.5 2 0 0 3.0 Jul 15 Jun 10 Jun 11 Jun 12 Jun 13 Jun 14 Jun 15 Jun 16 Oct 10 Oct 11 Oct 12 Oct 14 Oct 15 Feb 11 Feb 12 Feb 13 Feb 14 Feb 15 Feb 16 Jan 15 Jan 16 Jun 15 Jun 16 Oct 13 Sep 14 Sep 15 Oct 14 Oct 15 Feb 15 Feb 16 Apr 15 Apr 16 Dec 14 Dec 15 Nov 14 Nov 15 Mar 15 Mar 16 Agu 14 Agu 15 May 15 May 16

Weighted Average Rate Highest Rate (%) Max-Min Spread (rhs) O/N Rupiah Interbank Rate Volatility Weighted Average of Loans (rhs)

Source: Bank Indonesia Source: Bank Indonesia

38 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

borrowers on the interbank money market, but that on the foreign exchange interbank market and changed in the first semester of 2016, with BUKU 2 the average for all tenors were 0.28% and 0.30% banks becoming net lenders. It remained business respectively, exceeding the 0.10% and 0.12% posted as usual for the other bank groups, with BUKU 4 in the previous semester. The foreign exchange and 1 banks as net lenders and BUKU 3 banks as interbank rate increased not only because of net borrowers. liquidity, but also in line with the term deposit rate hike by Bank Indonesia in the first semester from In terms of market share, BUKU 4 and 2 banks 0.38% to 0.40%, which represents an alternative dominated interbank transactions. By volume, the outlet for the banks to place their short-term share both bank groups accounted for 68% of the foreign exchange. total. In terms of counterparties, however, BUKU 3 banks had more counterparties than BUKU 2 banks, A wider max-min spread on the O/N foreign while the size of BUKU 3 banks exceeded the size of exchange interbank money market, coupled with BUKU 2 banks. Therefore, the impact of default on increased volatility, was indicative of escalating risk. BUKU 3 banks was considered higher than on BUKU In the first semester of 2016, the average spread 2 banks. was recorded at 19.70bps, up from 12.06bps in the previous period and 5.37bps one year earlier. In Lower rupiah interbank rates during the first addition, average volatility on the foreign exchange semester of 2016 were not accompanied by lower interbank money market skyrocketed to 271% from rates on the foreign exchange interbank money 22.74% in the previous period and 17.9% one year market. The weighted average daily overnight rate earlier.

Graph 2.11 Rupiah Interbank Money Market Graph 2.12 Rupiah Interbank Transaction Distribution

% Rp Triliun Rp Triliun 8.0 35 150

7.0 30 100 6.0 25 5.0 50 20 4.0 15 0 3.0 10 2.0 -50

1.0 5 -100 - -

-150 2013 2013 2013 2013 2013 2013 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2014 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 Jul 2013 Jul 2014 Jul 2015 Jul 2012 Jan 2013 Jan 2014 Jan 2015 Jan 2012 Sep 2013 Sep 2014 Sep 2015 Sep 2012 Sep 2011 Nov 2015 Nov 2012 Nov 2013 Nov 2014 Nov 2012 Mar 2012 Mar 2013 Mar 2014 Mar 2015 May 2013 May 2014 May 2015 May 2012 Jul Jul Jul Jan Jan Jun Jun Oct Oct Oct Feb Feb Apr Apr Sep Sep Sep Dec Dec Nov Nov Nov Mar Mar Agu Agu Agu May May Dec Average Daily O/N Volume (rhs) Average Daily Non-O/N Volume (rhs) BUKU 4 BUKU 3 BUKU 2 BUKU 1 Weighted Average of all Rates Weighted Average O/N Rate Source: Bank Indonesia Source: Bank Indonesia

39 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 2.13 Foreign Exchange Interbank Money Market Graph 2.14 O/N Foreign Exchange Interbank Rate Performance % USD Jt 0.40 1.600 0.60 0.40

0.35 1.400 0.35 0.50 0.30 1.200 0.30 0.40 0.25 1.000 0.25

0.20 800 0.30 0.20

0.15 600 0.15 0.20 0.10 400 0.10 0.10 0.05 200 0.05

0 0 0 0 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 Jun 2012 Jun 2013 Jun 2014 Jun 2015 Jun 2016 Oct 2012 Oct 2013 Oct 2014 Oct 2015 Feb 2013 Feb 2014 Feb 2015 Feb 2016 Apr 2012 Apr 2013 Apr 2014 Apr 2015 Apr 2016 Dec 2012 Dec 2013 Dec 2014 Dec 2015 Aug 2012 Aug 2013 Aug 2014 Aug 2015

Daily Average Non-O/N Volume (rhs) Weighted Average Interest Rate Highest Rate (%) Daily Average O/N Volume (rhs) Max-Min Spread (rhs) Weighted Average of all Rates Weighted Average of O/N Rate Source: Bank Indonesia Source: Bank Indonesia

Transaction volume on the foreign exchange in behaviour on the foreign exchange interbank interbank money market increased for O/N tenors money market during the reporting period. For the but decreased for all other tenors. The average past two years, BUKU 4 banks had tended to lend to daily volume of O/N foreign exchange interbank the interbank money market, but over the past two transactions was recorded at USD537.38 million in semesters, BUKU 4 banks have tended to borrow the first semester of 2016, up USD119.53 million from the interbank money market. The reverse on the previous semester. In contrast, the average is true for BUKU 3 banks, namely changing from daily volume of non-O/N tenors fell from USD65.35 borrowing banks to lending banks in the past two million to USD40.88 million. Based on historical semesters. BUKU 4 banks made the change in order norms, BUKU 4 and 3 banks experienced a change to meet increased demand for foreign exchange from their customers.

Graph 2.15 Foreign Exchange Interbank Rate Volatility Graph 2.16 Foreign Exchange Interbank Transactional Behaviour

% % USD Miliar 5 450 0.45 4 400 0.40 3 350 0.35 2 300 0.30 1 250 0.25 0 200 0.20 -1 150 0.15 -2 100 0.10 -3 50 0.05 -4

0 0.00 -5 Jul 15 Jan 15 Jun 15 Jun 16 Sep 14 Sep 15 Oct 14 Oct 15 Feb 15 Feb 16 Apr 15 Apr 16 Dec 14 Dec 15 Nov 14 Nov 15 Mar 15 Mar 16 Jul 2014 Jul 2015 Aug 14 Aug 15 May 15 May 16 Jan 2014 Jan 2015 Jan 2016 Jun 2015 Jun 2016 Jun 2014 Oct 2014 Oct 2015 Feb 2014 Feb 2015 Feb 2016 Sep 2014 Apr 2014 Apr 2015 Sep 2015 Apr 2016 Dec 2014 Dec 2015 Nov 2014 Nov 2015 Mar 2014 Mar 2015 Mar 2016 Aug 2014 Aug 2015 May 2014 May 2015 May 2016

USD Interbank Rate Average Weighted Lending Rate (rhs) BUKU 4 BUKU 3 BUKU 2 BUKU 1 Volatility Source: Bank Indonesia Source: Bank Indonesia

40 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 2.17 Interbank Repo Transactions Graph 2.18 Lending Facility Transactions

Rp Triliun % Rp Triliun % 12,0 8.5 1800 7.5 8.0 1600 10,0 7.0 7.5 1400 6.5 8,0 7.0 1200 6.5 1000 6.0 6,0 6.0 800 5.5 4,0 5.5 600 5.0 5.0 2,0 400 4.5 4.5 200 0 4.0 7 9 11 1 3 5 7 9 11 1 3 5 10 12 2 4 6 8 10 12 2 4 6 8 10 12 2 4 6 0 4.0 Jul Jul Jan Jan Jan Jun Jun Jun Oct Oct Feb Feb Feb Apr Sep Apr Sep Apr Dec Dec Nov Nov

Mar Mar Mar 2012 2013 2014 2015 2016 Aug Aug May May May

2014 2015 2016 Total Volume LF Rate (rhs) Weighted Average (All Tenors) Repo Rate (rhs) Source: Bank Indonesia Source: Bank Indonesia

2.2.1.2 Interbank Repo Market1 (LF) volume in the reporting period was linked Risk tended to ease on the interbank repo market to seasonal demand to withdraw deposits during the first semester of 2016. The average daily towards yearend in 2015 and to pay government interbank rate for all tenors tracked a downward infrastructure projects. trend from the 6.45-7.15% range to 5.28-6.50% in the reporting period. Such conditions were 2.2.2. Foreign Exchange Market accompanied by a decline in the average daily Risk also eased on the foreign exchange market in the transaction volume for all tenors from Rp569 billion first semester of 2016, evidenced by lower average to Rp412 billion. The lower interbank rate and rupiah volatility against the US dollar, falling from transaction volume were indicative of abundant 14.09% to 9.54%. Furthermore, rupiah appreciation liquidity in the banking industry. The decrease of was driven by the promising domestic economic repo transactions was blamed on policy to enforce outlook, sound macroeconomic conditions and the Global Master Repurchase Agreement (GMRA) less negative fallout from uncertainty surrounding for repo transactions by the Financial Services the normalisation of US monetary policy on global Authority (OJK), thereby requiring time for the financial markets. In total, foreign exchange banks to adjust from the previous mini Master transaction volume increased from USD339.4 Repo Agreement (Mini MRA). billion at the end of semester II – 2015 to USD350.6 billion at the end of the reporting period. One year Meanwhile, repo activity with Bank Indonesia earlier, total foreign exchange volume stood at also declined in the first semester of 2016, with USD350.64 billion with exchange rate volatility at transaction volume falling from Rp3.10 trillion 8.01%. to Rp0.99 trillion. An increase of Lending Facility

1 Repurchase Agreement (Repo) adalah perjanjian untuk menjual dan membeli kembali surat berharga pada tanggal dan harga yang telah ditetapkan. Secara umum pasar Repo terdiri dari Repo antar bank dan Repo kepada Bank Indonesia melalui Lending Facility.

41 FINANCIAL STABILITY REVIEW No. 27, September 2016

Spot transactions continued to dominate the Graph 2.19 Rupiah Exchange Rate

% domestic foreign exchange market, accounting for 90 16000 63.66% of total transaction volume. Meanwhile, 80 15000 70 14000 derivatives in the form of swap and forward 13000 60 transactions accounted for 29.90% and 6.44% 50 12000 40 11000 respectively, increasing from 24.64% and 5.50% in 30 10000 the previous semester in line with Bank Indonesia 20 9000 10 8000 efforts to maintain rupiah exchange rate stability by 0 7000 deepening the domestic foreign exchange market, Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Oct-11 Oct-12 Oct-13 Oct-14 Oct-15 Oct-16 Feb-12 Feb-13 Feb-14 Feb-15 Apr-11 Apr-12 Apr-13 Apr-14 Apr-15 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 Aug-11 Aug-12 Aug-13 Aug-14 Aug-15 Aug-16 while encouraging market players to reduce spot Volatility Exchange Rate (rhs) transactions when meeting demand for foreign Source: Bloomberg, processed exchange. Furthermore, Bank Indonesia now also requires nonbanks with external debt to hedge Similar conditions were found on the Non- 20% of their foreign currency liabilities, effective Deliverable Forward (NDF) market. Average NDF since 1st January 2015. Since hedging policy was transaction spread to domestic forwards initially implemented, the portion of spot transactions increased to 41.45 points but then narrowed to has fallen from 70.94% to 63.66% due to lower -10.09 points. The swing points to a change in the demand for swap and forward transactions from risk perception of non-resident investors, indicating the corporate sector and relatively high premium less future risk. Compared to NDF spread in other costs on derivative transactions. several countries in the region, average NDF spread

to domestic forwards was seen to narrow, showing 2.2.3. Bond Market that the perception and expectations of foreign 2.2.3.1 Government Securities (SBN) Market investors to the majority of regional currencies In the first semester of 2016, positive global against the rupiah is comparatively sound. sentiment, stemming from the transient impact of

Graph 2.20 Rupiah Volatility Graph 2.21 Foreign Exchange Market Risk Premium

400 15.500 % % 2016 300 15.000 30 15 10 14.500 5 200 25 - 14.000 100

20 1-Jan 4-Mar 6-May 22-Jan

13.500 17-Jun 12-Feb 15-Apr 25-Mar 0 27-May 13.000 15 -100 12.500 10 -200 12.000

-300 11.500 5 -400 11.000 0 Jul 15 Jan 15 Jan 16 Jun 15 Jun 16 Feb 15 Feb 16 Okt 15 Apr 15 Sep 15 Des 15 Apr 16 Mei 15 Mei 16 Nov 15 Mar 15 Mar 16 Agu 15 Jun-11 Jun-13 Jun-14 Jun-16 Jun-08 Jun-10 Jun-12 Jun-15 Feb-13 Feb-16 Feb-10 Feb-11 Feb-12 Feb-14 Feb-15 Apr-09 Sep-09 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Nov-08 NDF – FWD Spread 1B Daily Average 200 Spread NDF 1B (rhs)

Source: Bloomberg, processed Source: Bloomberg, processed

42 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 2.4 A Comparison of Average NDF Spread in the Region Graph 2.22 Domestic Foreign Exchange Market Composition

70 USD Miliar

2014 2015 2016 60 Country Sem I Sem II Sem I Sem II Sem I 50

Thailand 0.01 0.02 0.04 0.06 (0.00) 40

Malaysia (0.00) 0.00 (0.00) (0.00) (0.01) 30

Philippines (0.01) 0.01 (0.02) 0.05 0.04 20

India (0.12) (0.11) (0.08) (0.05) (0.04) 10 0 Indonesia (54.18) 14.20 25.77 41.45 (10.09)

Source: Bloomberg Jun 2012 Jun 2013 Jun 2014 Jun 2015 Jun 2016 Oct 2012 Oct 2013 Oct 2014 Oct 2015 Feb 2012 Feb 2013 Feb 2014 Feb 2015 Feb 2016 Apr 2012 Apr 2013 Apr 2014 Apr 2015 Apr 2016 Dec 2012 Dec 2013 Dec 2014 Dec 2015 Aug 2012 Aug 2013 Aug 2014 Aug 2015 Spot Swap Forward Option

Source: Bank Indonesia the Brexit and predicted postponement of the next The growing share of non-resident SBN holdings FFR hike, and auspicious domestic factors, including eroded the portion of domestic holdings, especially sound macroeconomic conditions and the expected banking sector holdings. At the end of the first enactment of the Tax Amnesty, helped to drive semester of 2016, the banks accounted for 22% SBN holdings by non-resident investors. Search of total SBN in circulation, down from 24% in the for yield was another trigger because the yields previous period. In contrast, the nonbank financial of government securities in Indonesia were more industry, including the insurance industry and attractive than similar government instruments in pension funds, expanded SBN holdings in terms other developing countries. Foreign SBN holdings of value and volume. Compared to the previous swelled in the first semester of 2016 to Rp85.5 semester, the shares of SBN holdings of the trillion, from Rp20.99 trillion in the previous period insurance industry and pension funds increased 1% and Rp76.18 trillion one year earlier. Most foreign to 13% and 4% respectively of total SBN circulating SBN purchases were of new issuances by the on the market. Such conditions are consistent with government. OJK2 regulations that require the nonbank financial industry to maintain a certain percentage of total On one hand, the growth of foreign SBN holdings investments in government securities (SBN) in is positive because the trend demonstrates non- order to expand the investor base and increase resident confidence in the domestic economic trade on the secondary market. outlook. On the other hand, large foreign SBN holdings expose the market to the whims of foreign SBN prices tracked an upward trend during the first investor sentiment and the inherent risk of sudden semester of 2016, as reflected in the IDMA index reversal. In the first semester of 2016, non-resident that climbed 9.04% from 93.33 in the previous investors continued to bolster SBN holdings, more period to 101.77. Rising SBN prices lowered so than other investors. Consequently, the position yields and eased market risk, hence volatility also of non-resident SBN holdings at the end of June decreased. The yield of the benchmark 10-year SBN 2015 stood at 39% of the total outstanding SBN in fell 127bps to 7.42%, accompanied by a 47.67bps circulation. dip in volatility from 14.49% to 9.81%. In general,

2 OJK Regulation (POJK) No. 1/POJK.05/2015, dated 11th January 2016, concerning Investment in Government Securities for Nonbank Financial Institutions.

43 FINANCIAL STABILITY REVIEW No. 27, September 2016

Table 2.5 Composition of SBN Holdings

2015 2016 Sem II-I

Sem - I Sem - II Sem I Holder Nominal Pangsa Jumlah Jumlah Nominal (Rp T) Pangsa Pangsa Pangsa (Rp T) (Rp T) (Rp T)

Banks 369,11 27.21% 350,07 23.95% 361,54 21.95% 11,47 3.17

Central Bank 80,58 5.94% 148,91 10.19% 150,13 9.12% 1,21 0.81%

Mutual Funds 56,28 4.15% 61,60 4.21% 76,44 4.64% 14,83 19.40%

Insurance 161,81 11.93% 171,62 11.74% 214,47 13.02% 42,84 19.98% Companies

Foreign 537,53 39.63% 558,52 38.21% 643,99 39.10% 85,47 13.27%

Pension Funds 46,32 3.42% 49,83 3.41% 64,67 3.93% 14,84 22.95%

Individuals 0,03 0.00% 42,53 2.91% 48,90 2.97% 6,37 13.03%

Others 104,02 7.67% 78,50 5.37% 86,72 5.27% 8,22 9.47%

Source: Ministry of Finance

Graph 2.23 Composition of SBN Holdings (June 2012 – June 2016) Graph 2.24 Net Foreign Flows to SBN and IDMA

Rp Trilion Rp Trilion

1600 90 115 1400 80 110 1200 70 105 1000 60 50 100 800 40 95 600 30 90 400 20 85 200 10

0 0 80 Jun-12 Dec-12 Jun-13 Dec-13 Jun-14 Dec-14 Jun-15 Dec-15 Jun-16 Sem I Sem II Sem I Sem II 2012 2013 2014 2015 2016 Banks Central Bank Mutual Funds Insurance Companies Foreign Pension Funds Securities Individuals Net Flow Asing SBN IDMA (rhs) Source: Ministry of Finance Source: Bank Indonesia

the yields of all tenors followed a downward 14.51 (May 2016). Nonetheless, the turnover ratio trend, most significantly short-term yields, which remained above the crisis level recorded in 2008 indicates that near-term economic risks are being at approximately 12%. Furthermore, the turnover well mitigated, thus the risk premiums requested ratio of the corporate bond market is low and stable are coming down for short-term placements. Like in the 6% range. Such conditions show that most the downtick of SBN yields in Indonesia, SBN yields investors tend to hold government securities until in neighbouring countries also tended to decline maturity. In comparison to neighbouring countries, (Graph 2.24). however, Indonesia has the lowest SBN to GDP ratio. In March 2016, the updated SBN to GDP ratio Against a backdrop of less risk on the SBN market, was recorded at 52%, up from 45% at the end of liquidity on the secondary market evaporated, 2014. In contrast, the Philippines, maintained the as indicated by a decrease in the turnover ratio highest SBN to GDP ratio in the region, followed by from 18.18% in the second semester of 2015 to Thailand and Malaysia.

44 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 2.25 SBN Yield Curve Graph 2.26 Rebased SBN Yield by Tenor

10.0 % 220 rebased 1/1/2013

9.5 200 180 9.0 160 8.5 140 8.0 120 7.5 100 Short-Term : 1-5 years Medium-Term : 6-10 years 7.0 80 Long-Term : 11-30 years 6.5 60

6.0 Jul-14 Jul-15 Jan-14 Jan-15 Jan-16 Jun-14 Jun-15 Jun-16 Oct-15 Oct-14 Feb-14 Feb-15 Feb-16 Apr-14 Apr-15 Apr-16 Sep-14 Sep-15 Dec-14 Dec-15 Mar-14 Nov-14 Nov-15 Mar-15 Mar-16 Aug-14 Aug-15 1 2 3 4 5 6 7 8 10 11 12 13 15 16 18 20 30 May-14 May-15 May-16 (Tahun)

Jun-15 Dec-15 Jun-16 Short-Term Medium-Term Long-Term Source: Bloomberg, processed Source: Bloomberg, processed

Graph 2.27 SBN Yield Volatility by Tenor

45 % 40

35 30 25 20 15

10 5 0 Jun-14 Jun-15 Jun-16 Oct-15 Oct-13 Oct-14 Feb-14 Feb-15 Feb-16 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15

Short-Term Medium-Term Long-Term

Source: Bloomberg

Graph 2.28 SBN and Corporate Bond Transaction Turnover Graph 2.29 SBN to GDP Ratio

35% 140% 30%

25% 120%

20% 100%

15% 80%

10% 60%

5% 40%

0% 20% Feb-09 Feb-10 Feb-11 Feb-12 Feb-13 Feb-14 Feb-15 Feb-16 Nov-09 Nov-10 Nov-11 Nov-12 Nov-13 Nov-14 Nov-15 Aug-09 Aug-10 Aug-11 Aug-12 Aug-13 Aug-14 Aug-15 May-09 May-10 May-11 May-12 May-13 May-14 May-15 May-16 Jun-11 Jun-13 Jun-12 Jun-14 Jun-15 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-11 Dec-14 Dec-15 Dec-12 Dec-13 Mar-11 SBN Turnover Corporate Bond Turnover Mar-12 Mar-13 Mar-14 Mar-15 Mar-16

Indonesia Malaysia Thailand Philippines Source: CEIC Source: CEIC, processed

45 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 2.30 Rebased 10-Year SBN Yield in several Emerging Market Economies (EME)

rebased 1/1/2014 150 130 110 90 60 50 30 Jul-14 Jul-15 Jan-15 Jan-16 Jun-15 Jun-16 Oct-15 Oct-14 Feb-15 Feb-16 Apr-15 Apr-16 Sep-14 Sep-15 Dec-14 Dec-15 Nov-14 Nov-15 Mar-15 Mar-16 Aug-14 Aug-15 May-15 May-16

Indonesia India Thailand Malaysia Philippines

Source: Bloomberg

Table 2.6 10-Year SBN Yields in the Region (%) Table 2.7 10-Year SBN Yield Volatility in the Region (%)

Indo Indi Thai Maly Phil Indo Indi Thai Maly Phil Jun-14 8.09 8.58 3.57 3.93 3.78 Jun-14 4.11 8.11 8.92 8.25 11.45 Jul-14 7.94 8.58 3.44 3.81 3.72 Jul-14 4.22 7.85 11.49 7.68 10.82 Aug-14 8.09 8.75 3.31 3.83 3.77 Aug-14 4.40 7.60 10.90 12.04 7.84 Sep-14 8.28 8.75 3.20 3.84 3.93 Sep-14 8.32 7.83 10.76 5.09 7.03 Oct-14 7.97 8.41 2.98 3.79 3.85 Oct-14 6.99 8.06 16.13 14.32 6.02 Jun-14 8.09 8.58 3.57 3.93 3.78 Nov-14 6.98 5.52 17.91 9.60 12.14 Jul-14 7.94 8.58 3.44 3.81 3.72 Dec-14 17.73 8.77 25.44 25.80 8.62 Aug-14 8.09 8.75 3.31 3.83 3.77 Jun-15 18.11 9.90 25.71 27.06 29.16 Sep-14 8.28 8.75 3.20 3.84 3.93 Jul-15 10.76 4.36 13.12 21.74 33.09 Oct-14 7.97 8.41 2.98 3.79 3.85 Aug-15 13.43 4.61 21.62 27.22 31.42 Nov-14 7.69 8.22 2.66 3.74 3.55 Sep-15 13.61 6.73 23.26 22.64 27.92 Des-14 7.74 8.02 2.49 4.04 3.62 Oct-15 22.25 4.51 20.11 13.37 24.42 Jun-15 8.26 8.09 2.62 3.82 3.68 Nov-15 7.81 3.66 19.32 20.36 14.63 Jul-15 8.42 8.06 2.50 3.88 3.76 Aug-15 8.50 8.02 2.52 4.32 3.67 Dec-15 15.45 3.47 8.57 13.14 44.29 Sep-15 9.51 7.82 2.53 4.10 3.76 Jan-16 12.20 2.57 24.13 12.62 20.61 Oct-15 8.67 7.80 2.46 4.05 3.80 Feb-16 7.56 5.66 41.71 11.86 31.95 Nov-15 8.43 7.89 2.39 4.00 4.16 Mar-16 14.42 4.57 21.01 8.37 14.39 Des-15 8.75 7.86 2.25 3.89 4.27 Apr-16 6.76 6.62 31.36 10.86 20.09 Jan-16 8.18 7.74 1.99 3.62 3.96 May-16 8.13 1.81 45.47 28.62 11.25 Feb-16 7.91 7.85 1.75 3.63 3.84 Jun-16 9.79 2.69 46.81 7.83 22.05 Mar-16 7.37 7.76 1.46 3.56 3.70 Apr-16 7.37 7.57 1.59 3.65 3.54 Source: Bloomberg, processed May-16 7.51 7.58 2.08 3.66 3.48 Jun-16 7.62 7.49 1.74 3.43 3.33

Source: Bloomberg, processed

2.2.3.2. Corporate Bond Market Outstanding corporate bonds at the end of the first Consistent with relatively well mitigated risk on semester of 2016 increased from Rp242.44 trillion the SBN market, risk on the corporate bond market to Rp261 trillion, with foreign holdings increasing also eased in the first semester of 2016, with lower 1.19% or Rp214 billion, to Rp18.20 trillion. yields of bonds from corporations of all ratings compared to the previous period. In addition, the Despite the increase in value, foreign holdings average volatility of corporate bond yields of all of corporate bonds experienced a decline from tenors fell from 8.94% to 6.10% in the reporting 7.20% to 6.74%. Growth of outstanding corporate period. bonds held by non-residents accelerated slightly on positive global and domestic sentiment.

46 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 2.8 Corporate Bond Holdings Graph 2.31 Net Foreign Flows to Corporate Bonds and Holdings

2015 2016

Holder Sem I Sem II Sem I Rp Trilion Rp Trilion 8 25 Total % Total % Total % 6 Corporate 20 10.57 4.6% 9.37 3.9% 9.39 3.60% 4 Individual 6.28 2.7% 6.32 2.6% 6.54 2.51% 2 15

Mutual Funds 48.49 20.9% 54.38 22.4% 63.82 24.45% 0 10 Securities (2) 0.92 0.4% 0.68 0.3% 0.84 0.32% Companies (4) 5 Insurance 34.22 14.7% 36.66 15.1% 41.58 15.93% Companies (6) Sem 1 Sem 2 Sem 1 Sem 2 0 Pension Funds 65.17 28.1% 68.92 28.4% 68.80 26.36% 2011 2012 2013 2014 2015 2016 Financial 49.11 21.2% 54.07 22.3% 56.68 21.72% Companies Net Flow Outstanding Foreign Holdings (rhs) Foundations 1.38 0.6% 3.06 1.3% 3.55 1.36% Others 10.34 4.5% 8.98 3.7% 9.80 3.76% Source: CEIC, processed Total 232.07 242.44 261.00

Source: OJK Reports, processed

Graph 2.32 Corporate Bond Yield Curve Graph 2.33 Corporate Bond Yield Volatility by Tenor

% % 16 30 15 25 14

13 20 12 15 11

10 10 9 5 8 0 7 1 2 3 4 5 6 7 8 9 10 Jul-15 Jan-15 Jan-16 Jun-15 Jun-16 Oct-15 Feb-15 Feb-16 Apr-15 Apr-16 Sep-15 Dec-14 Dec-15 Nov-15 Aug-15 May-15 May-16

AAA, Dec 2015 AAA, June 2016 Marr-15 Marr-16 AA, Dec 2015 AA, June 2015 Short-Term BBB, Dec 2015 BBB, Jun 2016 Medium-Term Long-Term

Source: CEIC, processed Source: Bloomberg, processed

Graph 2.34 Corporate Bond Issuers by Sector

70 Property Mining Trade 60 Consumption Miscellaneous Industries Infrastructure Financial Basic Industries Agriculture

50

40

30

20

10

0 Sem I Sem I Sem I Sem I Sem I Sem I Sem I Sem I Sem I Sem II Sem II Sem II Sem II Sem II Sem II Sem II Sem II

2008 2009 2010 2011 2012 2013 2014 2015 2016

Source: OJK Reports, processed

47 FINANCIAL STABILITY REVIEW No. 27, September 2016

Pension funds, mutual funds and finance the previous period to 5016.6. Stock price indexes in companies are the three largest creditors that the region also tended to track gains due, amongst dominate domestic corporate bonds. Nevertheless, others, to investor optimism concerning domestic the composition of corporate bond holdings and regional economic performance. experienced a change in the first semester of 2016, with pension funds releasing share of outstanding The value of non-resident stock holdings on the corporate bonds from 28.4% to 26.4% of the total domestic stock market was recorded at Rp171.76 value. Such conditions were the result of pension trillion at the end of the first semester of 2016. In funds diverting from corporate bonds to SBN as the the same period, foreign investors accumulated priority investment instrument in order to comply domestic stocks to book a net inflow totalling with the OJK regulation concerning minimum Rp15.38 trillion. International financial institutions holdings of SBN by the nonbank financial industry. and mutual funds recorded the largest value gains in terms of stock holdings. By sector, the increase 2.2.4. Stock Market primarily affected the consumption sector, mining Risks also subsided on the stock market during the sector and property sector. Non-resident investors first semester of 2016. Accordingly, the Jakarta booked more additional units of stock holdings Composite Index (JCI) rallied, while volatility has than in the previous period, totalling 24.15 billion decreased as an aggregate and by sector since the units. middle of reporting period. The JCI rallied 9.22% on

Graph 2.35 Regional Stock Price Indexes Graph 2.36 Stock Price Volatility

140 Rebased 40 35 130 30 120 25 110 20 15 100 10 90 5 80 0 Jul-15 Jul-14 Jul-15 Jan-15 Jan-16 Jan-14 Jan-16 Jan-15 Jun-15 Jun-16 Jun-14 Jun-16 Jun-15 Feb-15 Feb-16 Apr-15 Apr-16 Oct-13 Oct-14 Oct-15 Feb-14 Feb-15 Feb-16 Apr-14 Apr-16 Apr-15 Okt-15 Sep-15 Des-15 Sep-13 Sep-14 Sep-15 Mei-15 Mei-16 Dec-13 Dec-14 Dec-15 Mar-15 Nov-15 Mar-16 Mar-14 Mar-15 Mar-16 Nov-13 Nov-14 Nov-15 Agu-15 Aug-13 Aug-14 Aug-15 May-14 May-16 May-15

Source: Bloomberg, processed Source: Bloomberg, processed

Graph 2.37 Foreign Capital Inflows to Regional Stock Markets Graph 2.38 Net Foreign Trade on the Stock Market and JCI Sumber : Bloomberg, diolah 110 Rp Trilion 50 5.500 105 40 5.000

100 30 4.500 20 95 4.000 10 3.500 90 0 3.000 85 -10 -20 2.500 Jun-11 Jun-12 Jun-13 Jun-14 Jun-16 Oct-11 Oct-12 Oct-13 Oct-14 Feb-11 Feb-12 Feb-13 Feb-14 Feb-16 2.000 Mei-15 Nov-15 Agu-15 -30 Sem I Sem II Sem I Sem II Sem I 2009 2010 2011 2012 2013 2014 2015 2016 India Philippines Indonesia Thailand

Source: Bloomberg, processed StocksStock JCIJCI (rhs) (rhs)

Source:Source: Bloomberg,Bloomberg, processedprocessed

48 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 2.9 Foreign Stock Holdings by Business Group (Rp, trillions) Rp Trilions

Equity Dec-14 Jun-15 Dec-15 Jun-16 ∆ Sem I’15 ∆ Sem II’15 ∆ Sem I’16 Corporate 383.50 365.51 317.01 325.19 (17.99) (48.50) 8.18 Individual 13.97 13.32 10.93 10.74 (0.65) (2.39) (0.19) Mutual Funds 343.24 317.03 289.14 328.48 (26.21) (27.89) 39.34 Securities Companies 78.62 80.86 218.07 229.99 2.24 137.21 11.92 Insurance Companies 16.00 16.56 17.06 18.43 0.56 0.50 1.37 Pension Funds 115.99 111.42 111.60 129.54 (4.57) 0.18 17.94 Financial Institutions 314.56 324.61 283.95 328.38 10.05 (40.66) 44.43 Foundations 3.64 3.67 2.20 4.60 0.03 (1.47) 2.40 Others 571.23 569.10 406.42 452.81 (2.13) (2.13) 46.39 Total 1.840.75 1.802.08 1.656.39 1828.15 -38.7 -145.69 171.76

Source: OJK Reports

Table 2.10 Foreign Stock Holdings by Economic Sector (Units, billions) Billions Unit

Sector Dec-14 Jun-15 Dec-15 Jun-16 ∆ Sem I’15 ∆ Sem II’15 ∆ Sem I’16

Financial 238,53 240,20 241,78 245,91 1.68 1.58 4.13 Consumption 38,86 38,54 38,55 72,75 (0.31) 0.01 34.20 Trade 237,23 243,00 255,11 249,18 5.77 12.11 (5.94) Infrastructure 123,06 117,33 128,57 131,74 (5.73) 11.24 3.17 Property 154,26 159,48 158,19 170,29 5.23 (1.29) 12.09 Miscellaneous Industries 34,75 36,02 36,39 35,68 1.26 0.37 (0.71) Basic Industries 90,65 79,09 75,01 76,32 (11.56) (4.07) 1.30 Mining 156,76 160,78 163,27 179,24 4.02 2.49 15.96 Agriculture 35,07 42,25 43,97 43,97 7.18 1.72 (0.42) Total 1.109,17 1.116,71 1.140,86 1.204,65 7.54 24.15 63.79

Source: Indonesian Central Securities Depository (KSEI)

JCI and sectoral index volatility decreased on the stable over the same period. previous period. By sector, miscellaneous industries recorded the highest level of volatility due to Astra The JCI rally in the reporting semester was triggered International stock that accounts for around 84% by blue chip stocks, reflecting an 8.7% rally on the of market capitalisation value of the miscellaneous LQ45 Index from 792.03 in the second semester industries sector. A decline of automotive sales due of 2015 to a level of 860.72 in the subsequent to domestic economic moderation was the main period. By sector, the miscellaneous industries, drag on the performance of Astra International. consumption and infrastructure sectors were the main contributors to LQ45 momentum, with Astra In terms of transaction volume, the daily average International, Unilever and Telkom experiencing was recorded at Rp5.77 trillion in the first semester an uptick in stock prices and accounting for 27.9% of 2016, up from Rp5.03 trillion in the previous of LQ45 capitalisation value and 19.14% of JCI period. Nevertheless, the turnover ratio remained capitalisation value.

49 FINANCIAL STABILITY REVIEW No. 27, September 2016

Table 2.11 Index Volatility by Sector Graph 2.39 Stock Market Turnover

2014 2015 2016 Rp T Sem 1 Sem 2 Sem 1 Sem 2 Sem 1 0.25% 9 Jakarta Composite 14.56 10.79 11.41 19.53 11.84 8 Index (JCI) 0.20% 7 Financial 19.51 13.52 14.00 25.38 15.76 6 0.15% Agriculture 18.50 16.38 21.78 24.57 19.82 5 4 Basic Industry 21.21 16.17 16.22 31.85 16.79 0.10% 3 Consumption 15.13 11.82 17.76 22.71 18.33 2 Property 21.55 17.75 17.13 21.71 13.66 0.05% 1 Mining 15.95 15.49 13.25 18.09 18.95 0.00% 0 Infrastructure 16.72 12.33 12.20 19.55 16.60 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-09 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Trade 11.94 11.90 12.51 16.01 11.28 Mar-10 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 Miscellaneous 24.02 19.42 22.73 36.11 27.93 Transaction Turnover Daily Transaction Volume (rhs) Industries

Source: Bloomberg, processed Source: CEIC, processed

Graph 2.40 JCI and LQ45 Capitalisation Graph 2.41 JCI Share Trade Frequency

Rp Trilion Rp Trilion 6,000 80% 100% 90% 75% 5,000 80% 70% 70% 4,000 60% 65% 50% 3,000 60% 40% 30% 55% 2,000 20% 50% 10% 0% 1,000 45%

0 40% Jun-09 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Oct-09 Oct-10 Oct-11 Oct-12 Oct-13 Oct-14 Oct-15 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Feb-09 Feb-10 Feb-11 Feb-12 Feb-13 Feb-14 Feb-15 Feb-16

JCI Capitalisation LQ45 Capitalisation LQ45 Share (rhs) LQ45 NON LQ45

Source: Bloomberg, processed Source: Bloomberg, processed

2.2.5. Mutual Funds3 In the first semester of 2016, the yields on most Mutual funds continued to expand in the first mutual funds increased. Such conditions were semester of 2016, reflecting a net asset value reflected by the risk profile quadrants, where (NAV) of 11.75%, up considerably from 3.63%. the majority of excess returns in June 2016 (red Rising SBN and stock prices, as the underlying dots) were higher than the positions recorded in assets, contributed to the NAV increase along with December 2015 (blue dots). In terms of risk, the the dominance of equity funds, which accounted volatility of fixed-income funds decreased, with for 35.68% of the total. Nominally, fixed income most red dots located below 1.0 compared to and protected funds enjoyed the most significant the December 2015 positions, in line with the NAV gains. Meanwhile, NAV volatility eased on the characteristics of underlying assets, namely debt three main markets. The most volatile funds were securities and short-term securities that have a confirmed as equity and discretionary funds. lower inherent level of price volatility than stocks.

3 Mutual funds are an investment media used to accumulate funds from a group of investors for investment in instruments available on the market as mutual funds.

50 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 2.42 Position of Mutual Funds Graph 2.43 NAV of Mutual Funds by Type

350 1400 300 Rp Trilion

300 1200 250

250 1000 200 200 800 150 150 600 100 100 400

200 50 50

0 0 0 Jun Jun Jun Jun Oct Oct Oct Oct Feb Feb Feb Feb Apr Apr Apr Apr Dec Dec Dec Dec Aug Aug Aug Aug Jun Jun Jun Jun Oct Oct Oct Feb Feb Feb Apr Apr Apr Apr Dec Dec Dec Aug Aug Aug 2013 2014 2015 2016 2012 2013 2014 2015 2016

Units in Circulation NAV Total Equity Funds Money Market Funds Discretionary Funds (millions) (Rp, trillions) Mutual Funds (rhs) Fixed-Income Funds Protected Funds Other Funds

Source: OJK Reports Source: OJK Reports Graph 2.44 NAV Volatility of Mutual Funds Graph 2.45 Growth of Mutual Funds (yoy)

45 % 50% 40 40% 35 30% 30 20% 25 10% 20 0% 15 -10% 10 -20% 5 -30% 0 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 1 3 5 7 9 11 2012 2013 2014 2015 Jul-14 Jul-15 Jan-15 Jun-15 Oct-14 Oct-15 Feb-15 Apr-15 Sep-14 Sep-15 Dec-14 Mei-15 Dec-15 Mar-15 Nov-14 Nov-15 Aug-14 Aug-15 NAV Units in Total Mutual JCI IDMA Fixed-Income Funds Discretionary Equity Funds Circulation Funds Funds Source: OJK Reports, various periods Source: OJK Reports, various periods

Graph 2.46 Risk Profile of Mutual Fund Products Equity Funds Fixed-Income Funds 30 Jun’15 10 Jun’15 25 Dec’15 Dec’15 20 5 Jun’16 Jun’16 15 10 0

5 -5 0

-5 -10 -10 -15 -15 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 -1 -0.5 0 0.5 0.5 1.5 2.5 3 Beta Beta Discretionary Funds Money Market Funds 3.0 15 Jun’15 Jun’15 10 Dec’15 2.0 Dec’15 5 Jun’16 1.0 Jun’16 - 0.0 (5) -1.0 (10) (15) -2.0 (20) -3.0 (25) -4.0 (30)

-1 -0.5 0 0.5 1 1.5 2 2.5 3 -0.5 -0.3 -0.1 0.1 0.3 0.5 0.7 0.9 Beta Beta Source: Bloomberg, processed

51 FINANCIAL STABILITY REVIEW No. 27, September 2016

In addition to classification based on the underlying closed-end funds. Growth of closed-end and open- assets, mutual fund products are also categorised ended funds in the reporting period stood at as open-ended or closed-end funds. Most mutual 2.31% and 8.84% respectively, accelerating from fund products circulating on domestic markets 1.64% and 0.92%. The performance of open-ended are open-ended funds, which can be resold to funds was considered more promising due to the the investment manager. As of the first semester persistent upward trend. In contrast, closed-end of 2016, around 1,315 open-ended mutual fund funds are more stable because they are less liquid. products were available, compared to just 62

Graph 2.47 Average NAV of Closed-End and Open-Ended Funds

Dec’12 = 100 120 115 110 105 100 95 90 85 80 Jul-14 Jul-15 Jan-14 Jan-15 Jan-16 Sep-14 Sep-15 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16 May-14 May-15 May-16

Closed-End Funds Open-Ended Funds Source: Bloomberg, processed

(PUAS) was recorded at Rp628 billion, down from 2.3. Assessment of Islamic Financial Rp736 billion. In addition, the average yield on Market Conditions and Risks Mudharabah Investment Certificates (SIMA), as the leading PUAS instrument, fell from 6.19% to Islamic financial market performance decelerated 5.05% during the reporting period. The lower PUAS in the first semester of 2016, as the domestic volume, combined with lower SIMA yield, indicated and global economies continued to moderate. that Islamic banks could adequately meet demand Nonetheless, the Islamic capital market, particularly for liquidity without abnormal demand for liquidity government sukuk, posted positive performance arising between Islamic banks. Nevertheless, a on rising demand despite sluggish performance at shift did occur towards shorter-tenor liquidity Islamic financial institutions.

instruments, indicating greater prudence at Islamic 2.3.1. Islamic Money Market banks. 2.3.1.1. Islamic Interbank Money Market (PUAS) Risks on the Islamic interbank money market In addition to Mudharabah Investment Certificates (PUAS) were well mitigated during the first (SIMA), repurchases (repo) of Islamic Bank semester of 2016, indicated by decreasing volume Indonesia Certificates (SBIS) and Government and yield. The average monthly transaction Islamic Securities (SBSN) represented an alternative volume on the Islamic interbank money market way to meet demand for short-term liquidity due to

52 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 2.48 Islamic Interbank Money Market and Islamic Bank Graph 2.49 Islamic Interbank Money Market Performance and Indonesia Certificate Yield of Mudharabah Investment Certificates (SIMA) 12.000 80.00 1.800.000 8.00 60.00 1.600.000 10.000 40.00 1.400.000 7.00 8.000 1.200.000 20.00 6.000 1.000.000 6.00 0.00 4.000 800.000 -20.00 400.000 5.00 2.000 -40.00 200.000 0 -60.00 0 4.00

Jul-12 Jul-13 Jul-14 Jul-15 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16

Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Sep-12 Sep-13 Sep-14 Sep-15 May-12 May-13 May-14 May-15 May-16

PUAS SBIS SBIS Growth PUAS Volume SIMA Yield Volume Volume

Source: Bloomberg, processed Source: Bloomberg, processed their liquid nature. Like conditions on the Islamic The average monthly volume of Islamic repo interbank money market (PUAS), the average transactions tended to decline during the first monthly transaction volume of SBIS decreased semester of 2016, with Islamic repo transactions slightly from Rp7.4 trillion in the second semester recorded in just one month, namely June 2016 of 2015 to Rp7.2 trillion in the first half of 2016. worth Rp120 billion. Compared to the previous period, Islamic repo transaction volume is well 2.3.1.2. Islamic Repo Market down on the peak of Rp2.12 trillion recorded in Islamic repo transactions are conducted in December 2015. Consistent with the lower policy Indonesia pursuant to Bank Indonesia Regulation rate maintained by Bank Indonesia in the first (PBI) No. 17/4/2015, dated 27th April 2015, and half of the year, the repo rate also declined after Bank Indonesia Circular Letter (SEBI) No. 17/10/ peaking in December 2015. DKMP, dated 29th May 2015. At the beginning of 2016, the Financial Services Authority (OJK) An interesting phenomenon of the Islamic interbank released guidelines concerning the Indonesian repo market that emerged from 2014 – 2015 was Global Master Repurchase Agreement (GMRA) greater participation of conventional banks, which opted to manage their liquidity using Islamic

Graph 2.50 Nominal SBSN and Market price Graph 2.51 Market Price and Repo Rate

2.500.000.000.000 96 96 9 94 9 94 2.000.000.000.000 92 8 90 92 8 1.500.000.000.000 88 90 7 86 7 88 1.000.000.000.000 84 6 82 86 6 500.000.000.000 80 5 84 78 5 0 76 82 4 Jul-15 Jul-15 Jul-14 Jul-14 Jan-14 Jan-14 Jan-15 Jan-16 Jan-15 Jan-16 Oct-14 Oct-15 Oct-14 Oct-15 Apr-16 Apr-16 Apr-14 Apr-15 Apr-14 Apr-15

Nominal SBSN Avg Price Avg reporate Avg Price

Source: Bloomberg, processed Source: Bloomberg, processed

53 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 2.52 SBSN Issuances (2008 – 2016)

July 28,2016 146.69 2015 118.51 2014 75.54

2013 53.18

2012 57.09 2011 33.31 2010 26.97

2009 16.55 IDR trillion 2008 4.70

0 25 50 75 100 125 150

2008 2009 2010 2011 2012 2013 2014 2015 July 28, 2016 IFR 4.70 1.28 6.15 4.61 0.40 - - - - SR - 5.56 8.03 7.34 13.61 14.97 19.32 21.97 31.50 SNI - 7.03 - 9.04 9.64 17.24 17.75 26.42 33.41 SDHI - 2.69 12.78 11.00 15.34 - 12.86 4.50 1.00 SPN-S - - - 1.32 1.38 11.65 16.17 14.30 9.49 SPN-S NT ------5.08 2.54 PBS - - - - 16.71 9.32 9.45 46.25 68.76 Total 4.70 16.55 26.97 33.31 57.09 53.18 75.54 118.51 146.69

Source: Bloomberg, processed

as the basis for repo transactions on the capital repo transactions and SBSN as the underlying. market. Islamic repo transactions, however, were Such conditions show that the market considers not included within the scope of the GMRA. SBSN attractive because the instrument is secure, tradeable and offers high yields. Furthermore, Internationally, repo transaction guidelines in such transactions now come under the remit of the form of a GMRA reflect a market initiative. Bank Indonesia. Notwithstanding, considering the In Indonesia, however, the relevant authorities differences between Islamic and conventional repo initiated the process considering the passive transactions, it is important to remain vigilant of nature of the domestic markets. To promote Islamic bank compliance to the Bank Indonesia regulations repo transactions between market players, Bank pertaining to Islamic repo transactions. Moving Indonesia helped formulate and issue the Mini forward, the role of Islamic repo transactions Master Repo Agreement (mini MRA), in accord with to manage liquidity at conventional and Islamic the Islamic banking industry collectively under the banks will expand as more instruments are made auspices of the Indonesian Islamic Global Market available, such as sukuk, which can be used as the Association (IIGMA) in the form of a Memorandum underlying asset for Islamic repo transactions. of Understanding (MoU). The Mini MRA MoU was singed on 2nd July 2015 by 18 Islamic banks, 2.3.2. Sukuk Market including Islamic banks and sharia business units. 2.3.2.1. Government Sukuk Market Conventional banks represented by the Indonesian The accumulated volume of SBSN issuances from Foreign Exchange Market Committee (IFEMC) are 2008 – July 2016 totalled Rp532.53 trillion, with yet to sign the mini MRA MoU, however, requiring the current year (as of 28th July 2016) contributing more time to learn the concept of Islamic repo Rp146.69 trillion. In the first semester of 2016, transactions. SBSN issuances were dominated by Project Based Sukuk (PBS) worth Rp68.76 trillion, followed by Global Sukuk (SNI) amounting to Rp33.41 trillion

54 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

and Retail Sukuk (RS) at Rp31.5 trillion. PBS Of the various types of Government Islamic are available in medium and long-term tenors, Securities (SBSN), PBS enjoyed significant gains ranging from 5-30 years. On the other hand, SNI from Rp9.45 trillion in 2014 to Rp46.25 trillion are medium-term sukuk ranging from 5-10 years. in 2015 and Rp68.76 trillion in 2016 (as of 28th Conversely, RS are short-term sukuk of less than July 2016). Consequently, the annual SBSN gain three years. Issuances of all three types of sukuk of averaged 65.7%. Based on the latest developments, varying tenors contribute positively to complement the plans to issue the the yield curve information for the Indonesian inaugural series of non-tradeable savings sukuk sukuk market. Nonetheless, more tenors should be in the second half of 2016 with tenors of 2 years added in the future (Graph 2.50). (wakalah contracts) and early redemptions available.

Graph 2.53 Outstanding SBSN (2008 – 2016) (Trillion IDR) (Trillion IDR) 140 450 386.17 120 400 350 100 300 80 250

60 200 150 40 100 20 50 0 0 July 28, 2008 2009 2010 2011 2012 2013 2014 2015 2016 IFR 4.70 5.98 12.13 16.74 17.14 16.59 16.59 11.24 11.24 SR - 5.56 13.59 20.93 28.99 35.92 47.91 56.26 72.79 SNI - 8.52 8.52 21.64 41.31 54.42 65.57 91.79 124.57 SDHI - 2.69 12.78 23.78 35.78 31.53 33.20 36.70 36.70 SPNS - - - 1.32 0.20 8.63 10.74 11.01 7.49 PBS - - - - 16.71 26.03 35.48 82.72 130.86 SPNS-NT ------5.08 2.54 Total 4.70 22.74 47.02 84.41 140.12 173.13 209.47 294.80 386.17

Source: Bloomberg, processed Graph 2.54 SBSN Maturity Profile (Trillion IDR) 90 1USD = Rp 13,113

75

60

45

30

15

0 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2036 2037 2038 2040 2043 TOTAL

TOAL 10.02 22.49 81.28 60.67 38.33 14.83 19.67 8.71 21.67 29.77 22.95 3.79 0.00 3.86 2.18 14.25 4.11 10.15 0.00 7.53 9.93 386.17 SPNS-NT 2.54 ------2.54 SDHI - 2.00 2.50 6.00 6.50 5.00 5.34 1.50 2.00 2.00 - - - 3.86 ------36.70 SNI - - 13.11 19.67 - 9.83 13.11 - 19.67 26.23 22.95 ------124.57 SR - 19.32 21.97 31.50 ------72.79 PBS - - 41.72 3.50 31.58 - 1.22 7.21 - - - 3.79 - - - 14.25 - 10.15 - 7.53 9.93 130.86 IFR - 1.17 1.99 - 0.25 - - - - 1.55 - - - - 2.18 - 4.11 - - - - 11.24 SPNS 7.49 ------7.49

Source: Bloomberg, processed

55 FINANCIAL STABILITY REVIEW No. 27, September 2016

Looking at the maturity profile, the availability of The majority of government-issued SNSB in SBSN instruments for the upcoming 10 years until Indonesia are tradeable and relatively liquid. By 2026 has been maintained. Most SBSN will mature currency, investors continued to favour rupiah- in 2018, totalling Rp81.3 trillion, consisting of PBS denominated SBSN, accounting for 67.74%, worth Rp41.7 trillion, and in 2019, totalling Rp60.7 with only 32.3% of SBSN denominated in a trillion, with RS accounting for 31.5 trillion. For foreign currency. Nonetheless, in line with the the period from 2020 to 2026, only around Rp8-38 Government’s avowed commitment to develop the trillion of SBSN will mature. sukuk market, the portion of SBSN denominated in a foreign currency is expected to continue growing. PBS and SNI continued to dominate Government Islamic Securities (SBSN), accounting for 33.8% 2.3.2.2. Corporate Sukuk Market and 32.3% respectively of total outstanding SBSN Corporate sukuk development remained positive at Rp 386.17 trillion. By tenor, most SBSN (85.5%) in the first semester of 2016, with the value of were short and medium-term tenors of 0-10 outstanding sukuk recorded at Rp11.1 trillion. The years, while the remaining 14.5% were long term. trend declined in July 2016, however, slipping to Such conditions safeguarded outright and repo Rp10.75 trillion. The months of June and July 2016 transaction continuity on Islamic financial markets, were interesting because they represented the with short and medium-term SBSN utilised for first time that the value of outstanding corporate investment purposes and liquidity management. sukuk has topped Rp10 trillion. In July 2016, the

Graph 2.55 SBSN Distribution by Type Graph 2.57 SBSN Distribution by Currency

IDR130,86T PBS 33.88% IDR227,63T 0-5 years SNI IDR124,57T 58.94% 32.26% SR IDR72,79T 18.85% IDR36,70T IDR102,77T SDHI 9.50% 6-10 years 26.61% IDR11,24T IFR 2.91% IDR7,49T SPNS 1.94% IDR55,78T > 10 years 14.44% IDR2,54T (trillion IDR) (trillion IDR) SPST-NT 0.66%

0 25 50 75 0 50 100 150 200 250

Graph 2.56 SBSN Distribution by Tenor Graph 2.58 SBSN Distribution by Tradability

IDR261,60T IDR346,94T IDR 67.74% Tradeable 89.84%

IDR124,57T IDR39,23T USD 32.26% Non-tradable 10.16%

(trillion IDR) (trillion IDR)

0 50 100 150 200 250 300 0 100 200 300 400

56 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

accumulated value of corporate sukuk reached Makmur Tbk (INDF). In addition to solid share Rp18.7 trillion, up Rp200 billion on the aggregate price performance, the Islamic stock market also figure for June 2016 at Rp18.5 trillion. A total of benefitted from large-scale socialisation activities 47 corporate sukuk are outstanding of the 95 total conducted by the Indonesia Stock Exchange for the issuances through to July 2016. public on the advantages of investing in Islamic stocks. In addition, the regulators and securities

Graph 2.59 Corporate Sukuk Performance companies also facilitated customers opening 18.692,40 19.000 120 accounts for Islamic stocks. Consequently, the 17.000 95 100 15.000 public has acquired greater understanding of the

13.000 10.756,00 80 capital market and is more interested to invest 11.000 60 7.000 there.

5.000 49 40 3.000 20 1.000 Compared to the previous semester, the 0 0 performance of Islamic mutual funds deteriorated,

Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Mar-14May-14 Sep-14Nov-14 Mar-15May-15 Sep-15Nov-15 Mar-16May-16 indicated by a 10.74% contraction in the NAV Total Issuances (rhs) Total Outstanding (rhs) Total Issue Value Outstanding Value from Rp11 trillion to 9.9 trillion. Such conditions Source: Bloomberg, processed contradicted conventional mutual funds, for which growth remained in positive territory. In June 2016, 2.3.3. Islamic Stock Market and Mutual Funds of the 1,226 mutual fund products available in Historically, the Islamic stock market in Indonesia Indonesia, 106 or 8.65% were Islamic mutual funds, began with the Jakarta Islamic Index (JII) in the increasing from 93 products previously. year 2000. Through to the first semester of 2016, 321 Islamic stocks have been issued from 307 listed Table 2.12 Issuers of Islamic Stocks

STOCK issuers, 4 public companies and 10 unlisted issuers, Total Year Listed Public Unlisted IPO Issuers with no IPOs. The total declined 4.18% on the 335 Issuers Companies Issuers 2011 Semester I 217 3 9 5 234 issued in the previous period due to slower real 2011 Semester II 238 3 9 3 253 sector growth in the first half of 2016. 2012 Semester I 280 5 9 10 304 2012 Semester II 302 5 10 4 321

2013 Semester I 288 5 9 8 310 The risks on Islamic financial markets eased in 2013 Semester II 313 5 10 8 336 the first semester of 2016, indicated by less 2014 Semester I 301 4 12 5 322 2014 Semester II 314 4 13 3 334 volatility and a stronger Jakarta Islamic Index 2014 Semester I 313 4 13 4 334 (JII). Index performance was driven by blue-chip 2014 Semester II 315 4 12 4 335 2014 Semester I 307 4 10 0 321 stocks, including PT Astra International (AASI), PT Source : OJK Telekomunikasi Indonesia (TLKM), PT Perusahaan Gas Negara Tbk (PGAS), PT Semen Indonesia (Persero) Tbk (SMGR) and PT Indofood Sukses

57 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 2.60 Growth of Islamic Stock Issuers

400 25.00%

350 20.00% 300 15.00% 250 10.00% 200 5.00% 150 0.00% 100

50 -5.00%

0 -10.00% Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I 2011 2012 2013 2014 2015 2016 Total Issuers Growth of Issuers

Source : OJK

Graph 2.61 Jakarta Islamic Index (JII) Graph 2.62 Jakarta Islamic Index Volatility

750 50

45 750 40 35 700 30

25 650 20 600 15

10 550 5

500 0

02/02/201302/06/201302/10/201302/02/201402/06/201402/10/201402/02/201502/06/201502/10/201502/02/2016 02/06/2016 02/02/201302/06/201302/10/201302/02/201402/06/201402/10/201402/02/201502/06/201502/10/201502/02/2016 02/06/2016

Source : Bloomberg Source : Bloomberg

Table 2.13 Islamic Mutual Funds

Comparison of Total Mutual Funds Comparison of NAV (Rp, billions) Year Islamic Mutual Conventional Total Mutual Islamic Mutual Conventional Total Mutual Percentage Percentage Funds Mutual Funds Funds Funds Mutual Funds Funds 2010 48 564 612 7.84% 5.225,78 143.861,59 149.087,37 3.51% 2011 50 596 646 7.74% 5.564,79 162.672,10 168.236,89 3.31% 2012 58 696 754 7.69% 8.050,07 204.541,97 212.592,04 3.97% 2013 65 758 823 7.90% 9.432,19 183.112,33 192.544,52 4.90% 2014 74 820 894 8.31% 11.158,00 230.304,09 241.426,09 4.65% 2015 93 998 1091 8.52% 11.019,43 260.949,57 271.969,00 4.05% 2016 January 94 906 1000 9.40% 10.396,86 266.704,38 277.101,24 3.75% February 96 1026 1122 8.56% 9.061,02 274.712,98 283.774,00 3.19% March 99 1051 1150 8.61% 9.470,14 283.316,17 292.786,31 3.23% April 101 1087 1188 8.50% 9.303,47 289.377,62 298.681,08 3.11% May 102 1103 1205 8.46% 9.556,16 292.493,33 302.049,49 3.16% June 106 1120 1226 8.65% 9.901,24 299.540,37 309.441,60 3.20%

Source: Financial Services Authority (OJK)

58 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 2.63 Islamic Mutual Funds

12.000 120

10.000 100

8.000 80

6.000 60

4.000 40

2.000 20

0 0 2010 2011 2012 2013 2014 2015 Jan Feb Mar Apr May June

Islamic Mutual Funds NAV of Islamic Mutual Funds

Source: Financial Services Authority (OJK)

59 FINANCIAL STABILITY REVIEW No. 27, September 2016

Foreign Currency Structured Product Transactions Box 2.1 against the Rupiah as Call Spread Options

The domestic foreign exchange market is an Thailand at USD13.0 billion per day. In Indonesia, important financial market in Indonesia. Through spot transactions dominate foreign exchange the foreign exchange market, economic players, transactions, accounting for 60% of the total. including households and the corporate sector, Meanwhile, the use of derivatives, such as FX can purchase other currencies as required. The Forwards, FX Swaps and FX Options, for hedging foreign exchange market also offers hedging purposes remains relatively limited. instruments against currency risk to economic players looking for security and convenience Seeking to overcome the outstanding when conducting business by reducing the constraints, Bank Indonesia constantly adverse impact of exchange rate fluctuations on promotes hedging against foreign exchange corporate performance. exposure. Such efforts to bolster market liquidity for hedging instruments are important Notwithstanding, the domestic foreign exchange because Bank Indonesia Regulation (PBI) No. market in Indonesia contains structural 16/21/PBI/2014, concerning the Application of weaknesses, including limited liquidity and Prudential Principles for Nonbank Corporations the prevalence of spot transactions. In 2016, to Manage External Debt, requires indebted the average daily volume of domestic foreign corporations to hedge a minimum of 25% of net exchange transactions reached USD5.0 billion, liabilities using domestic banks. To expand and up from USD4.5 billion per day in 2015. Despite enrich hedging instruments, Bank Indonesia the increase, the transaction volume was deregulated the domestic foreign exchange much smaller than that recorded in Malaysia, market in 2014 and 2015 through promulgation for example, at USD11.0 billion per day and of Bank Indonesia Regulation (PBI) No. 16/16/ PBI/2014 and Bank Indonesia Regulation Box Graph 2.1.1 Turnover on the Domestic Foreign Exchange Market (PBI) No. 16/17/PBI/2014 concerning Foreign 6,000,000 Exchange Transactions against the Rupiah $ Ribu 5,000,000 between Banks and Domestic or Foreign 4,000,000 Parties. The regulation was refined by licensing 3,000,000 net settlement of derivative transactions and 2,000,000

1,000,000 introducing cross-currency swap transactions. On the other hand, prudential principles were still maintained through mandatory reporting of Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Sep-12 Sep-13 Sep-14 Sep-15 May-12 May-13 May-14 May-15 May-16

Source: Daily Reports of Commercial Banks the underlying document.

60 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Relatively high hedging costs in Indonesia stem the hedging premium on the call buying option from the prolonged process to expand liquidity can be deducted from the income premium of on the foreign exchange market. Currently, the call selling option. Consequently, however, hedging costs in Indonesia, as reflected by the the effectiveness of hedging through call spread swap premium on 1-month tenors, stand at options is more limited in certain exchange around 6%, well above the costs reported in rate ranges. Hedging costs through call spread other countries. For example, hedging costs in options are thought to range from 1.5% to 2.5%. Malaysia are 3.3% and just 1% in Thailand.

Box Graph 2.1.2 Hedging Costs (1-Month Swap Premium): According to call spread option contracts, A Comparison of Several Countries market players can simultaneously buy a call 8.00 7.38 7.13 option, paying a certain premium (for instance 7.00 6.84 6.68 6.7 6.00 6%) and then sell the call option at a certain

5.00 premium (for instance 4%), thus the net hedging 4.00 cost incurred using the call spread option is 3.36 3.36 3.34 3.37 3.36 3.00 2.63 2.63 2.56 2.46 2.40 just 2%. Lower hedging costs are expected to 2.00 0.99 1.27 1.17 1.17 1.00 increase incentives for hedging and facilitate 1.00 0.83 0.82 0.82 0.84 0.77 hedging transactions. 13-Jun-16 14-Jun-16 15-Jun-16 16-Jun-16 17-Jun-16 Source : Bloomberg Box Graph 2.1.3 Call Spread Option Transaction Mechanism

Supporting hedging transactions on the Profit Buy Call on USD Strike price 1 = Rp13.000 domestic foreign exchange market, Bank

Indonesia issued a new instrument that is more Unlimited gain 10.000 premium cost 16.000 efficient but also comparatively more complex, namely a structured product in the form of Loss call spread options. A call spread option is a Sell Call dengan Strike Price 1 - If USD depreciates to below the strike price of 1, therefore bought on the market with a premium cost of 10,000 simultaneous call buying option (buying the - If the USD appreciates to above the strike price of 1 – unlimited gain

right to purchase currency at a certain future Profit Sell Call on USD price) and a call selling option (selling the right Strike price 2 = Rp14.000

to purchase currency at a certain future price) 4.000 premium cost combined into one contract with the same value 16.000 Unlimited loss but different strike prices. Call spread options Loss represent a more efficient hedging instrument Sell Call dengan Strike Price 2 - If the USD depreciates to below the strike price of 2, the call buyer only receives the premium because of lower costs than plain vanilla - If the USD appreciates to above the strike price of 2 – unlimited loss instruments. Hedging costs are lower because Source : Bank Indonesia

61 FINANCIAL STABILITY REVIEW No. 27, September 2016

• Illustration: Structure Products, only BUKU 3 and 4 banks A market player has foreign currency are permitted to settle such transactions. In liabilities and intends to hedge against addition, this form of structured product can the currency risk. The player expects the only be sold to professional customers (financial USD/IDR exchange rate to fluctuate in the companies or firms with a capital base of > Rp13,000 – 14,000 per USD range and, Rp20 billion and operating for a minimum of 36 therefore, hedges against fluctuations months). Banks offering structured products are within that range. The player could initiate also required to apply prudential principles and a call spread option on the Rp13,000 – sound risk management. 14,000 per USD range, with a hedging cost of just 2% compared to 6% through a call Bank Indonesia is currently in the process of buying option alone. honing existing regulations, thereby making call spread options available to more bank Despite the clear advantages of low cost customers as quickly as possible. Bank hedging, not all banks are able to offer such Indonesia also expects the presence of more transactions. Pursuant to OJK Regulation (POJK) efficient hedging instruments to support tax No. 7/POJK.03/2016 concerning Prudential amnesty implementation, particularly for those Principles for Commercial Banks engaged with repatriating funds.

62 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box 2.2 Waqf-based Sukuk to Empower Waqf Assets

The Islamic economy is becoming increasingly • More than 90% of allotted waqf land is used developed, as evidenced by the growing diversity for education, mosques and burial grounds. of sharia-compliant (halal) businesses, including • The asset exchange policy for strategic land Islamic hotels, Islamic tourism, Islamic hospitals in large cities to economically less viable and schools, halal cosmetics, Muslim fashion land. and so on. Nonetheless, one potential asset for • Lack of support from private or government Muslims that is currently underdeveloped is bank/nonbank financial institutions. Waqf. According to the Indonesia Waqf Board • The waqf land database remains incomplete. (BWI), as the relevant authority, waqf land in • Most nazhir are still individuals. Indonesia is disbursed across 435,395 locations • Lack of socialisation activities and differing totalling 414 million hectares (5 million km2). opinions. Based on consolidation of the Indonesia Waqf • Lack of public confidence in waqf Board (BWI) and Ministry for Religious Affairs, organisations. the waqf land is valued at around Rp2,050 trillion. Meanwhile, potential waqf funds total The constraints have led to less productive waqf around Rp60 trillion, of which the proceeds are asset management (refer to Box Figure 2.1.1). stored by the new BWI worth Rp350 billion. For example, moveable waqf assets in the form of cash or gold as well as immovable waqf assets The remain several constraints to waqf asset as land or buildings are generally used to build management as follows: a place of worship (mosque or musholla), burial • Understanding of the public, waqif grounds or Islamic boarding school, which do not (founder/donor), nazhir and government produce a fixed income. Meanwhile, operating as regulator concerning productive waqf the nazhir or waqf assets requires a fixed remains extremely low. income, which is normally covered by income

Box Figure 2.2.1 Less Productive Waqf Asset Management

- Mosque Land - Mosque Buildings - Burial Grounds Moveable: - Boarding School Land Cash, Gold - Boarding School Buildings

Sources of Funds - Mosque Land Waqf Nazhir Cost - Mosque Buildings Centre - Burial Grounds - Boarding School Land - Boarding School Buildings

Immovable: Land, Buildings - Mosque - Boarding School - Burial Grounds

Source: Bank Indonesia

63 FINANCIAL STABILITY REVIEW No. 27, September 2016

from the mosque or public contributions. One of owned enterprises have greater flexibility the most binding constraints to waqf land asset when determining projects and payment plans, development is the lack of funds accumulated including the possible issuance of SOE sukuk to by the nazhir to construct a building on the fund waqf assets. waqf land. In practice, however, on the Islamic • Several state-owned enterprises have financial market funds can be accumulated experience of issuing sukuk, for example through issuances of sukuk. Therefore, in Garuda, PLN and so on. conjunction with the Indonesia Waqf Board • Relevant ministries could provide support (BWI), Ministry of Finance and Ministry of State- to state-owned enterprises interested in Owned Enterprises, Bank Indonesia has held issuing waqf-based SOE sukuk, in the form of discussions and developed a waqf-based sukuk credit enhancements, supporting regulations, model for state-owned enterprises in order to socialisation activities and additional leverage the large potential of available waqf capitalisation. land. In addition, the Indonesia Waqf Board (BWI) shall Sukuk were chosen as an alternative way to play an important role of coordinating with the accumulate funds considering that: nazhir or could even become a nazhir of the waqf • Sukuk are already a popular Islamic financial assets used as the underlying of the SOE sukuk market instrument in Indonesia and traded issued. Legal assurance concerning the status, relatively actively. quality, quantity and prospects of the waqf asset • Sukuk have already been issued by the could also originate from BWI recommendations or government, state-owned enterprises, decision-making. Meanwhile, Bank Indonesia has private corporations as well as conventional the strategic role of deepening the Islamic financial and Islamic banks. markets, whilst making them more attractive for • A developed sukuk market already exists waqf-based SOE sukuk. Bank Indonesia efforts to with investor interest continuing to grow. deepen the Islamic financial markets, by issuing • Sukuk are a viable alternative investment Islamic repo and hedging regulations as well as instrument on the Islamic financial market facilitating the markets to produce an Islamic for banks and nonbank financial institutions. Mini Master Repo Agreement (MRA) and Islamic Market Code of Conduct (ICOC) that includes public State-owned enterprises, particularly those that socialisation and education activities, will improve operate in the construction and infrastructure the success of waqf-based SOE sukuk. sectors, could issue waqf-based sukuk due to the following: From a macro perspective, the Islamic economy • • Compared to the government, state- considers waqf-based sukuk as a form of

64 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

coordination and cooperation between the financial market instruments, attract investors, real sector and financial sector through Islamic boost trade on the sukuk market and help financial market instruments (refer to Box the government provide social services and Figure 2.2.2). Not only for commercial economic facilities. purposes (investment and business) but social activities can also be financed using social funds Based on the intensive discussions between (for instance waqf). Funds can be mobilised from Bank Indonesia, the Indonesia Waqf Board the financial sector through sukuk issuances (BWI), Ministry of Finance and Ministry of State- for example. Consequently, sukuk would play a Owned Enterprises, a model was developed for strategic role in terms of supporting economic waqf-based sukuk to potentially be issued by activities, while creating economic and social state-owned enterprises that empowers waqf stability for public betterment. land assets as presented in Box Figure 2.2.3.

Waqf-based sukuk are just one way sukuk could The contract begins with a long-term lease empower the social sector. In fact, waqf-based agreement between the nazhir and state- sukuk have a dual role, not only to provide owned enterprise, where the nazhir, as waqf social benefits but also commercial advantages, asset manager, transfers the asset to the state- including Islamic financial market deepening. owned enterprise. Thereafter, the state-owned For instance, waqf sukuk issued by state- enterprise issues a sukuk contract (sale and owned enterprises will help diversify Islamic lease back) to the investor, namely an Islamic

Box Figure 2.2.2 Real Economic and Islamic Financial Market Conditions

Sukuk

Islamic Financial Economic Public Institutions Stability Prosperity Economic financing using waqf-based sukuk Economic Conventional Stability Financial Institutions

Social Prosperity Product Variation Social Purposes Indonesia Waqf Board (BWI) Increased Volume - Prosperity Ministry of Economic - Public Waqf Activities - Social Services Finance Increased Frequency

State-Owned Enterprises, Other Broader Customer Base Stimulate economic activities, Commercial Purposes Institutions ameliorate prosperity and create Islamic Financial Market Deepening price stability Institutions

Source: Bank Indonesia

65 FINANCIAL STABILITY REVIEW No. 27, September 2016

or conventional financial institution, in order as well as the gains from the sukuk issuance to generate funds to develop the waqf land. (as the issuer, trade activity on the financial The state-owned enterprise then contacts the market and so on) and as a market maker. contractor to begin construction for a given • For Bank Indonesia and the Ministry of duration. Upon completion, the building is Finance, the benefits include support for leased to a third party pursuant to a lease government social project realisation and agreement used by the state-owned enterprise Islamic financial market deepening. to pay the rental fee to the investor, as the

Box Figure 2.2.3 Waqf-Based Sukuk (SOE)

Credit enhancement BWI Ministry of (3) Transfer sukuk funds Finance

Endorsement & (2) Issue sukuk contract Recommendation

(1) Long Lease Agreement Pengalihan Manfaat Long Lease Objek Waqf Nazhir State-Owned Investor : Enterprises LKS, LKK (7) Lease income (8) Contract instalments and fees (9) Transfer building, (4) Contract with Wakalah Pemberi Sewa end of year 35 contractor Regulatory support Repo Ministry of Ministry of (5) Contruction Contractor State-Owned State-Owned Enterprises Enterprises

Repo, TENANT Islamic Financial Outright (6) Leasing Market (rental fee)

Source: Bank Indonesia

holder of the sukuk. In the final period, after • For the public, the benefits include greater the lease agreement has expired, the building public facilities and increased economic is transferred back to the nazhir from the state- and social activities. owned enterprise. The model has already received support from A number of benefits for several parties will the Ministry of Finance, Ministry of State- materialise if this model can be applied as Owned Enterprises, Indonesia Waqf Board follows: (BWI) and Bank Indonesia, thus the state- • For the nazhir, the advantages include owned enterprises and other interested parties project realisation on waqf land in addition can consider its adoption and uptake. Moving to receiving a portion of the returns forward, several factors must be addressed as generated by the building constructed on follows: the waqf land. • Coordination between nazhir and the • For the state-owned enterprise, the benefits Indonesia Waqf Board (BWI) concerning include receiving a return on project revenue stipulation of waqf assets, sukuk (model)

66 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

structure, cash flow and the portion of sukuk proceeds as well as the length of tenors. • Regulatory preparedness at the Ministry of State-Owned Enterprises, feasibility studies, as well as sukuk market assessments and simulations. • Socialisation and education concerning waqf-based SOE sukuk. • Financial market deepening (repo to BI, Islamic repo, Islamic hedging and so on).

67 FINANCIAL STABILITY REVIEW No. 27, September 2016

Strengthening JIBOR as the Price Reference Rate Box 2.3 on the Money Markets

The short-term yield curve is vital in terms of regulation again in 2016 in order to further producing a long-term yield curve to reflect the improve JIBOR credibility. From 2015 until costs of long-term financing/investments. There April 2016, JIBOR use continued to expand is a price reference on the money market, which and develop, as indicated by the transactable not only helps determine the short-term yield feature that benefits contributor banks when curve but could enhance efficiency through transacting with other contributors. The simultaneous utilisation for various financial transactable feature has also been effective in transactions. Such a reference would facilitate creating money market transactions/liquidity, various financial transactions for market particularly for longer tenors such as 1 month, players, including portfolio diversification, where market liquidity has traditionally been that could ultimately contribute to economic tight. development. The success of previous adjustments encouraged The JIBOR regulation was honed in April 2015 Bank Indonesia to refine the JIBOR regulations to enhance credibility. The move was successful again in 2016 by extending the window time, enough for Bank Indonesia to adjust the JIBOR nominal value and tenors applicable for the transactable mechanism. Effective from 1st

Box Graph 2.3.1Benefits of the Transactable Mechanism by Contributor Banks

Frequency Frequency: Interbank Transactions under Volume Volume : Indikasi Transaksi PUAB (times) JIBOR Transactable mechanism (Rp Miliar) under Mekanisme Transactable JIBOR 140 1400

13 130 120 21 1200 210 7 70 15 150 100 11 1000 110 56 560 36 360 17 1 170 10 4 40 39 390 80 3 20 800 30 200 15 150 9 90 60 8 3 600 80 30 12 120 18 8 180 80 13 6 130 60 95 11 950 110 0 0 40 80 400 800 78 73 780 730 69 0 690 0 64 58 640 580 50 46 4 500 460 40 43 46 40 430 460 400 20 32 200 320

0 - Jul-15 Jul-15 Jan-16 Jan-16 Jun-15 Jun-15 Oct-15 Oct-15 Feb-16 Feb-16 Apr-15 Apr-15 Apr-16 Apr-16 Sep-15 Sep-15 Des-15 Dec-15 Nov-15 Mar-16 Mar-16 Aug-15 Nop-15 Aug-15 May-15 May-15 1 Month 1 Week Overnight 1 Month 1 Week Overnight

Contribution of Liquidity Creation on Money Market Year under the Window Time Transactable Mechanism to Industry-Wide Money Market Liquidity Transaction Frequency Transaction Volume O/N 3.5% 0.45% 1 Week 2.2% 0.3% 1 Month 20% 3%

Source: Bank Indonesia assessment

68 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

June 2016, the transactable window time was doubled from 10 to 20 minutes. Furthermore, nominal transaction value was also doubled from Rp10 billion to Rp20 billion, while total demand for transactions from all asking banks met by quoting banks has not exceeded Rp20 billion per day. To enhance JIBOR credibility for longer tenors, the transactable mechanism will also be extended to tenors of 3 months on 1st September 2016 through promulgation of Bank Indonesia Circular Letter (SEBI) No. 18/14/ DPPK concerning Interbank Rates (JIBOR). By refining the regulations, JIBOR utilisation is expected to increase, hence boosting market liquidity and ultimately accelerating financial market deepening and expanding JIBOR’s role in development financing.

69

In the first half of 2016, households and the corporate sector began to recover despite continuing to track a downward trend. Economic growth in the second quarter of 2016 led to household and corporate optimism concerning the economic outlook. Notwithstanding, the economic growth recorded towards the end of the second quarter was attributed primarily to the seasonal effects of increased consumption during the approach to Eid-ul-Fitr, therefore, economic momentum failed to have a significant impact on household performance. Consequently, household performance continued to deteriorate despite increased optimism, indicated by slower growth of new loans and a rising level of non-performing loans (NPL), which were still controlled below the threshold.

Similar to households, corporate sector performance also worsened in the reporting period. Ongoing global economic moderation undermined demand for exports, thus the slight gains in commodity prices did not translate into corporate performance. Waning demand for exports was slightly offset by growing domestic demand as the economy accelerated in the second quarter of 2016. Nevertheless, modest economic momentum was not transmitted into corporate performance gains. Furthermore, credit growth slowed and corporate repayment capacity decreased, indicating rising non-performing loans (NPL) as well as efforts to restructure offshore corporate loans. Moving forward, potential risk from the corporate sector demands vigilance in line with unstable export performance against a backdrop of large-scale external debt.

HOUSEHOLDS AND THE CORPORATE3 SECTOR FINANCIAL STABILITY REVIEW No. 27, September 2016

Household and Corporate Performance began to Improve despite Continuing to Track a Downward Trend in line with Sluggish Economic Growth and Fewer Exports but the Risks were Mitigated

Household performance slowed but the risks were controlled

Household Consumption Robust Ability to Save Decreased Portion of household income Portion of saving used for consumption to households to 70.63% 81.49%

Individual NPL to Growth of individual Growth of individual LOAN % deposits to loans to 1.75 7.18% (yoy) Rp 7.92% (yoy)

Corporate performance remained sluggish but the risks were mitigated

Profitability Liquidity Debt Repayment

Rp and Solvency Capacity Rp ROA to Rp 4.75% Rp Current Ratio to DSR to 1.45 75.30% ROE to 10.05% TA/TL to DER to 1.93% 1.08%

Deposit Growth to Credit Growth to Gross NPL to % % % 9.95 (yoy) 12.13 Rp 3.56

72 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

(yoy), driven by sales of electronic devices (audio/ 3.1. Household Sector Assessment video) (Graph 3.2).

Graph 3.2 Real Sales Growth % 40 3.1.1. Household Sector Profile and Sources of 30 Vulnerability 22.8 20 20.6 Economic growth gained momentum in the first 13.6 15.5

10 8.5 6.2 half of 2016 compared to conditions in 2015, 4.0 3.7 1.5 2.6 0 which inflated household optimism concerning the -3.9 domestic economic outlook. Stronger economic -10

-20 growth, primarily at the end of the first semester, 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6 7 8 9 101112 1 2 3 4 5 6* 7** was supported by an increase in household 2014 2015 2016 Holy Fasting Month Growth (%, mtm) Growth (%, yoy) purchasing power during the approach to Eid- Notes: *) Preliminary Data **) Preliminary Data ul-Fitr, which elevated household consumption Source: Retail Sales Survey, Bank Indonesia, June 2015 (Graph 3.1). The Consumer Confidence Index (CCI), which Graph 3.1 Contribution of Household Consumption to GDP illustrates consumer confidence in current (yoy) 105% 6.0% economic conditions, increased from 107.5 at the

90% end of 2015 to 113.7 at the end of the first semester 5.6% 75% of 2016. Both components, namely the Current 5.18% 5.2% 60% Economic Condition Index (CECI) and the Consumer 45% 5.04% 4.8% Expectation Index (CEI), contributed to the gains. 30% 4.4% 15% The CECI, which reveals consumer perception of

0% 4.0% current economic conditions, increased from 94.0 I II III IV I II III IV I II III IV I II 2013 2014 2015 2016 to 99.9 over the same period (Graph 3.3), triggered Proportion of Household Household Consumption Growth (rhs) Consumption to GDP by all components, namely optimism surrounding Proportion of Non-Household GDP Growth (rhs) Consumption to GDP job availability, current incomes and conditions Source : BPS- for buying durable goods2. Likewise, the Consumer Household optimism on economic conditions was Expectation Index (CEI), which shows consumer corroborated by the Real Sales Index (RSI) and expectations of future economic conditions in the Consumer Confidence Index (CCI). Preliminary data upcoming six months, also rallied on the back of from the Retail Sales Survey conducted at the end future job availability and business activity. The of the first semester revealed an RSI of 15.9% (yoy), government continued to release stimulus packages up from 11.4% (yoy) at the end of 2015.1 Retail sales in the first semester of 2016, containing policy of foods and non-foods surged, with information to ensure equitable development of electrical and communication equipment growing 28.9% infrastructure, beef price stabilisation measures in

1 The Real Sales Index (RSI) is used to detect sources of demand-side inflationary pressures and illustrate retail sales and consumption trends amongst the public. The survey is available at the official website of Bank Indonesia. 2 The Consumer Confidence Index (CCI) is a simple average of the Current Economic Condition Index (CECI) and the Consumer Expectation Index (CEI). The survey is available at the official website of Bank Indonesia.

73 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 3.3 Consumer Confidence Index (CCI), Current Economic Condition Index (CECI) and Consumer Expectation Index (CEI)

(Index, Weighted Average of 18 Cities) 140.0

130.0

120.0 119.1 113.7 112.1 110.0 110.5 optimistic 111.6 110.5 100.0

Effect of Fuel Price Hike 90.0 Effect of Fuel Price Hike Pessimistic Effect of Fuel Price Reduciton 80.0 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 2014 2015 2016 Current Economic Condition Index (CECI) Consumer Confidence Index (CCI) Consumer Expectation Index (CEI) Quarterly Consumer Confidence Index (CCI) Source: Consumer Survey (18 Cities), Bank Indonesia, December 2015

rural areas, facilitating investment and consumer (PEI) (September 2016) experienced a -4.1-point protection for micro, small and medium enterprises decline on the position one year earlier at 156.4 (MSMEs) as well as approving implementation of (Graph 3.4). furthermore, inflationary pressures the Tax Amnesty in June 2016, which left households eased on all commodity groups, especially upbeat on the domestic economic outlook. foodstuffs and clothing.3 Consumers also predicted Household expectations of better future economic milder inflationary pressures in the next six months conditions was also reflected in slower rising prices. (December 2016), with the corresponding index Accordingly, the 3-month Price Expectations Index falling from 173.8 to 162.1 (Graph 3.5).

Graph 3.4 Three-Month Price Expectations Index (PEI) Graph 3.5 Six-Month Price Expectations Index (PEI)

(Index, weighted average of 18 cities) % (Index, weighted average of 18 cities) % 200 8.0 200 8.0

190 6.0 190 6.0 180 4.0 174,0 180 171,3 170 2.0 4.0 170 160 0.0 164.9 162.1 156,4 2,0 160 150 -2.0 157.7

140 -4.0 150 0.0 5 6 7 8 91011121 2 3 4 5 6 7 8 91011121 2 3 4 5 6 7 8 91011121 2 3 4 5 6 7 8 9 5 6 7 8 9101112 1 2 3 4 5 6 7 8 9101112 1 2 3 4 5 6 7 8 9101112 1 2 3 4 5 6 7 8 9101112 2013 2014 2015 2016 2013 2014 2015 2016

Quarterly inflation – BPS (rhs) 3-month PEI (lhs) Semesterly inflation – BPS (rhs) 6-month PEI (lhs) Eid-ul-Fitr Eid-ul-Fitr

Source: Consumer Survey (18 Cities), Bank Indonesia, June 2016

3 The Price Expectations Index (PEI) shows consumer price expectations for the upcoming three and six months.

74 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

3.1.2. Household Financial Performance less of their income to repay debt, with the debt Consumer optimism, driven by accelerated expectations index decreasing to 11.61%, while economic growth towards the end of the first the savings expectations index increased slightly to semester of 2016, did not necessarily improve 17.76% (Graph 3.6). the financial status of households in the reporting The greater propensity to consume, combined period. Increased household consumption, which with less allocation to repay debt, indicated that was the main driver of domestic economic growth households were trying to maintain consumption in the second quarter of 2016, stemmed primarily without relying on loans. Such behaviour was from seasonal factors during the approach to Eid- particularly acute amongst middle and upper class ul-Fitr. Against a backdrop of unstable economic households. Nonetheless, households tended to conditions, households were more prudent when refrain from withdrawing large loans. managing their finances because of higher incomes due to the food crop harvesting season and annual According to the consumer survey, heavily bonuses, coupled with greater consumption indebted households (DSR>30%) declined from spending towards Eid-ul-Fitr. 8.84% to 7.32% at the end of the first semester of 2016, thereby raising the proportion of households Household financial prudence was confirmed unable to save amongst that group from 18.51% to by the consumer survey conducted at the end of 26.82%. Other household groups, however, tended the first semester of 2016, which revealed that to maintain their savings as the percentage of households were more inclined to consume, households saving 30% of their income increased reflecting an increase in the propensity to consume from 17.79% in the second semester of 2015 to ratio to 70.63%. In contrast, households allocated 20.34% in the subsequent period (Table 3.2).

Graph 3.6 Allocation of Household Spending

June 2015 December 2015 June 2016

18.58% 17.36% 17.76%

13.73% 13.18% 11.61%

67.69% 69.46% 70.63%

Consumption Loan Repayments Saving

Source: Consumer Survey (30 Cities), Bank Indonesia, June 2016, processed

75 FINANCIAL STABILITY REVIEW No. 27, September 2016

3.1.3. Household Deposits4 in the Banking Industry share declined on the previous semester to 54.65%, Growth of household deposits accelerated in the which still surpassed the 54.00% posted one year reporting period as households allocated more earlier, however. of their income to saving. Therefore, household deposit growth increased from 6.35% (yoy) to 7.18% Household deposits increased primarily on savings (yoy), exceeding non-household deposit growth of deposits, which accelerated significantly from 7.98% 4.40% (yoy) (Graph 3.7). Although the household (yoy) in the second semester of 2015 to 15.82% sector continued to dominate bank deposits, the (yoy) in the subsequent period. Conversely, growth

Table 3.1 DSR Composition based on Monthly Income

Semester II 2015 Semester I 2016

DSR DSR Income Total Income Total 0-10% 10%-20% 20%-30% >30% 0-10% 10%-20% 20%-30% >30%

Rp 1.39 - 2.77 million 10.37% 19.41% 5.56% 3.59% 2.34% Rp 1.34 - 2.69 million 25.54% 17.52% 3.52% 2.60% 1.90%

Rp 2.97-4.24 million 30.90% 18.36% 5.60% 3.81% 2.48% Rp 2.93 - 4.19 million 34.51% 21.84% 6.10% 4.41% 2.16%

Rp 4.58-5.91 million 30.24% 9.95% 4.54% 2.88% 1.72% Rp 4.55- 5.87 million 21.69% 12.56% 4.38% 3.44% 1.30%

Rp 6.20-7.76 million 19.09% 4.66% 1.87% 1.96% 0.91% Rp 6.05 - 7.70 million 9.41% 5.45% 1.89% 1.34% 0.72%

> Rp 7.76 million 9.41% 1.39% 4.46% 1.83% 1.39% > Rp 7.70 million 8.86% 4.55% 1.56% 1.53% 1.24%

Total 100.00% 57.02% 19.39% 14.75% 8.84% Total 100.00% 61.91% 17.44% 13.32% 7.32%

Source: Consumer Survey (30 Cities), Bank Indonesia, December 2015 and June 2016, processed

Table 3.2 Composition of Savings based on Monthly Income

Semester II 2015

Saving Income Total 20%- 0-10% 10%-20% >30% Tidak bisa menabung 30%

Rp 1.39 - 2.77 million 10.37% 7.32% 7.03% 4.05% 4.16% 8.34%

Rp 2.97 - 4.24 million 30.90% 9.25% 7.29% 4.46% 3.68% 5.56%

Rp 4.58- 5.91 million 30.24% 5.83% 5.05% 3.27% 2.44% 2.50%

Rp 6.20 - 7.76 million 19.09% 3.38% 2.48% 1.48% 1.17% 0.90%

> Rp 7.76 million 9.41% 3.88% 2.05% 1.87% 1.34% 1.22%

Total 100.00% 29.67% 23.91% 15.13% 12.79% 18.51%

Semester I 2016

Saving Income Total 20%- 0-10% 10%-20% >30% Tidak bisa menabung 30%

Rp 1.34- 2.69 million 25.54% 5.10% 3.34% 3.26% 7.76% 5.96%

Rp 2.93 - 4.19 million 34.51% 7.63% 5.56% 4.55% 7.13% 9.65%

Rp 4.55- 5.87 million 21.69% 5.84% 3.71% 3.38% 3.19% 5.56%

Rp 6.05 - 7.70 million 9.41% 2.25% 1.66% 1.57% 1.36% 2.57%

> Rp 7.70 million 8.86% 1.98% 1.59% 1.31% 0.91% 3.08%

Total 100.00% 22.80% 15.96% 14.07% 20.34% 26.82%

Source: Consumer Survey (30 Cities), Bank Indonesia, December 2015 and June 2016, processed

4 Household deposits are calculated using individual deposits as a proxy.

76 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

of term deposits and demand deposits slipped into 3.1.4. Bank Credit to the Household Sector5 negative territory at -0.003% (yoy) and -9.07% (yoy) Growth of credit allocated to the household sector respectively, reversing the previous positive growth continued to track a slowing trend in line with the of 4.78% (yoy) and 3.50% (yoy) (Graph 3.8). Slower overall decline of credit growth in the banking term deposit growth was blamed on households industry. In the first semester of 2016, bank loans diverting some of their savings to consumption during extended to the household sector decelerated from the approach to Eid-ul-Fitr. Meanwhile, growth of 8.04% (yoy) to 7.92% (yoy).

Graph 3.7 Composition and Growth of Deposits

(Share, %) Household Non-Household (yoy) %

20 100% 13.97 13.06 12.65 90% 12.29 45.47 43.36 46.00 43.84 45.35 15 14.51 11.56 80% 13.63 11.31 12.61 70% 8.45 10 7.26 60% 6.35 7.18 50% 5.90 40% 54.53 56.64 54.00 56.16 54.65 5 4.40 30% - 20% Sem I Sem II Sem I Sem II Sem I 10% 2014 2015 2016 0% Sem-I 2014 Sem-II 2014 Sem-I 2015 Sem-II 2015 Sem-I 2016 Household Non-Household Total

Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed

Share (%) 100% 6.21 5.94 6.27 5.78 5.32 90% 80% 44.86 42.57 42.10 44.76 45.82 41.94 43.64 41.77 45.28 70% 41.24 60% 50% 40% 51.23 53.15 50.28 51.17 50.09 30% 52.55 51.48 48.97 52.27 52.92 20% 10% 3.91 4.74 3.90 5.19 4.63 0% Household Non- Household Non- Household Non- Household Non- Household Non- Household Household Household Household Household Sem-I 2014 Sem-II 2014 Sem-I 2015 Sem-II 2015 Sem-I 2016

Savings Term Deposits Demand Deposits Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed Note: Household deposits are a proxy of Individual Deposits demand deposits slowed due to a general reduction The share of household credit to total bank credit in the number of household demand deposits during increased, however, from 44.00% to 44.49% in the the reporting period in line with the industry-wide reporting period (Graph 3.9). Most loans to the decline as business conditions continued to fluctuate. household sector were utilised for consumption Consequently, the portion of household saving purposes (60.95%), followed by productive deposits increased from 52.27% to 52.92%, which purposes (27.66%) and investment (11.39%) (Table demands careful observation due to the potential 3.3). liquidity mismatch in the banking industry.

5 In this section, household sector credit is defined as personal loans for productive and consumptive purposes.

77 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 3.8 Composition and Growth of Household Deposits (Share, %) 30 100 6.79 6.43 6.21 5.49 6.27 5.78 5.32 90 25 80 38.46 38.62 41.24 42.57 44.76 41.94 41.77 20 70 60 15 15.82 50 10 40 30 54.75 54.95 52.55 51.48 48.97 52.27 52.92 7.18 5 20 (0.00) 10 0 0 Sem-I 13 Sem-II 13 Sem-I 14 Sem-II 14 Sem-I 15 Sem-II 15 Sem-I 16 Sem I Sem II Sem I Sem II Sem I Sem II Sem I -5 2013 2014 2015 2016 (9.07) -10 Savings Deposits Term Deposits Demand Deposits Savings Term Demand Total Deposits Deposits Deposits Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed

Graph 3.9 Composition of Bank Credit

100% 16.00%

55.06% 55.02% 55.12% 56.00% 55.51% 80% 12.00%

60% 7.92% 8.00% 40% 44.94% 44.98% 44.88% 44.00% 44.49% 4.00% 20%

0% 0.00% Sem I Sem II Sem I Sem II Sem I 2014 2015 2016

Individual Non-Individual Individual Growth (yoy) Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed

Table 3.3 Personal Loans by Type

Jun-15 Dec-15 Jun-16 Loan Credit Share NPL Credit Share NPL Credit Share NPL (Rp. T) (%) (%) (Rp. T) (%) (%) (Rp. T) (%) (%)

1. Working Capital 496.07 28.87 3.93 498.67 27.93 3.75 512.87 27.66 4.21

2. Investment 186.48 10.85 3.92 200.25 11.22 4.53 211.13 11.39 5.01

3. Consumption 1,035.66 60.28 1.69 1,086.46 60.85 1.51 1,130.30 60.95 1.68

TOTAL 1,718.21 100.00 2.58 1,785.38 100.00 2.47 1,854.24 100.00 2.76

Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed

Consumer loans disbursed to the household sector growth at 8.89% (yoy) in the same period due decelerated in the reporting period, from 9.11% to multipurpose loans and housing loans, which (yoy) to 10.03% (yoy), due to a deeper contraction posted growth of 14.35% (yoy) and 7.62% (yoy) of automotive loans, deteriorating from -2.12% respectively. (yoy) to -5.38% (yoy). Unstable domestic economic conditions, along with barely recovering household The NPL ratio for household consumer loans incomes, influenced the household decision to continued to follow the annual cycle in the first reduce consumption of durable goods such as semester, increasing from 1.55% in the second cars. Despite decelerating, consumer loans to the semester of 2015 to 1.75% in the reporting household sector still outpaced total bank credit period, which is unchanged from the year earlier

78 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 3.10 Household Credit Growth by Loan Type

(yoy) % 40 35

30 25

20

15 14.35 10 9.11 7.62 5 0

-5 (5.38) -10

-15 Jun-13 Jun-14 Jun-15 Jun-16 Sep-12 Sep-13 Sep-14 Sep-15 Dec-12 Dec-13 Dec-14 Dec-15 Mar-13 Mar-14 Mar-15 Mar-16 Housing Automotive Multipurpose Total Source: Commercial Bank Reports, Bank Indonesia, June 2016, processed at 1.75% (Graphs 3.11 and 3.12). Non-performing Household consumer loans were dominated in loans (NPL) mainly originated from housing loans, the first semester of 2016 by multipurpose loans, which increased from 2.34% to 2.67%. In addition, accounting for 42.21%, followed by housing loans the NPL of automotive loans also increased, from (40.22%) and automotive loans (12.46%). The 1.40% to 1.52%, and multipurpose loans from composition of household consumer loans changed 0.88% to 1.01%. Despite remaining well below the from the year earlier, when most consumer loans 5% threshold, the rising NPL trend on household were disbursed as housing loans (40.78%), followed consumer loans must be monitored against a by multipurpose loans (40.28%) and automotive backdrop of decelerating credit growth, especially loans (14.37%). the NPL of housing loans, which are the largest contributors to household consumer NPL.

Graph 3.11 Growth and NPL of Household Consumer Loans Graph 3.12 NPL of Household Loans by Type

Rp (Trilion) NPL % NPL (%) 1.000 2.00 944 3.0 2.67 2.5 800 1.60 1,75 2.0 600 1.20 1.75 1.5 1.52 400 0.80 1.0 1.01

200 0.40 0.5

0 - Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-12 Sep-13 Sep-14 Sep-15 Jun-13 Jun-14 Jun-15 Jun-16 Dec-12 Dec-13 Dec-14 Dec-15 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 Sep-13 Sep-14 Sep-15 Dec-13 Dec-14 Dec-15 Mar-13 Mar-14 Mar-15 Mar-16

Household Loans Household NPL (rhs) Housing Automotive Multipurpose Total

79 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 3.13 Composition of Household Consumer Loans

4.74%

4.33%

40.22% Housing 40.78% Automotive June Household Equipment 40.28% 2015 Multipurpose 42.21% Other Household Loans

0.25% 14.37 June 2016 0.37% 12.46%

Source: Commercial Bank Monthly Reports, Bank Indonesia, June 2016, processed

up prices. CPO prices increased as El Nino triggered 3.2. Corporate Sector Assessment drought that reduced supply. Consequently, higher commodity prices have not significantly improved the 3.2.1. Corporate Sector Exposure performance of commodity-oriented corporations In the first semester of 2016, corporate financial in Indonesia due to persistently limited demand for performance was influenced by developments in the export commodities. external and internal sectors. Externally, the prices of several leading commodities began to rebound Global economic moderation not only reduced despite ongoing global economic moderation. At export demand for commodities but also for other home, however, corporate financial performance goods. Deteriorating corporate performance due was boosted by national economic momentum in the to weaker demand was slightly offset by a modest second quarter of 2016. bump in domestic demand as the national economy gained momentum in the second quarter of 2016. The prices of several leading commodities began The impact of the gains was insignificant and limited, to show signs of recovery in the reporting period however, because increased domestic demand for but remained well below their peak (Graph 3.14). goods only emerged at the end of the first semester Furthermore, the prices of several export commodities and was influenced more by the seasonal increase in from Indonesia began to rebound, including crude consumption during the approach to Eid-ul-Fitr. oil, crude palm oil (CPO), rubber and minerals such as lead. Commodity prices rose on less supply rather Corporations engaged in the energy sector, especially than more demand. Crude oil prices increased as coal, also enjoyed performance gains due to increased production was reduced in the United States and domestic demand for coal to support the national several other producers. Meanwhile, the three largest 35GW national electricity program. Around 57% of rubber exporters, namely Thailand, Malaysia and the program shall be met through coal power but the Indonesia, agreed to curb production, which pushed impact on corporate performance has been limited by low project realisation.

80 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 3.14 Global Commodity Prices

USD USD USD/kg USD/metric ton 160 25 0.7 1400

140 6,82 $/mmbtu 0.6 1200 20 120 0.5 584,79 $/metric ton 1000 15 100 43,00 $/bbl 0.4 800

80 10 0.3 600 60 0.2 1,77 $/kg 400 41,02 $/short ton 5 40 0.1 200 20 0 0.0 0 Jul-07 Jul-08 Jul-09 Jul-10 Jul-11 Jul-12 Jul-13 Jul-14 Jul-15 Jul-16 Jul-07 Jul-08 Jul-09 Jul-10 Jul-11 Jul-12 Jul-13 Jul-14 Jul-15 Jul-16 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Oct-07 Oct-08 Oct-09 Oct-10 Oct-11 Oct-12 Oct-13 Oct-14 Oct-15 Oct-07 Oct-08 Oct-09 Oct-10 Oct-11 Oct-12 Oct-13 Oct-14 Oct-15 Apr-08 Apr-09 Apr-11 Apr-12 Apr-14 Apr-15 Apr-16 Apr-08 Apr-09 Apr-11 Apr-12 Apr-14 Apr-15 Apr-16 Aprl-07 Aprl-10 Aprl-13 Aprl-07 Aprl-10 Aprl-13

Coal Crude Oil Gas (rhs) Rubber Crude Palm Oil (rhs)

USD/metric ton USD/metric ton 12,000 35,000

10,000 30,000 25,000 8,000 20,000 6,000 15,000 4,000 10,000 2,000 5,000 0.0 0 Jul-07 Jul-08 Jul-09 Jul-10 Jul-11 Jul-12 Jul-13 Jul-14 Jul-15 Jul-16 Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Oct-07 Oct-08 Oct-09 Oct-10 Oct-11 Oct-12 Oct-13 Oct-14 Oct-15 Apr-08 Apr-09 Apr-11 Apr-12 Apr-14 Apr-15 Apr-16 Aprl-07 Aprl-10 Aprl-13

Copper Aluminium Lead

Source: Bloomberg, processed

3.2.2. Corporate Performance Business activity accelerated in nearly all economic Domestic economic momentum in the second quarter sectors during the second quarter of 2016, affecting the of 2016 had a favourable impact on business activity. trade, hotels and restaurants (THR) sector in general The Business Survey conducted by Bank Indonesia and the wholesale and retail subsector specifically, showed that business activity increased in the second as domestic demand increased. Nonetheless, quarter of 2016 compared to the end of 2015. Increased business activity was predicted to decrease again in business activity was evidenced by a corresponding the subsequent period, with a weighted net balance weighted net balance (WNB) of 18.40%, up from 3.02% (WNB) of 17.70%. The slowdown was predicted to at the end of 2015 (Graph 3.15).

GrafikGraph 3.153.16. ActualPerkembangan and Projected Realisasi Corporate dan Perkiraan Activity Dunia Usaha Graph 3.16 Production Capacity Utilisation %qtq %SBT % 5.0 25.0 90 4.0 3.75 85 82.56 18.40 20.0 3.0 80 77.12 78.03 2.0 17.70 15.0 75 1.0 11.90 -0,34 70 70.33 0.0 10.0 -1.0 65 5.80 5.0 -2.0 60 75.75 77.01 0.0 -3.0 TW I TW II TW III TW IV TW I TW II TW III TW IV TW I TW II TW III TW IV TW I TW II I II III IV I II III IV I II III IV I II III* 2013 2014 2015 2016 2013 2014 2015 2016 *) Perkiraan Total Mining and Agriculture, Livestock, Quarrying Forestry and Fisheries WNB per the Business GDP Growth (lhs) Survey (rhs) Utilities Manufacturing Industry

Source: Business Survey, Bank Indonesia, Semester II 2016 Source: Business Survey, Bank Indonesia, Semester I – 2016

81 FINANCIAL STABILITY REVIEW No. 27, September 2016

hit the agricultural, plantation, livestock, forestry and of 2016. Declining productivity fed through to lower fisheries sector hardest, with a weighted net balance corporate profitability in general. Indicators of (WNB) of 1.48%. corporate profitability, namely the return on assets (ROA) and return on equity (ROE), also declined on the Congruent with increased business activity, average year earlier, from 4.83% and 10.42% in second quarter production capacity utilisation was also observed to of 2015 to 4.75% and 10.05% in the second semester rise from 75.23% in the fourth quarter of 2015 and of 2016 but improved on the 4.22% and 8.97% posted from 75.75% in the first quarter of 2016 to 77.01% in the fourth quarter of 2015. The moderate increases in the second quarter of 2016. The highest level of of ROA and ROE stemmed from a bump in net income production capacity utilisation was found in the utilities after the corporate sector implemented measures to sector, averaging 82.56% in the reporting period. boost efficiency by holding any further expansion of debt, amongst others, as reflected by a lower portion Although production increased, the value of inventory of debt in the second quarter of 2016 compared to the remained large. Large inventories were maintained same period of the previous year. Furthermore, the due to weak sales performance last year as well as declines affected all sectors. As an aggregate, the debt- limited domestic and export demand as consumption to-equity ratio (DER) dropped from 1.16 in the second only picked up at the end of the first semester. quarter of 2015 to 1.08 in the second quarter of 2016. Furthermore, the global economy remained sluggish, Less debt prompted an increase in corporate solvency which generally undermined corporate performance (TA/TL) and liquidity (current ratio), climbing from 1.86 in Indonesia. Corporate indicators of productivity, and 1.41 respectively in the second quarter of 2015 to profitability, solvency, liquidity and the debt-to-equity 1.93 and 1.45 in the second quarter of 2016. ratio (DER) all tended to decline. In general, the performance of commodity-oriented Asset turnover and inventory turnover decreased, companies, including coal, crude palm oil (CPO), indicating lower corporate productivity. rubber, oil and gas as well as metals, deteriorated. Notwithstanding, the consumer goods industry, Although corporate productivity has improved on miscellaneous industries as well as the infrastructure, rising commodity prices, low demand for exports utilities and transportation sector all posted slight undermined the impact of productivity gains on productivity gains in line with ongoing energy corporate profitability. Accordingly, corporate ROA and infrastructure project implementation by the and ROE declined in the second quarter of 2016 government coupled with stronger household demand compared to one year earlier, except in the coal for consumer goods during the approach to Eid-ul-Fitr. subsector as government electricity projects buoyed domestic demand. The corporate sector responded Compared to the second semester of 2015, asset to low profitability by reducing debt, thereby raising turnover decreased from 0.77 to 0.71 and inventory the liquidity and solvency indicators, except for the oil turnover fell from 6.42 to 6.19 in the second quarter and gas sector, which demands further monitoring. Oil

82 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

and gas sector exposure increased, evidenced by weak was accompanied by an increase in the share of solvency and liquidity indicators and rising debt (Table corporations with DSR>100% and negative DSR from 3.5). Increasing debt, shown by the DER value, requires 50% to 60.11%. In addition, corporate capacity to monitoring against a backdrop of lower profitability repay interest also declined, indicated by a drop in the due to the impact on corporate repayment capacity. interest coverage ratio (ICR) from 3.04 in the fourth quarter of 2014 to 2.38 in the fourth quarter of 2015 in Corporate repayment capacity has declined over the line with an increase in the share of corporations with past few years. Based on the latest data available, an ICR value < 1.5, which is indicative of rising debt at the debt service ratio (DSR) increased from 71.72% risk6. (median) in 2014 to 75.30% (median) in 2015, which

Graph 3.17 Key Indicators of Corporate Financial Performance

Current Ratio 0.00

2.00

4.00

Inventory 6.00 ROA Turnover 8.00

10.00

2015Q2 2015Q4 2016Q2

TA/TL ROE

Source: IDX Corporate Financial Statements, Bloomberg, processed Note: Small ratios, represented by larger Graphs, indicate worse performance.

Table 3.4 Corporate Financial Performance Indicators by Sector

ROA (%) ROE (%) DER Current Ratio TA/TL Asset TO Inventory TO No, Sector 2015 2016 2015 2016 2015 2016 2015 2016 2015 2016 2015 2016 2015 2016

1 Agriculture 2.61% 1.49% 5.62% 3.28% 1.22 1.19 0.86 0.95 1.82 1.84 0.65 0.52 8.26 7.29

Basic Industries and 2 4.74% 5.86% 10.01% 11.63% 1.10 0.99 1.60 1.58 1.91 2.01 0.79 0.75 5.33 5.16 Chemicals

3 Consumer goods 11.31% 11.87% 23.47% 22.59% 1.04 0.79 1.66 1.85 1.96 2.27 1.30 1.30 4.54 4.77

infrastructure, Utilities 4 2.99% 4.57% 7.64% 11.41% 1.57 1.43 1.04 0.98 1.64 1.70 0.54 0.53 65.24 74.22 and Transportation

5 Miscellaneous Industries 4.95% 4.13% 11.08% 9.15% 1.24 1.19 1.22 1.23 1.80 1.84 0.83 0.75 7.76 7.82

6 Mining 1.37% 0.32% 2.62% 0.60% 0.89 0.83 1.47 1.81 2.12 2.21 0.56 0.46 12.60 12.37

7 Property and Real Estate 6.74 4.77% 14.27% 10.09% 1.11 1.12 1.82 1.72 1.90 1.89 0.40 0.36 2.16 1.97

Trade, Services and 8 4.17% 3.71% 8.23% 7.39% 0.99 0.99 1.53 1.61 2.01 2.01 1.05 0.99 7.23 6.89 Investment

Aggregate 4.83 4.75% 10.42% 10.05% 1.16 1.08 1.41 1.45 1.86 1.93 0.77 0.71 6.42 6.19

Source: IDX Corporate Financial Statements, Bloomberg, processed Note: Position per Q2/2015 and Q2/2016 (observation sample of 328 non-financial corporations)

6 Debt at risk: Total corporate debt with an ICR value < 1.5/total corporate debt.

83 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 3.18 Financial Performance of Publicly Listed Non-Financial Corporations

12% ROA (%) ROE (rhs) 25% 1.8 DER Current Ratio TA/TL (skala kanan) 2.2

10% 1.6 2.1 20% 8% 1.4 2.0 6% 15% 1.2 1.9 4% 10% 1.0 1.8 2%

0% 5% 0.8 1.7 Jun-12 Jun-15 Jun-10 Jun-13 Jun-16 Jun-12 Jun-15 Jun-10 Jun-13 Jun-16 Jun-10 Jun-13 Jun-16 Sep-11 Sep-14 Sep-12 Sep-15 Sep-11 Sep-14 Sep-12 Sep-15 Sep-12 Sep-15 Dec-10 Dec-13 Dec-11 Dec-14 Dec-10 Dec-13 Dec-11 Dec-14 Dec-11 Dec-14 Mar-10 Mar-13 Mar-16 Mar-11 Mar-14 Mar-10 Mar-13 Mar-16 Mar-11 Mar-14 Mar-11 Mar-14

1.0 Asset Turnover Inventory Turnover 8.5 (skala kanan) 1.0 8.0 0.9 0.9 7.5 0.8 7.0 0.8 6.5 0.7

0.7 6.0 0.6 5.5 0.6 0.5 5.0 Jun-12 Jun-15 Jun-10 Jun-13 Jun-16 Sep-11 Sep-14 Sep-12 Sep-15 Dec-10 Dec-13 Dec-11 Dec-14 Mar-10 Mar-13 Mar-16 Mar-11 Mar-14

Source: IDX Corporate Financial Statements, Bloomberg, processed Note: Position per Q2/2015 and Q2/2016 (observation sample of 328 non-financial corporations)

Table 3.5 Corporate Financial Performance Indicators by Major Export Commodity Sector

ROA (%) ROE (%) DER TA/TL Current Ratio Asset Turnover Inventory TO Sector 2015 2016 2015 2016 2015 2016 2015 2016 2015 2016 2015 2016 2015 2016

Coal 1.51% 1.79% 2.93% 3.45% 0.92 0.90 2.09 2.12 1.43 2.05 0.65 0.59 16.13 18.24

Crude Palm Oil 2.97% 1.91% 6.29% 4.14% 1.19 1.15 1.84 1.87 0.81 0.90 0.62 0.49 8.81 7.76

Rubber 0.94% 0.62% 1.94% 1.31% 1.11 1.11 1.90 1.90 0.60 0.58 0.38 0.34 7.38 7.42

Oil and Gas -1.60% -6.36% -4.42% -19.60% 1.97 2.46 1.51 1.41 1.03 0.95 0.29 0.26 14.60 15.07

Metals -0.87% -1.33% -1.68% -2.18% 0.99 0.57 2.01 2.74 1.13 1.29 0.67 0.45 4.26 5.37

Source: IDX Corporate Financial Statements, Bloomberg, processed Note: Position per Q2/2015 and Q2/2016 (observation sample of 73 non-financial corporations)

Graph 3.19 Corporate Financial Performance Indicators by Major Export Commodity 30% ROA 2.5 Current Ratio 25% 2.0 20%

15% 1.5 10% 1.0 5%

0% 0.5 -5%

-10% 0.0

I II III IV I II III IV I II III IV I II III IV I II I II III IV I II III IV I II III IV I II III IV I II 2012 2013 2014 2015 2016 2012 2013 2014 2015 2016

7 The Altman Z-Score is a quantitative method to measure corporate soundness and the probability of bankruptcy. An Altman Z-Score of > 2.99 is the safe zone; 1.81 < Z < 2.99 is the grey, or moderate, zone and Z < 1.81 is the distress zone. The Altman Z-Score was calculated using data from 226 publicly listed non-financial corporations representing all economic sectors.

84 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

2,5 DER 35 Inventory Turnover 30 2,5 25 2,0 20 1,5 15 1,0 10 0,5 5

0,0 0

I II III IV I II III IV I II III IV I II III IV I II I II III IV I II III IV I II III IV I II III IV I II 2012 2013 2014 2015 2016 2012 2013 2014 2015 2016

Batu bara Kelapa Sawit Logam Karet Minyak dan Gas

Source: IDX Corporate Financial Statements, Bloomberg, processed

Potential risk of default increased in the corporate 3.2.3. Bank Exposure to the Corporate Sector sector compared to the same period one year earlier. Worsening corporate performance must be monitored The decline was reflected in the Altman Z-Score because bank credit exposure to the corporate sector using data from 226 publicly listed non-financial remained dominant despite growth slowing. In the first corporations covering all economic sectors.7 The semester of 2016, the portion of bank credit disbursed calculations showed that the share of corporations in to the corporate sector increased from 46.99% the distress zone increased in the second quarter of one year ago to 48.39%. BUKU 4 banks dominated 2016 compared to the same period one year earlier, corporate credit, accounting for 43.85%, followed by from 36.81% to 42.04%. In addition, the upward trend BUKU 3 banks with 38.95%. Such conditions reflect the of corporations in the distress zone has persisted since business orientation of BUKU 4 and 3 banks, namely early 2013 but remains comparatively low compared targeting corporate customers, while BUKU 2 and 1 to the crisis period of 2008-2009. Plotting the Altman banks focus more on retail credit (Graph 3.23). Z-Score against GDP growth revealed that economic moderation, domestic and global, has a strong effect on corporate financial performance.

Graph 3.20 Corporate Repayment Capacity

% % % % 60.11 100 65 8.0 40.31 39.10 45 50.00 90 7.0 40 47.91 55 33.60 80 46.26 47.59 33.03 43.55 6.0 30.31 35 70 45 27.30 27.44 27.71 32.45 30 60 5.0 35 29.51 25 4.0 50 26.82 26.62 25 20 40 3.0 15 30 15 2.0 20 10 5 1.0 10 5 50.69 54.80 47.82 61.25 71.72 75.30 3.84 3.93 4.32 3.64 3.04 2.38 0 -5 0.0 0 2010 2011 2012 2013 2014 2015 2010 2011 2012 2013 2014 2015 *Posisi TW III *Posisi TW III DSR % of Corporations with DSR > 100 and ICR % of Corporations % of Debt at (Median) Negative DSR (rhs) (Median) with ICR < 1.5 (rhs) Risk (rhs)

Source: IDX Corporate Financial Statements, Bloomberg, processed Note: Position per Q4 from 2010-2015 (observation sample of 399 corporations)

85 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 3.21 Corporate Performance based on the Altman Graph 3.22 Distressed Corporate Performance against GDP Z-Score GDP % (yoy) Share % Share (%) 55 45 7.0 42.04 50 6.5 45 44.17 42.04 40 40 39.33 6.0 35 39.82 35 5.5 30 30 25 5.18 5.0 20 25 4.5 15 18.14

10 20 4.0 Jun-08 Jun-09 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-08 Sep-09 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-07 Dec-08 Dec-09 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Jul-11 Jul-12 Jul-13 Jul-15 Mar-08 Mar-09 Mar-10 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 Jun-16 Mar-11 Nov-11 Mar-12 Nov-12 Mar-13 Nov-13 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16

Safe Zone Distress Zone Grey Zone GDP (rhs) Share of Distressed Corporations Source: Bloomberg, CEIC, June 2016, processed Source: Bloomberg, CEIC, June 2016, processed

Bank lending to the corporate sector grow slower in total. Meanwhile, lending to the mining sector has the first semester of 2016, decelerating from 12.98% experienced negative growth since last year, with the (yoy) to 12.13% (yoy). The slowdown primarily affected contraction deepening in the reporting period due to the manufacturing industry and mining sector (Table heightened credit risk. Despite decelerating, corporate 3.6). Slower credit growth in the manufacturing credit growth still outpaced total credit growth in the sector was a strong drag on overall corporate credit same period at just 8.89%. growth because the sector accounts for 32.48% of the

Graph 3.23 Corporate Credit by BUKU Bank Group Share, % (%) 100 35.00 90 30.00 80 70 25.00 60 20.00 50 12.13 15.00 40 30 10.00 20 3.56 5.00 10 0 - Jun Jun Jun Jun Jun Jun Sep Sep Sep Sep Sep Dec Dec Dec Dec Dec Mar Mar Mar Mar Mar Mar 2011 2012 2013 2014 2015 2016 Credit Growth (yoy, rhs) BUKU 1 BUKU 2 BUKU 3 BUKU 4 NPL Gross (rhs)

Source: Commercial Bank Reports, June 2016, processed

Table 3.6 Corporate Credit by Economic Sector

Jun-15 Dec-15 Jun-16

Outstand- Credit Gross Outstand- Credit Gross Outstand- Credit Gross No Economic Sector Share Share Share ing Credit Growth NPL ing Credit Growth NPL ing Credit Growth NPL (%) (%) (%) (Rp T) (%) (%) (Rp T) (%) (%) (Rp T) (%) (%)

1 Manufacturing 598,54 33.28 9.46 2.23 652,68 33.69 15.11 2.39 655,16 32.48 9.46 3.78 2 Trade, Hotels and Restaurants 380,06 21.13 13.14 3.15 411,90 21.26 16.29 2.95 430,01 21.32 13.14 3.61 3 Corporate Services 152,75 8.49 24.52 2.00 173,53 8.96 14.21 2.01 190,20 9.43 24.52 2.15 4 Agriculture 145,39 8.08 23.68 1.11 157,89 8.15 14.76 1.30 179,82 8.92 23.68 1.01 5 Transportation, Warehousing and Communications 149,25 8.30 1.31 3.19 152,13 7.85 2.52 3.65 151,21 7.50 1.31 5.61 6 Construction 130,06 7.32 21.17 5.51 136,55 7.05 18.76 4.14 157,59 7.81 21.17 4.63 7 Mining 129,13 7.18 (14.92) 2.80 122,95 6.35 (5.88) 3.73 109,85 5.45 (14.92) 6.13 8 Utilities 82,07 4.56 27.78 1.67 92,79 4.79 22.54 2.38 104,87 5.20 27.78 1.73 9 Social/Public Services 23,83 1.32 32.86 4.16 29,04 1.50 2.25 3.40 31,66 1.57 32.86 3.17 10 Others 7,61 0.42 (14.28) 2.51 7,64 0.39 (22.92) 2.29 6,52 0.32 (14.28) 4.99 Total 1.798,68 100.00 12.20 2.67 1.937,09 100.00 13.33 2.71 2.016,89 100.00 12.20 3.56

Source: Commercial Bank Reports, June 2016, processed

86 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 3.7 Credit to Major Export Commodities

Outstanding Share of Total Credit (%) Annual Growth (%) Gross NPL Ratio (%) Credit as of No. Commodity June 2016 Jun’15 Des’15 Jun’16 Jun’15 Des’15 Jun’16 Jun’15 Des’15 Jun’16 (Rp T)

1. Crude Palm Oil 243,33 5.26 5.84 5.84 14.71 24.61 20.82 1.25 1.11 1.10

2. Oil and Gas 93,97 2.63 2.64 2.25 23.56 1.59 (6.71) 3.72 4.63 5.93

3. Metals 91,82 2.18 2.19 2.20 20.21 12.01 10.14 1.39 1.42 2.38

4. Coal 41,61 1.31 1.14 1.00 13.86 0.66 (17.88) 8.79 6.51 8.31

5. Rubber 19,01 0.51 0.45 0.46 (2.04) (5.43) (2.10) 6.02 4.51 4.24

Total 489,73 11.89 12.25 11.75 16.59 13.00 7.60 2.86 2.55 3.00

Source: Commercial Bank Reports, June 2016, processed

The large share of corporate credit, coupled with coal as well as oil and gas, has already exceeded the robust growth above the industry average, was also threshold. Non-performing loans (NPL) in the coal accompanied by heightened credit risk. The gross NPL subsector were recorded at Rp4.41 trillion in June 2015, ratio of the corporate sector increased from 2.71% in subsequently declining to Rp3.02 trillion in December the second semester of 2015 to 3.56% in the reporting 2015 but then climbing back to Rp3.46 trillion in June period. Credit risk increased in all sectors, except the 2016. Deteriorating NPL performance was blamed on agricultural sector. The highest NPL ratio affected the medium and smaller-scale firms that were not affected mining sector, which increased significantly from 3.73% by the government’s electricity infrastructure projects. to 6.13%. Furthermore, mining industry performance The upward NPL trend forced the banks to become is not expected to improve in 2016 due to the sluggish more selective when lending to the commodity sector global economic recovery that has undermined global to avoid exacerbating NPL, while simultaneously demand for mining products. controlling existing bad debt.

Bank credit risk associated with corporations engaged Corporate deposit growth decelerated in the first half in the five major commodities also increased in line of 2016, from 11.44% to 9.95%, due to corporations with weak corporate performance in the sector. The withdrawing funds to pay off and/or repay offshore level of NPL linked to several commodities, particularly debt.

Graph 3.24 Corporate Deposits DPK Korporasi (Rp T) yoy %

35 1,600 1,201 1,400 30 1,200 25 1,000 20 800 15 600 10 400 9.95 200 5 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-15 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-15

Corporate Deposits Growth (rhs)

Source: Commercial Bank Reports, June 2016, processed

87 FINANCIAL STABILITY REVIEW No. 27, September 2016

In the first semester of 2016, BUKU 4 and 3 banks which would ultimately dissuade the corporate sector remained the preferred choice for corporations to from expanding external debt. place funds, accounting respectively for 43.09% and 42.35% of total corporate deposits. The advantages of In contrast, public external debt has followed a large banks include administrative and transactional consistent upward trend since December 2014 in line convenience as well as better security (Graph 3.25). with government efforts to reduce the budget deficit (2.5% of GDP) due to increased capital spending in 3.2.4. Private External Debt the 2016 budget. From 2004-2012, the government The private sector continued to dominate external and monetary authority dominated external debt in debt in Indonesia, accounting for 52% of the total, or Indonesia. Since 2013, however, private external debt USD319 billion. Nonetheless, private sector external has exceeded public external debt. Consequently, in debt has decelerated since December 2014, particularly the first semester of 2016, external debt growth was the financial sector, because of economic moderation recorded at 6.17% (yoy), down from 6.60% (yoy) one (especially the mining sector) and rupiah fluctuations. year earlier and 6.31% (yoy) in the second semester of Exchange rate instability could potentially increase 2015. currency risk exposure for prospective borrowers,

Graph 3.25 Corporate Deposits by BUKU Bank Group 100% 90% 43.09% 80% 70% 60% 50% 40% 42.35% 30% 20% 12.68% 10% 0% 1.88% Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Mar-10 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16

BUKU 1 BUKU 2 BUKU 3 BUKU 4

Source: Commercial Bank Reports, June 2016, processed

Graph 3.26 External Debt Structure in Indonesia

USD Billion yoy (%) Share (%) 180 20.0% 100% 165 159 160 90% 143 15.0% 140 80% 124 41% 70% 41% 40% 43% 43% 44% 43% 120 10.0% 47% 50% 51% 54% 54% 100 6.17% 60% 56% 83 50% 80 5.0% 59% 58 40% 59% 60% 57% 57% 56% 57% 60 0.0% 53% 50% 49% 30% 46% 44% 46% 40 -5.0% 20% 20 10% - -10.0% 0% 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 (Jun) (Jun) Private Government and Monetary Authority Private Government and Monetary Authority Total External Debt Growth (%, yoy) (rhs)

Source: External Debt Statistics of Indonesia, June 2016

88 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Although private external debt remained dominant, Grouping external debt by the aims of restructuring growth was noted to decelerate. Private external debt helps differentiate restructuring due to dwindling totalled USD165 billion in the first semester of 2016, corporate performance (for instance: repayment with growth decelerating from positive 10.31% (yoy) difficulties, a deteriorating business outlook, in the first semester of 2016 and 2.43% (yoy) in the inadequate liquidity) from restructuring due to better second semester of 2015 to negative 3.10%. Non- performance and other business factors (for example: financial corporations, banks and the nonbank financial a favourable business outlook so the ceiling is raised, industry contributed to the slowdown. The biggest interest rate negotiations, or corporate infrastructure decline affected the financial sector, namely banks and development). Negative tone restructuring indicates the nonbank financial industry, which reported growth worsening corporate performance that could of -5.06% (yoy) and -10.04% (yoy) respectively in the undermine repayment capacity to the domestic reporting period due to weak demand for new loans. banking industry. In comparison, the external debt of non-financial corporations contracted by -1.92% (yoy) due to sluggish In line with weaker corporate financial performance, performance. the restructured debt of non-financial corporations

Graph 3.27 Private External Debt Structure and Growth

Growth, USD Billion USD Billion 100.00% 100 350 yoy (%) 324 80.00% 300 60.00% 80 250 40.00% 60 200 20.00% -3.10% -3.10% 124 150 0.00 40 -5.06% 30 100 -20.00% -10.40% 20 -40.00% 50 11 -60.00% - - Dec-04 Dec-06 Dec-08 Dec-10 Dec-12 Dec-14 Jun-16 Jun-16 Dec-04 Dec-05 Dec-06 Dec-07 Dec-08 Dec-09 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Nonbank Financial Institutions Total Private External Debt (rhs) Nonbank Financial Institutions Total Private External Debt Bank Corporations (rhs) Bank Corporations

Source: External Debt Statistics of Indonesia, June 2016

The large share of corporate external debt, despite has increased since January 2015, peaking at USD35.19 growth decelerating, combined with the amount billion in May 2016. Most restructured external debt of restructured corporate external debt required of non-financial corporations is classified as negative increased monitoring. Restructured external debt tone. A total of 730 corporations applied negative tone can be categorised into positive tone and negative restructuring worth USD29.9 billion in the reporting tone. Positive tone involves (i) raising the ceiling; (ii) period. Restructuring is the rational choice to improve refinancing; (iii) rollover; and (iv) diversifying creditors. the efficacy of principal and interest payments in line Meanwhile, negative tone restructuring includes: (i) with domestic and global economic moderation. reconditioning; (ii) interest decapitalisation; (iii) debt to equity swaps; (iv) debt reduction; (v) rescheduling; The manufacturing industry has the highest level of and (vi) other restructuring8. restructured debt, reaching USD14.3 billion in May

8 The tone of external debt restructuring is determined by Focus Group Discussions (FGD) with the corporation affected by the debt restructuring.

89 FINANCIAL STABILITY REVIEW No. 27, September 2016

2016. The manufacturing industry in Indonesia is of a currency mismatch, which increases exposure to considered risky because of importing raw materials currency risk. Negative tone restructuring has increased in USD, while selling on the domestic market in since the middle of 2015, even outpacing positive tone rupiah. Consequently, the corporate sector is at risk restructuring.

Graph 3.28 Restructured Non-Financial Corporate External Debt

(USD Bilt) 40,0 36,19 35,0 30,0 27,15 25,0 20,0 15,0 10,0 5,0 0,0 Jul-15 Dec15 Jan-15 Jan-16 Jun-15 Oct-15 Feb-15 Feb-16 Apr-15 Apr-16 Sep-15 Mar-15 Nov-15 Mar-16 Aug-15 May-15 May-16 Source: External Debt Statistics of Indonesia, May 2016, processed

Table 3.8 Restructured External Debt by Economic Sector in May 2016

ULN May’16, (USD Jt) *) Restructured No. Commodity Total Non- External Restructured Positive Negative Total Restructured Tone Tone Debt Debt 1. Manufacturing Industry 14,845 1,949 12,351 14,300 29,145 2. Mining and Quarrying 16,443 521 4,023 4,543 20,987 3. Utilities 15,854 218 3,638 3,856 19,710 4. Transportation and Communications 7,433 2,235 2,007 4,242 11,676 5. Trade, Hotels and Restaurants 6,1 93 680 2,551 3,231 9,424 6. Financial, Leasing and Corporate Services 5,694 203 1,917 2,120 7,814 7. Agriculture, Livestock, Forestry and Fisheries 4,297 498 2,451 2,949 7,246 8. Other Sectors 1,360 30 318 349 1,709 9. Construction 884 18 299 317 1,201 10. Services 822 273 12 285 1,107 Total 73,825 6,626 29,567 36,193 110,018

Source: External Debt Statistics of Indonesia, May 2016

Graph 3.29 Outstanding Restructured External Debt (USD, Graph 3.30 Share of Outstanding Restructured External Debt to billions) Total Restructured External Debt (%)

(USD Bil) 40,0 May-16 17% 83% Apr-16 35,0 Mar-16 Negative Tone 29,92 Feb-16 30,0 Negative Tone Jan-16 Dec15 Nov-15 25,0 21,93 Oct-15 Sep-15 20,0 Aug-15 Jul-15 15,0 Jun-15 May-15 10,0 Apr-15 5,22 Positive Tone 6,27 Positive Tone Mar-15 5,0 Feb-15 0,0 Jan-15 19% 81% 0% 20% 40% 60% 80% 100% Jul-15 Dec15 Jan-15 Jan-16 Jun-15 Oct-15 Feb-15 Feb-16 Apr-15 Apr-16 Sep-15 Mar-15 Nov-15 Mar-16 Aug-15 May-15 May-16 Source: External Debt Statistics of Indonesia, May 2016 Source: External Debt Statistics of Indonesia, May 2016

90 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Based on total outstanding external debt, negative tone debt increased from USD1.13 million to USD2.28 tone restructuring was dominated by reconditioning, million over the same period. In addition, principal accounting for 588 facilities (May 2016), while most payments on negative and positive tone debts tended positive tone restructuring involved increasing the to increase. ceiling, amounting to 125 facilities (May 2016). Reconditioning is achieved by changing the terms and Corporations with restructured external debt plan conditions of the external debt, through adjustments to repay the debt before maturity but this requires to the total of the debt, interest rate or creditor. In intensive monitoring, especially of negative tone debt a number of cases, reconditioning has been applied if considering the outstanding continues to rise. new loans with more attractive terms and conditions are offered, for example with a lower interest rate or Most domestic banks extend loans to corporations longer maturity period. Meanwhile, the debt ceiling is with negative tone external debt. Therefore, a decline raised for positive tone restructuring through creditor in repayment capacity would also impact repayments confidence in the business outlook and repayment of domestic debt. Stress tests were conducted capacity. to measure banking resilience to declines in the repayment capacity of corporations with negative In general, principal and interest payments on tone restructured external debt. The simulations used restructured external debt increased in May 2016 scenarios of 20%, 30% and 50% default. The stress compared to one year earlier. Interest payments on tests showed that only with a 50% default would the negative tone restructured debt decreased from level of NPL exceed the 5% threshold but bank capital USD34.94 million in May 2015 to USD30.65 million in would still not be impacted significantly. May 2016. In contrast, interest payments on positive

Table 3.9 Positive and Negative Tone External Debt Restructuring

External Debt Total Tone Restructuring Position in May 2016 Facilities (USD, millions) Reconditioning 14,564 588 Rescheduling 7,335 1,105 Negative Interest Decapitalisation 3,953 49 Tone Others 3,220 208 Debt Reduction 260 10 Debt to Equity Swap 234 16 Raised Ceiling 2,888 28 Positive Creditor Diversification 2,585 125 Tone Rollover 718 68 Refinancing 435 16 Total 36,193 2,213

91 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 3.31 Principal and Interest Payments on Positive and Negative Tone Restructured External Debt

Interest Payments Interest Payments Principal Payments Principal Payments (USD, million) (USD, million) (USD, million) (USD, million) 250,0 60,0 3.000,0 250,0

50,0 2.500,0 200,0 200,0

40,0 2.000,0 1.903,3 Tone 150,0 150,0 1.500,0 Positif Tone 30,0 (rhs) Negatif 102,5 100,0 100,0 30,65 20,0 1.000,0 50,0 50,0 10,0 500,0 2,28 0,0 0,0 0,0 0,0 Jul-14 Jul-15 Jul-14 Jul-15 Jan-14 Jan-15 Jan-16 Jan-14 Jan-15 Jan-16 Sep-14 Sep-15 Sep-14 Sep-15 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16 May-14 May-15 May-16 May-14 May-15 May-16 Positive Tone (rhs) Negative Tone Positive Tone (rhs) Negative Tone

Source: External Debt Statistics of Indonesia, May 2016 Graph 3.32 Planned Interest and Principal Payments on Positive and Negative Tone Restructured External Debt

(USD Million) Negative Tone (USD Million) Positive Tone 3,000 250

2,500 200

2,000 150 1,500 100 1,000

500 50

0 0 Jul-16 Sep-16 Nov-16 Jan-17 Mar-17 May-17 Jul-16 Sep-16 Nov-16 Jan-17 Mar-17 May-17

Mature External Debt Planned Payments Mature External Debt Planned Payments

Source: External Debt Statistics of Indonesia, May 2016

92 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Regional Financial Surveillance (RFS) Implementation Box 3.1 Framework at Domestic Bank Indonesia Representative Offices

Pursuant to Bank Indonesia Regulation (PBI) No. mandates strengthening the main function, namely 16/11/PBI/2014, dated 1st July 2014, concerning financial system stability, through monitoring Macroprudential Regulation and Supervision, one financial imbalances and systemic risks, proactively objective of macroprudential policy regulation and mitigating risks and financial imbalances as supervision is to prevent and mitigate systemic well as deepening and enhancing the quality risk. According to the regulation, systemic risk is of financial intermediation and cooperation, defined as potential instability as a consequence including strengthening Domestic Bank Indonesia of contagion in part or all of the financial system Representative Offices (KPwDN). due to interactions of size, business complexity and interconnectedness between financial institutions One effort to enhance KPwDN is through and/or financial markets. Regional Financial Surveillance. RFS involves a series of activities, including off-site surveillance/ As financial system players become increasingly assessments and on-site inspections against the interconnected, shocks in one sector are easily various risks that affect regional financial stability transmitted to other sectors, nationally and locally. in order to maintain financial system stability Consequently, the role of regional institutions must and support inclusive and sustainable regional be expanded in the face of increasingly complex economic development. risks, thus such institutions will play a growing role in maintaining financial system stability. Therefore, The goal of RFS is to monitor risks and imbalances Bank Indonesia formulated the Bank Indonesia in local areas in order to maintain regional financial Strategic Function Architecture (AFSBI) 2004 that stability and support inclusive and balanced

Box Figure 3.1.1 Regional Financial Surveillance Implementation Framework

Target Maintain financial system stability and support inclusive and sustainable regional economic development

Promote a Balanced Prevent and Mitigate and Quality Financial Systemic Risk Intermediation Institutions Function

Strategy Regional Financial Surveillance

Principals Research-Based* Future-Oriented Well Managed * : Regional Department P : Guidelines Main PP : Surveillance guidelines according Research Activities Coordination Surveillance Macroprudential and Studies, to financial system surveillance with Internal (including RBS Surveillance including and External department mandate and RFA) (as required) financial system Stakeholders stability GP : Guiding Principles RBS : (Regional Balance Sheet), RFA P PP GP GP (Regional Financial Account)

Source: Bank Indonesia

93 FINANCIAL STABILITY REVIEW No. 27, September 2016

regional economic development. RFS is achieved Household surveillance includes consumer and by collating regional data, while monitoring and investor behaviour at the lowest level. In addition, mitigating potential systemic risk. Box Figure 3.1.1 regional surveillance also encompasses analysis presents the RFS implementation framework at of the Regional Balance Sheet and Regional domestic Bank Indonesia representative offices Financial Account. The business processes of RFS (KPwDN). implementation are presented in Box Figure 3.1.2.

The main RFS activities consist of regional 2. Macroprudential Inspections assessments/surveillance, macroprudential If required, macroprudential inspections shall be surveillance, thematic research and reviews as carried out by the Financial System Surveillance well as coordination with internal and external Department (DSSK) in pursuance of the mandate stakeholders as follows: given in coordination with the Bank Indonesia representative office. In addition, aBank 1. Regional Financial Assessments/Surveillance Indonesia representative office could also initiate The objects of surveillance include banks, nonbank macroprudential surveillance based on the results financial institutions, non-financial corporations of the assessment. The inspections are coordinated and households. Bank surveillance incorporates the with the Financial System Surveillance Department. parent company, affiliates and subsidiaries deemed to have a significant risk exposure or systemic 3. FSS Thematic Reviews and Research impact. Corporate surveillance covers companies Conduct thematic reviews and research in line with with strong ties to the financial sector. the direction of the Annual Work Meeting, Strategic Programs and Board of Governors.

Box Figure 3.1.2 Business Processes of RFS Implementation

Identification Identifying Risk Coordination and and Pressures Assessments Communication Observation

Thematic Inspections*

Data, Information and Research

Notes: The black dotted box represents elements of the RFS framework *possible role of Bank Indonesia representative offices as required.

94 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

4. Coordination with Internal and External Stakeholders Coordination with external parties involves the Local Government and Financial Services Authority (OJK). Coordination with OJK will refer to the BI- OJK coordination mechanism in accordance with the BI-OJK joint decree concerning Cooperation and Coordination in terms of Task Implementation at Bank Indonesia and the Financial Services Authority (OJK). Meanwhile, coordination with local government shall refer to the Economic Cooperation and Regional Finance Forum.

95 FINANCIAL STABILITY REVIEW No. 27, September 2016

Box 3.2 Bank Indonesia Household Balance Sheet Survey

Maintaining monetary and financial system SNRT implementation at Bank Indonesia began stability to support sustainable economic growth, with a pilot project in 2007-2008 and since 2009 Bank Indonesia implements several strategies, has been conducted routinely, growing to involve including research and surveillance to monitor 12 provinces and 2,170 household respondents in various risks that could threaten financial system 2015. This year, Bank Indonesia plans to conduct stability. Monitoring uses a variety of performance the Household Balance Sheet Survey (SNRT) indicators for each economic unit, consisting of the with the participation of 3,500 respondents in financial sector, corporate sector and households. 14 provinces, namely, Jakarta, West Java, Central Java, East Java, , , West Sumatra, The household sector plays an important role in South Sumatra, South Kalimantan, East Kalimantan, the economy due to its function in the financial West Kalimantan, North Sulawesi, South Sulawesi system, namely as investors/borrowers (surplus and Maluku. The SNRT will be conducted towards units) and lenders (deficit units). The pressures the end of 2016. on the household balance sheet could potentially influence the financial sector and vice versa. The SNRT questionnaire for 2016 has been divided Therefore, household surveillance is vitally into two parts as follows: (i) the Household important when monitoring and gauging potential Questionnaire to obtain information on the risk in the overall financial system. demographic characteristics of all household members and the financial conditions of the Bank Indonesia routinely monitors the household household, including the assets and liabilities; (ii) sector. Annually, household surveillance is the Household Spending Questionnaire to collect achieved through the Household Balance Sheet information on income, spending and financial Survey (SNRT). SNRT aims to collect information exposures. According to the survey, households concerning the structure of household balance are defined as a family unit who cook in the same sheets in Indonesia, specifically households with kitchen. If, in one house, there is more than one access to and influence over the banking system, family cooking in separate kitchens, the household develop basic data to help design an appropriate is defined as two households. surveillance system, as well as collate household asset and liability data for inclusion in the National The survey sample is based on SUSENAS in the third and Regional Balance Sheets and indicators of quarter of 2013, which is broken down into three financial imbalances. categories according to spending as presented in Box Table 3.2.1.

96 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box Table 3.2.1 Household Classification based on Spending

Economic Class Operational Definition Annual Spending

Lower The 40% of households with the lowest spending < Rp24,5 million Middle The 40% of households with the second lowest spending Rp24,5 juta – Rp56,3 million Upper The 20% of households with the highest spending > Rp56,3 million

The sample includes 40% of lower class The modified cash basis accounting concept is also households, 40% of middle class households and used to record SNRT 2016 data, where household 20% of upper class households, thereby capturing income and spending are recorded on a cash basis, a fair representation of the characteristics of the and balance sheet transactions are recorded on population in each province. Survey locations at the an accrual basis. Family members’ incomes are provincial to enumeration area (household) level recorded as a gross figure to simplify the data are determined using multistage random sampling. validation process and enhance the accuracy of Consequently, the total and distribution of the SNRT 2016 data. SNRT 2016 sample is different in each province. The information collected from SNRT 2016 will Direct face-to-face interviews with the head include a national household demographic profile, or members of the family who understand the household financial statement (containing assets, household’s financial conditions are used to collect liabilities and net worth, profit and loss, as well as the SNRT 2016 panel data. cash flow) and financial analysis (liquidity, solvency and profitability) as well as information pertaining to household exposure.

97

Against a backdrop of global and domestic economic moderation, banking industry stability was maintained during the first half of 2016 due to a solid capital base, far beyond the minimum threshold, combined with increased bank liquidity. Despite lower lending rates, bank credit growth continued to decelerate due to low demand for new loans, which lowered the loan-to-deposit ratio (LDR). In terms of credit risk, gross non-performing loans (NPL) tracked an upward trend on dwindling corporate and household performance, which also undermined deposit growth. Furthermore, deposit growth was also slowed by a transfer of funds in the nonbank financial industry to government securities (SBN), fewer export-import transactions and less local government funds in the banking system. Seasonally, slower deposit growth at the end of the first semester was also influenced by significant withdrawals of Currency Outside Banks (COB) during Ramadan and Eid-ul-Fitr.

Congruent with the conventional banking industry, growth of Islamic banks decelerated, which was accompanied by heightened financing risk that squeezed profitability and capital. Nonetheless, Islamic banks maintained resilience.

In general, the nonbank financial industry achieved positive performance. Financing from finance companies began to pick up as funding increased. Meanwhile, the insurance industry also improved, with assets and investment observed to grow. In terms of risk, finance companies experienced elevated non-performing financing (NPF), while the business risk of insurance companies was noted to decline, indicated by an increase in the ratio of premiums to claims.

BANKS AND NONBANK FINANCIAL 4INSTITUTIONS FINANCIAL STABILITY REVIEW

The Performance of Financial Institutions Deteriorated but the Risks were Mitigated

Banking Risk Increased but Resilience was Maintained

Credit Risk

Strong Liquidity Rp Eased Capital Base Rp Maintained Gross NPL Rp Rp LA/NCD to CAR to to % % 22.56% 97.40 3.05 Market Risk Relatively Efficiency Declined Well Mitigated Intermediation Slowed BOPO but began to Recover Interest Rate Risk efficiency ratio to controlled at % Credit 82.23 % Growth to 1.92 CIR to 8.89% Currency Risk 56.20% Deposit eased to Profitability Improved Growth to Rp4,26 trilion Rp ROA to % 7.26 Risk of 2.31% LDR to Lower SBN Prices NIM to 91.12% Mitigated 5.61%

In general, the Nonbank Financial Industry achieved Positive but Slower Growth

Finance Companies Insurance Industry

Asset Growth Financing Asset Investment to Volume Growth Growth to Volume Growth to 0.93% (yoy) 12.19% (yoy) to 0.81% (yoy) Adequate Financing % Rp 13.42 (yoy) Volume Growth to Liquidity Rp

Rp Maintained ROA to Efficiency Rp Profitability Down 3.64% Declined Current Ratio Rp of ROA to ROE to BOPO % 1.69 2.12 11.14% efficiency ratio to ROE to % 4.31% 82.71 Risks Accumulated Growth of Ratio of Gross Sources of Credit Risk Claims to Funds to mitigated 1.17% Premiums up NPF at to 1.45% 155.74%

100 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Islamic Financial Institutions

Islamic Banks

Capital injections at several Islamic banks from parent companies demonstrated the industry’s avowed The Islamic banking industry experienced a period of commitment to maintain Islamic consolidation. banking performance.

Liquidity Profitability Rp Rp CAR to LA/NCD to ROE to % Rp 14.72 Rp 103.5% 5.67% LA/Deposits to ROA to 18.82% 1.11%

Intermediation Credit Risk Rp Deposits to FDR to Gross NPF % 13.06% 92.06 to Financing to 4.84% 7.85%

Takaful

The takaful industry continued to growth but tended to fluctuate

Investment Portfolio Assets increased to Rp30.61 trilion Islamic Stocks Term Deposits to 41.14% 35.75%

101 FINANCIAL STABILITY REVIEW

4.1.1. Assessment of Liquidity and Risks 4.1. The Banking Industry When compared to the previous period, banking industry liquidity improved in terms of resilience and additional liquid assets, despite a build-up of In general, banking industry performance was pressures towards the end of the second quarter of maintained in the first semester of 2016 on a 2016 due to withdrawals of Currency Outside Banks relatively solid capital base and adequate liquidity (COB) to meet demand for Ramadan and Eid-ul-Fitr. despite the intermediation function continuing to Bank liquidity was maintained as the government decelerate. Total assets of the banking industry were expanded its accounts at the beginning of the recorded at Rp6,362.7 trillion, with asset growth year, while the primary reserve requirement was slowing from 9.22% (yoy) in the previous semester loosened and credit growth decelerated. Bank to 7.24% (yoy). Meanwhile, liquidity conditions liquidity was maintained above the threshold, improved in the banking industry. Deposit growth supported by the expected deluge of repatriated decelerated, however, from 7.26% to 5.90% (yoy) funds originating from the tax amnesty. and credit growth posted a decline from 10.45% to 8.89%. In terms of credit risk, gross NPL stood at Bank liquidity resilience was evidenced by the 3.05%, deteriorating from 2.49% one year earlier. ratio of liquid assets to noncore deposits, which Notwithstanding, the net interest margin (NIM) indicates bank capacity to meet its obligations in increased due to a broader interest rate spread, the case of deposit withdrawals and to support while the banking industry maintained a Capital credit growth. In the first semester of 2016, the Adequacy Ratio (CAR) of 22.56%, dominated by ratio of liquid assets to noncore deposits increased core capital. to a level of 97.40% from 93.44% previously. The

Graph 4.1 Bank Liquidity Ratios Graph 4.2 Bank Liquid Assets

110.0% 24.0% 120 1.000 900 105.0% 23.0% 110 800 22.0% 100.0% 100 21.0% 700 95.0% 600 20.0% 90 % 500 RpT 90.0% 19.0% 80 18.0% 400 85.0% 17.0% 70 300 80.0% 16.0% 200 60 75.0% 15.0% 100 50 0 Jun’12 Des’12 Jun’13 Des’13 Jun’14 Des’14 Jun’15 Des’15 Jun’16 Jul-13 Jul-14 Jul-15 Jul-16 Jan-13 Jan-14 Jan-16 Jun-15 Oct-13 Oct-14 Oct-15 Apr-16 Apr-13 Apr-14 Apr-15 LA/NCD Liquid Assets (rhs) LA/Deposits LA/NCD (rhs) Liquid Assets = cash + placements at Bank Indonesia (demand deposits held at Bank Indonesia after the reserve requirement) + SBN; NCD = 30% of demand deposits + 3-% savings deposits + 10% of term deposit Source: Bank Indonesia Source: Bank Indonesia

102 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

elevated LA/NCD ratio was also in line with the BUKU 2 banks due to fewer SBN. For the industry, ratio of liquid assets to deposits, which was well the position of LA/NCD remained well above the above the threshold too. 50% threshold.

Based on BUKU bank group, the LA/NCD ratios of In terms of liquidity in the economy, M2 growth BUKU 1, 3 and 4 banks increased on the previous decelerated from 9.00% to 8.71% in the reporting period, while that of BUKU 2 banks was observed period as bank deposit growth slowed, primarily to decline. The higher LA/NCD ratios of BUKU 1, 3 affecting term deposits and demand deposits. In and 4 banks were driven by an increase of liquid contrast, M1 growth accelerated from 12.02% in assets, primarily placements at Bank Indonesia, as the second semester of 2015 to 13.94% in the first BUKU 2 banks transferred deposit funds to BUKU semester of 2016 as the public withdrew currency 3 and 4 banks, thus lowering the LA/NCD ratio of to meet demand during Ramadan.

Table 4.1 LA/NCD by BUKU Bank Group Table 4.2 Additional Liquid Assets in Quarter II – 2016

LA/NCD Ratio Additional Liquid Assets (Rp, trillions) in Period Quarter II – 2016 2014 2015 2016 Sem I - 2012 Ytd Yoy Jun Dec Jun Dec Jun 2014 (0.94) 33.30 BUKU 1 89.87 102.88 87.15 86.38 104.90 2015 (24.04) 126.12 BUKU 2 94.24 109.44 101.88 113.07 109.13 2016 73.05 110.11 BUKU 3 84.21 82.33 91.72 89.15 99.43

BUKU 4 86.01 107.17 90.20 90.69 92.63 Source: Bank Indonesia

Industry 86.91 99.83 92.50 93.44 97.40

Source: Bank Indonesia Graph 4.3 Liquidity Growth in the Economy and Bank Liquidity Ratios

25% M2 (%, yoy) M1 (%, yoy) LA/NCD (%) – rhs 140%

120% 20% 100% 15% 80%

10% 60% 40% 5% 20%

0% 0% Jul Jul Jul Jul Jul Jan Jan Jan Jan Jan Jun Jun Jun Jun Jun Oct Oct Oct Oct Feb Feb Feb Feb Feb Apr Apr Apr Apr Apr Sep Sep Sep Sep Dec Dec Dec Dec Nov Nov Nov Nov Mar Mar Mar Mar Mar Aug Aug Aug Aug May May May May May 2012 2013 2014 2015 2016

Graph 4.4 Government Net Expansion Graph 4.5 Annual Deposit and Credit Growth % 250.000 6.000

200.000 197.711 165.500 5.000 150.000 156.790 105.180 10.45% 100.000 3.000 8.89%

50.000 7.26% 1.000 0 5.90%

50.000 0

100.000 Sem II 2014 Sem I 2015 Sem II 201% Sem I 2016 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Deposits Credit 2013 2014 2015 2016 Source: Bank Indonesia Source: Bank Indonesia

103 FINANCIAL STABILITY REVIEW

4.1.2. Assessment of Intermediation and Risks market, particularly in the form of bond issuances Bank intermediation continued to decelerate in that surpassed growth one year earlier. Nonetheless, the first semester of 2016, in terms of credit and the surge of financing through the capital market deposits. On the demand side, intermediation was inadequate to boost economic financing, decelerated as corporate performance declined, which continued to decline as a total. Rapid growth which reduced demand for new loans. On the of bond issuances was congruent with lower yields supply side, however, banks were less inclined compared to lending rates in the banking industry, to expand credit, through more stringent lending which expanded the yield spread. standards, as a result of heightened risk. The banks primarily tightened lending standards during the Deposits first quarter of 2016 before easing standards again Bank deposits decelerated from 7.26% (yoy) in in the subsequent period. the second semester of 2015 to 5.90% (yoy) in the first semester of 2016. Sluggish deposit growth The bank lending slump was inversely proportional was blamed on weak corporate performance, to the increase in financing through the capital slower growth of local government funds held at

Graph 4.6 Lending Standards Table 4.3 LDR by BUKU Bank Group

30 Sem II Sem I Sem II Sem I Description 25 2014 2015 2015 2016 Survey Q4 20 2015 BUKU 1 Survey Q1 Credit (Rp T) 102,60 113,60 120,18 126,99 15 2016 10 Survey Q2 Deposits (Rp T) 119,27 146,81 135,08 153,71 2016 LDR (%) 86.03 77.38 88.97 82.62 5 Espektasi BUKU 2 0 Q4 2015 Credit (Rp T) 541,23 571,37 597,53 619,16 -5 Deposits (Rp T) 589,42 661,56 617,76 683,09 -10

Investment Working Consumer Total LDR (%) 91.82 86.37 96.72 90.64 Loans Capital Loans Credit Loans BUKU 3

Credit (Rp T) 1.477,40 1.532,18 1.558,53 1.568,49

Deposits (Rp T) 1.482,04 1.577,61 1.579,50 1.596,10 Graph 4.7 Intermediation Interest Rates 12 8.5 LDR (%) 99.69 97.12 98.67 98.27

8 BUKU 4 10 7.5 Credit (Rp T) 1.553,07 1.610,90 1.781,89 1.853,67 8 7 Deposits (Rp T) 1.923,69 1.933,77 2.080,91 2.141,77 6.5 6 LDR (%) 80.73 83.30 85.63 86.55 6 4 Industry 5.5 Credit (Rp T) 1.553,07 1.610,90 1.781,89 4.168,31 2 5 Deposits (Rp T) 4.114,42 4.319,75 4.413,24 4.574,67 Jun-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 LDR (%) 89.30 88.62 91.95 91.12 Lending Rate Deposit Rate BI Rate Source: Bank Indonesia

Source: Bank Indonesia

104 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 4.8 Realisation of Bank and Capital Market Financing Graph 4.9 Comparison of Banking Rates and Corporate Bonds

400 400 13,00 350 378 350 314 12,00 300 322 300 290 283 250 248 250 11,00 227 218 200 207 200 10,00 150 150 9,00 100 100 50 50 8,00 - - 7,00 Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I

2012 2013 2014 2015 2016 Jul-13 Jul-14 Jul-15 Jul-16 Jan-13 Jan-14 Jan-15 Jan-16 Sep-13 Sep-14 Sep-15 Mar-13 Nov-13 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16 May-13 May-14 May-15 May-16 IPOs Rights Issues Bond Issuances Bank Loans AAA Bonds AA Bonds A Bonds Total (rhs) Investment Loan Interest Rates BUKU 4 Banks Source: Bank Indonesia regional banks as well as the transfer of deposits nonbank financial industry transferred deposits to to government securities (SBN) in the nonbank government securities (SBN). financial industry. Cyclically, slower deposit growth in the reporting period was also due to seasonal Rupiah and foreign currency deposits grew at 9.83% Ramadan trends, when the public typically (yoy) and -12.12% (yoy) respectively, with rupiah withdraws currency for Eid-ul-Fitr. deposits accelerating from 6.73% (yoy) and foreign currency deposits decelerating from 9.97% (yoy) in By bank group, BUKU 1 and 2 banks, especially the previous period. Foreign currency deposits have regional banks, experienced slower deposit growth recorded growth in negative territory since March as local government funds decelerated and the 2016, primarily affecting BUKU 3 and 4 banks as export and import transactions slumped.

Table 4.4 Annual Deposit Growth by Bank Group

Market Share Bank Group Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016 in Semester II – 2015 (%)

BUKU 1 23.4% 26.3% 14.4% -6.8% 3.4%

BUKU 2 17.5% 14.8% 3.7% -10.3% 14.9%

BUKU 3 5.8% 10.1% 7.1% -9.4% 34.9%

BUKU 4 14.8% 12.7% 8.2% 10.8% 46.8%

Industry 12.29% 12.65% 7.26% 5.90% 100.00%

Source: Bank Indonesia

Graph 4.10 Annual Deposit Growth

40% 30% 20% 10% 6.73% 7.26% 0% -10% 9.97% -20% Semester II Semester I Semester II Semester I Semester II Semester I Semester II Semester I 2012 2013 2014 2015 2016

Deposit Growth (yoy) Rupiah Deposit Growth (yoy) Foreign Currency Deposit Growth (yoy)

Sumber: Bank Indonesia

105 FINANCIAL STABILITY REVIEW

rate offered by banks in the reporting period was Savings deposit growth nearly doubled from 8.69% observed to decrease from 7.62% to 6.82%. to 16.33% (yoy) in the first semester of 2016. Meanwhile, demand deposits and term deposits In terms of deposit composition, the share of decelerated respectively from 11.01% (yoy) and demand deposits increased to 23.44% in the 4.60% (yoy) to 1.47% (yoy) and 1.97% (yoy). The first semester of 2016. In contrast, the shares of slowdown of term deposits primarily affected term term deposits and savings deposits narrowed. deposits exceeding Rp2 billion, slowing from 2.42% The smaller share of term deposits affected all to 0.35% (yoy). Meanwhile, term deposits of less accounts (more than Rp2 billion and less than Rp2 than Rp2 billion slowed from 9.20% to 5.37% (yoy). billion). Furthermore, the diversification of local Weaker deposit growth was attributed to slower government funds from deposits to government credit growth, which reduced the need for banks to securities (SBN) also contributed to slower accumulate funds, thus providing the opportunity to deposit growth. In addition to local government lower bank dependence on expensive funds (term funds, private individual deposits, non-financial deposits). Consequently, the banks were inclined to corporations and the nonbank financial industry lower interest rates. Therefore, the average deposit also contributed to slower deposit growth.

Graph 4.11 Deposit Rates Graph 4.12 Deposit Growth by Type

(%) (%) (%) 2.5 9.0% 50

40 8.0% 2.0 30

7.0% 20 16.33%

10 5.37% 1.5 1.47% 6.0% - 0.35% (10) 1.0 5.0% (20) Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I 2012 2013 2014 2015 2016 2012 2013 2014 2015 2016 Demand Deposits Term Deposits <=Rp2 billion Demand Savings 1-Month Term Deposits (Rp) – rhs Deposits Deposits (Rp) Savings Deposits Term Deposits > Rp2 billion (Rp) Graph 4.13 Average Rate on 1-Month Rupiah Term Deposits by Graph 4.14 Composition of Bank Deposits Bank Group

9.0% 31.99% 32.06% 30.54% 30.38%

8.5% 15.17% 15.24% 15.45% 15.16%

8.0% 31.22% 28.24% 31.63% 31.02%

7.5% 7.62 21.62% 24.46% 22.38% 23.44% 7.0%

Smt II 2014 Smt I 2015 Smt II 2015 Smt I 2016 6.82 6.5% Demand Deposits Term Deposits <=Rp2 billion

6.0% Savings Deposits Term Deposits > Rp2 billion Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16

Buku 1 Buku 2 Buku 3 Buku 4 Industry

Source: Bank Indonesia Source: Bank Indonesia

106 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Geographically, slower deposit growth affected all Loan Performance regions. Most deposits were accumulated on the Credit growth continued to track a decelerating island of Java, followed by Sumatera and Kalimantan, trend through the first semester of 2016. Credit in line with business activity and the circulation of growth declined from 10.45% (yoy) in the second money that also tended to concentrate on Java, semester of 2015 to 8.89% (yoy) in the reporting Jakarta in particular. Jakarta accounted for 49.49% period congruent with domestic and global of total bank deposits. Graph 4.15 Deposits by Holder Rp T 250 Sem I 2015 Sem II 2015 Sem I 2016 200 150 100 50 0% -50 -100 -150 -200

Central Local Private Private - Nonbank Non-Financial Private – Other Non-Resident Government Government Individual Financial Industry Institutions

Table 4.5 SBN Holdings by Institution

SBN Holdings through to 2016

Q1 Q2 Juli 2016 Posisi Institution (Rp, trillions) 2013 2014 2015 2016 2016 2016 (ytd Juli) Juli’06 Banks : 35,8 40,1 -25,5 90,8 -79,3 109,0 120,5 470,6

Bank Indonesia *) 41,4 -2,8 107,3 -90,7 91,9 -107,3 -106,0 42,9

Nonbanks : 97,9 177,4 170,1 103,2 69,2 24,6 196,9 1159,8

Domestic Nonbanks : 44,5 39,9 72,9 57,0 29,8 9,6 96,4 500,8

- Nonbank Financial 11,5 42,0 61,4 27,1 46,8 10,5 91,2 452,8 Industry

- Mutual Funds -0,7 3,3 15,8 5,5 9,3 1,5 16,3 77,9

- Insurance 46,1 21,0 21,0 17,7 25,2 -1,0 41,8 213,4

- Pension Funds -17,0 3,8 6,5 5,9 8,9 1,0 15,8 65,7

- Others -17,0 13,8 18,0 -2,1 3,4 9,1 17,3 95,8

Individual 32,5 -2,1 12,1 23,3 -17,0 -0,9 5,4 48,0

Non-Resident 53,3 137,5 97,2 46,1 39,9 15,0 100,5 659,0

Total 175,0 214,7 251,9 103,3 81,7 26,4 211,4 1673,2

Table 4.6 Share of Total Deposits by Island

Annual Growth Share Island Sem I of Deposits (%) 2013 2014 2015 2016

Java 14.25 12.86 7.48 6.27 76.93

Sumatera 9.43 12.12 4.79 3.05 11.30

Kalimantan 8.35 5.25 0.81 0.58 4.30

Sulawesi 11.04 9.96 17.87 14.07 3.21

Bali and Nusa Tenggara 15.16 11.36 10.09 7.87 2.69

Papua and Maluku Islands 13.17 13.35 8.38 6.13 1.58

Source: Bank Indonesia

107 FINANCIAL STABILITY REVIEW

Graph 4.16 Bank Credit Growth

40% 35% 30% 25% 20% 15% 12,25% 10% 8,89% 5% 0% -5% -10% -7,76%

Semester I Semester II Semester I Semester II Semester I Semester II Semester I Semester II 2012 2013 2014 2015

Credit Growth (yoy) Rupiah Credit Growth (yoy) Foreign Currency Credit Growth (yoy) Source: Bank Indonesia

economic moderation, which stifled demand Slower credit growth affected all loan types, for new loans as the corporate sector held off namely working capital loans, investment loans investment and households were more inclined to and consumer loans. Working capital loans were repay loans using savings. In addition, the banks hardest hit, particularly loans extended to the became more prudent lenders in order to mitigate manufacturing industry and mining sector. In the rising non-performing loans (NPL). manufacturing sector, the cigarette and paper industries were the largest contributors to the In terms of loan currency, growth of rupiah loans decline, while in the mining sector, the coal accelerated from 11.95% (yoy) to 12.25% (yoy), subsector as well as oil and gas were most affected. while foreign currency loans slipped into negative Likewise, the mining sector also contributed to territory, decelerating from 2.98% (yoy) to -7.76% slower growth of investment loans. In terms of (yoy). Less foreign currency lending, coupled with consumer loans, slower growth stemmed from more rupiah loans, was linked to a decline in import- multipurpose loans. Nonetheless, productive loans export activity as well as greater disbursements of continued to dominate bank credit, namely working People’s Business Credit (KUR) in 2016. capital loans.

Graph 4.17 Credit Growth by Loan Type Graph 4.18 Market Share of Different Loans

(%) 16 14.70 14 WCL IL 12.03 47.06% 25.40% 12 10.83 10.14 9.92 10 9.05 9.09 8.84 8 7.30 6 4 2 CL 27.54% - Working Capital Investment Consumer Loans Loans Loans

I - 2015 II - 2015 I - 2016

Source: Bank Indonesia Source: Bank Indonesia

108 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

By economic sector, the manufacturing industry, line with negative mining GDP growth due to soft mining and trade sectors were the main contributors international commodity prices. to slower credit growth in the reporting period. In the manufacturing sector, the cigarette, paper, Regionally, slower credit growth was found on Java motor vehicle components, cooking oil and animal and Sumatera, which undermined national credit feed industries were the largest contributors to growth despite loans in other areas beginning weak credit growth, along with coal, oil and gas as to recover. In terms of market share, most loans well as oil and gas services from the mining sector. were disbursed on Java, followed by Sumatera, Slower credit growth in the mining sector was in Kalimantan and Sulawesi.

Table 4.7 GDP Growth by Economic Sector

2014 2015 2016 Sector Jun Des Jun Des Jun Agriculture 4.88 3.32 6.86 1.57 3.23

Mining 1.15 1.51 (5.20) (7.91) (0.72)

Manufacturing 4.83 4.18 4.11 4.35 4.74

Electricity 6.47 6.50 0.76 1.81 6.24

Water 5.77 6.87 7.76 6.77 3.31

Construction 6.46 7.67 5.35 8.24 6.21

Trade 4.99 4.48 1.70 2.77 4.07

Transportation & Warehousing 7.56 7.20 5.92 7.67 6.81

Hotels and Restaurants 6.35 4.57 3.75 5.79 4.92

Information & 10.46 10.33 9.66 9.74 8.47 Communications

Financial Services 5.46 7.87 2.63 12.52 13.51

Real Estate 4.93 5.30 5.03 4.25 4.46

Corporate Services 9.99 9.69 7.64 8.13 7.57

Government Administration (2.49) 6.84 6.29 6.70 4.74

Education 4.48 6.62 11.71 5.32 5.58

Healthcare 8.74 6.03 7.48 7.44 6.59

Other Services 9.46 8.38 8.06 8.15 7.88

Source: Bank Indonesia

Graph 4.19 Credit Growth by Economic Sector

(%) 30 26.41 25 19.88 20 18.03

15 14.14 8.89 10 8.58 8.61 6.01 4.98 5 2.70

-

(-5)

(-10) -14.47 (-20)

Trade Total Others Mining Electricity Agriculture Construction Manufacturing Transportation Social Services Corporate Services I-2015 II-2015 I-2016

Source: Bank Indonesia

109 FINANCIAL STABILITY REVIEW

Table 4.8 Market Share of Credit in Indonesia based on Project Location

Annual Credit Growth Market Share Island Sem I of Credit (%) 2013 2014 2015 2016

Java 22.41 12.06 10.76 8.66 69.46

Sumatera 17.79 9.36 9.72 8.13 14.88

Kalimantan 21.72 9.69 3.16 5.19 6.03

Sulawesi 16.88 10.90 14.55 15.05 5.12

Bali & Nusa Tenggara 26.08 17.61 10.72 10.88 3.24

Papua & Maluku Islands 22.14 12.01 11.77 12.74 1.27

Source: Bank Indonesia

Graph 4.20 Lending Rates by Bank Group Table 4.9 Credit Growth by Bank Group

17% Pangsa Sem I Sem II Sem I Sem II Pasar Posisi BUKU 16% 2014 2014 2015 2015 Semester I 2016 (%) 15% 14% BUKU 1 14.54 17.88 17.13 11.79 3.05

13% BUKU 2 15.57 12.86 10.40 8.36 14.85 12% BUKU 3 9.85 7.89 5.49 2.37 37.63 11% 10% BUKU 4 11.74 11.42 14.73 15.07 44.47

Industry 11.59 10.37 10.45 8.89 100.00 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-12 Sep-13 Sep-14 Sep-15 Dec-12 Dec-13 Dec-14 Dec-15 Mar-13 Mar-14 Mar-15 Mar-16

BUKU 1 BUKU 2 BUKU 3 BUKU 4 Source: Bank Indonesia

By bank group, slower credit growth in the reporting first semester of 2016 reached Rp827.3 trillion, period affected nearly all bank groups, most accounting for 19.7% of all disbursed bank loans. significantly BUKU 1 banks, where lending rates are highest and loans therefore susceptible to economic Growth of MSME investment loans increased from moderation so credit growth decelerated to 11.79% 9.2% (yoy) in the second semester of 2015 and 7.8% (yoy). In contrast, credit growth accelerated at (yoy) in the first semester of 2015 to 9.6% (yoy) in BUKU 4 banks, due primarily to microfinance in the the reporting period. Meanwhile, working capital form of People’s Business Loans (KUR), for which loans accelerated slightly to 7.8% (yoy) from 7.6% BUKU 4 banks are the dominant lenders. (yoy) in the previous semester.

MSME Credit Stronger MSME credit growth affected several Against a backdrop of weaker intermediation, economic sectors as demand for financing MSME credit growth accelerated from 6.8% (yoy) increased and public purchasing power improved. the year earlier to 8.0% (yoy). The surge of MSME MSME credit growth accelerated in the wholesale loans originated primarily from People’s Business and retail sector, increasing to 12.5% (yoy) from Loans (KUR) due to the Government’s interest 11.6% (yoy) in the second semester of 2015 rate subsidy scheme. Nominally, lending to micro, and 8.7% (yoy) one year earlier. Similarly, in the small and medium enterprises (MSMEs) in the construction and real estate sectors, MSME credit

110 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

growth accelerated respectively from 5.4% (yoy) Regionally, the distribution of MSME credit and 9.3% (yoy) in the second semester of 2015 to remained uneven with a concentration in economic 8.0% (yoy) and 11.7% (yoy). hubs, such as areas on the islands of Java and Sumatera, with respective shares accounting for Conversely, the agricultural and forestry sector as 57.8% and 20.1% of the total. In contrast, the well as the manufacturing industry experienced shares of Kalimantan, Sulawesi, Bali and Nusa slower MSME credit growth, decelerating Tenggara, as well as Papua and the Maluku Islands respectively from 12.0% (yoy) and 10.0% (yoy) to remained comparatively small due to a lack of 9.8% (yoy) and 5.3% (yoy). A significant change in banking infrastructure, which tends to concentrate the climate, which undermined production due to in urban areas. a delayed planting season, affected MSME credit growth in the agricultural and forestry sector, By sector, most MSME loans were absorbed by while low demand for goods and services in the medium enterprises operating in the wholesale and manufacturing industry also eroded MSME credit retail sector (53.0% share) due to the competences growth. of human capital in the banking industry in terms of

Graph 4.21 MSME Credit

Trilion Rp (%) 900 25.0 800 386 700 20.0 19.70 600 15.0 500 247 400 10.0 300 8.3 200 5.0 100 194 - 0.0 Jul-16 Jul-13 Jul-14 Jul-15 Jan-13 Jan-15 Jan-16 Jan-14 Oct-13 Oct-14 Oct-15 Apr-13 Apr-14 Apr-15

Medium Enterprises Small Enterprises Micro Enterprises Annual MSME Credit Growth (rhs) MSME Credit Share (rhs) Source: Bank Indonesia

Graph 4.22 MSME Credit Growth in Five Economic Sectors 60.0%

50.0% 11.7% 40.0% 11.1% 8.5% 30.0% 5.3%

20.0% -4.6%

10.0%

0.0%

-10.0% -15.8% -20.0% Jul Jul Jul Jul Jan Jan Jan Jan Jun Jun Jun Jun Feb Feb Feb Feb Oct Oct Oct Apr Apr Apr Apr Sep Sep Sep Dec Dec Dec Nov Nov Nov Mar Mar Mar Mar Aug Aug Aug May May May May 2013 2014 2015 2016

Agriculture Trade Social Services Real Estate Manufacturing Source: Monthly Commercial Bank Reports, processed

111 FINANCIAL STABILITY REVIEW

extending loans to the trade sector as well as more Business Loans (KUR), for which BUKU 4 banks were measurable potential risks. Meanwhile, MSME also dominant. Such conditions were corroborated loans disbursed to other sectors remained low, by an increase in credit growth to micro and small including the manufacturing industry (10.0% share) enterprises, which accelerated respectively from as well as the agricultural, hunting and forestry 11.2% (yoy) and 6.4% (yoy) to 12.5% (yoy) and sector (8.1% share). 13.6% (yoy).

By bank group, BUKU 4 banks dominated MSME People’s Business Loans (KUR) loan disbursements in the first semester of 2016 KUR disbursements reached Rp54.8 trillion in because of the competitive advantages necessary the first semester of 2016, equivalent to 54.8% to lend to MSMEs, while maintaining credit quality of the Rp100 trillion targeted for 2016. KUR through a broad office network that penetrates disbursements still tended to concentrate on Java rural areas, coupled with adequate staffing levels. (48.9%), dominated by microfinance (66.2%) to the Consequently, MSME credit growth accelerated at wholesale and retail sector (69.3%). BUKU 4 banks, primarily in the form of People’s

Table 4.10 Growth and Market Share of MSME Credit by BUKU Bank Group (%) Annual MSME Credit Growth MSME Credit Share

BUKU Sem I Sem II Sem I Sem II Sem I Sem I Sem II Sem I Sem II Sem I 2014 2014 2015 2015 2016 2014 2014 2015 2015 2016

BUKU 1 18.02 16.54 10.85 -0.60 -1.90 5.48 5.59 5.68 5.14 5.10

BUKU 2 61.04 46.05 -3.78 -11.09 -10.40 17.61 16.64 15.87 13.70 13.10

BUKU 3 11.89 4.81 -2.29 6.40 3.70 30.13 28.69 27.57 28.26 26.40

BUKU 4 9.58 13.28 16.12 16.41 17.70 46.78 49.08 50.87 52.89 55.30

Source: Monthly Commercial Bank Reports, processed

Graph 4.23 Net Expansion of MSME Loans at Commercial Banks Trilion Rp

60 54.8 40 24.3 12.0 11.7 12.6 11.6 20 6.2 8.0 7.6 8.7 0 -3.2 -2.8 -3.1 1.3 -2.9 -4.2 3.8 -16.8 -20 -18.0 -28.0 -40 Jan-15 Jan-16 Jun-16 Feb-16 Feb-15 Apr-16 Mar-15 Mar-16 May-16

KUR Non-KUR Jan-Jul-16

Graph 4.24 Net Expansion of MSME Loans at BUKU 4 Banks Graph 4.25 Net Expansion of MSME Loans at BUKU 1 & 2 Banks Trilion Rp Trilion Rp 60 30 54.7 21.3 21.8 20.7 50 20 17.4 10.0 11.4 8.9 3.0 9.4 9.7 7.4 40 10 2.9 2.7 6.3 0.7 4.9 3.8 0.7 0.7 2.6 0.2 1.0 1.5 1.7 30 0 -2.3 -2.1 -1.5 -1.1 -1.3 -10 -5.3 -6.5 20 -9.8 -4.4 12.6 11.6 9.5 8.0 7.6 8.7 -20.0 10 6.2 -20 -2.7 3.3 -3.7 -21.8 0 -30 2.7 0.6 2.1 5.6 -2.5 -2.7 -5.7 -10 -8.1 Jul-15 Jan-15 Jan-16

-14.2 Jun-15 Jun-16 Oct-15 Feb-15 Feb-16 Apr-15 Apr-16 Sep-15 Dec-15 Mar-15 Mar-16 Nov-15 Aug-15 -20 -17.2 May-15 May-16 BUKU 1&2 Total Bank -30 Jan-15 Jan-16 Jun-16 Feb-16 Feb-15 Apr-16 Mar-15 Mar-16 May-16

KUR Non-KUR Jan-Jul-16

112 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

The KUR scheme was refined in 2016 and redirected predominantly BUKU 1 and 2 banks, have submitted towards stimulating the depressed economy. requests to disburse KUR, which is expected to Through Coordinating Minister for Economic Affairs offset the MSME credit decline. Regulation No. 13 of 2015, the KUR scheme was refined as follows: Credit Risk a) The scope of borrowers was expanded to include Credit risk continued to accumulate in the first start-up businesses (operating for a minimum of semester of 2016, evidenced by gross non- three months). performing loans (NPL) tracking an upward trend to b) The interest rate on KUR loans was capped at 9%. 3.05%. Credit risk built as corporate performance c) The scope of KUR lenders was expanded to deteriorated, which undermined corporate healthy banks and nonbanks, recommended by repayment capacity and household income. Credit the relevant supervisory authority, and risk associated with investment loans and working d) Other credit schemes were incorporated into the capital loans increased on the same period of the KUR program. previous year, while the NPL of consumer loans declined slightly. Working capital loans experienced The banking industry exploited the low-interest the largest increase of gross NPL, deteriorating KUR scheme to curb a deeper MSME credit decline, from 2.98% to 3.74%. Meanwhile, gross NPL of confirmed by KUR expansion and increased market investment loans worsened from 2.72% to 3.26% share to total credit from January to June 2016. but the NPL of consumer loans improved slightly In general, however, non-KUR MSME loans have from 1.68% to 1.67%. Compared to the second contracted since the beginning of the year despite semester of 2015, however, credit risk on all early signs of recovery at the end of the first loans increased from 2.99%, 2.61% and 1.50% semester. Several finance companies and banks, respectively for working capital loans, investment loans and consumer loans.

Graph 4.26 NPL Ratio (%) 4.5 4.0 3.5 3.0 2.5 3.05% 2.0 2.16 1.5

1.0 1.54% 1.08 0.5 - 2008 2009 2010 2011 2012 2013 2014 2015 2016

Gross NPL Net NPL

Source: Bank Indonesia

113 FINANCIAL STABILITY REVIEW

Graph 4.27 Gross NPL Ratio by Economic Sector Graph 4.28 Gross NPL Ratio by Loan Type (%) 3.74 (%) 3.5 3.26 6.28 2.98 2.99 6 5.54 3.0 2.72 2.61 5 4.55 2.5 3.95 3.85 4 2.0 2.89 3.05 1.68 1.67 3 1.66 1.50 1.68 1.98 1.85 1.5 2 1.0 1 0 0.5 0.0 Trade Total Others Mining Working Investment Electricity Consumer Agriculture Capital Loans Construction Loans ManufacturingTransportation Social Services Loans

Corporate Services

Source: Bank Indonesia Source: Bank Indonesia

In comparison to the first semester of 2015, the The gross NPL of the transportation and manufacturing industry was the main contributor to communications sector stood at 5.45% in the working capital NPL, especially the textile processing first half of 2016, increasing from 3.46% one industry, plastic articles industry, beverages year earlier and 3.84% in the second semester industry and animal feed industry. Meanwhile, the of 2015. Subsectors linked to the supply chain manufacturing and mining industries contributed of coal transportation, namely domestic sea to investment NPL, particularly the sugar and coal transportation, were the main contributors to subsectors, while property loans for large houses increased credit risk in the transportation sector. exceeding 70m2 were than main contributor to The gross NPL of the domestic sea transportation non-performing consumer loans. subsector doubled from 5.15% one year earlier to 11.50% in the first semester of 2016. By economic sector, the most significant spike in NPL was observed to affect the mining sector, Meanwhile, credit risk in the manufacturing industry transportation and communications as well as the was also noted to increase significantly, from 2.26% manufacturing industry. The mining sector recorded in the first semester of 2015 and 2.50% in the the highest level of gross NPL in the reporting period second semester of 2015 to 3.85% in the reporting at 6.28%. In addition to posting the highest gross period. Credit risk in the manufacturing industry NPL, the upward trend shows no signs of abating was not concentrated in one or two subsectors but in the mining sector. In line with the downturn in spread over several, including textile processing, the coal subsector, the banking industry began to plastic articles, packaged beverages and animal limit its exposure, thus the largest contributor to feed. NPL shifted from the coal mining to the oil and gas mining subsector. Accordingly, the gross NPL of Regionally, the gross NPL ratio of the banking the oil and gas mining subsector skyrocketed from industry increased in Kalimantan, Bali and Nusa 0.78% in the first semester of 2015 to 3.37% in the Tenggara as well as Java. Kalimantan, as a region first semester of 2016. hit hard by sliding international commodity prices,

114 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

recorded the largest NPL spike, increasing from Bank credit quality deteriorated as more corporate 3.40% in the first semester of 2015 to 4.76% in the bonds were downgraded. Based on the Pefindo reporting period. Nonetheless, the credit share of rating, 24 corporate bonds have already been Kalimantan was comparatively small, therefore the downgraded in 2016 compared to just 13 in the impact on the national NPL profile is expected to whole of 2015. be minimal. MSME Credit Risk Table 4.11 Gross NPL by Region Consistent with the prevailing credit risk trend in the Sem-II Sem-I Sem-II Sem-I Credit ISLAND 2014 2015 2015 2016 Share (%) overall banking industry, MSME credit risk tended Java 1.94 2.27 2.27 2.91 69.46 to accumulate at the end of the first semester of Sumatera 2.60 3.34 2.82 3.14 14.88 2016, indicated by a deterioration in the gross NPL Kalimantan 3.01 3.42 3.86 4.76 6.03

Sulawesi 3.01 3.40 2.98 2.99 5.12 ratio from 4.20% in the previous period to 4.58%.

Bali & Nusa 1.37 1.84 2.15 2.69 3.24 Heightened MSME credit risk stemmed from Tenggara

Papua & lower repayment capacity due to less demand for 3.59 4.09 3.72 3.79 1.21 Islands Maluku goods and services. From the banks’ perspective, Source: Bank Indonesia however, rising NPL was caused by: (i) lack of bank competence to extend loans to micro, small and Based on bank group, however, compared to the medium enterprises (MSMEs); (ii) limited human first and second semesters of 2015, the gross NPL resources (quality and quantity) in terms of MSME ratio of all BUKU bank groups was reported to credit management; and (iii) limited office network increase, most significantly at BUKU 2 and 4 banks. that restricts MSME credit monitoring. Nevertheless, the NPL level remained below the 5% threshold. Graph 4.29 Gross NPL by Region

(%) Table 4.12 Gross NPL Ratio by Bank Group 5.00

BUKU Sem-II 2014 Sem-I 2015 Sem-II 2015 Sem-I 2016 4.50 4.20% BUKU 1 2.23 2.60 2.26 2.84 4.00 BUKU 2 2.84 3.22 3.05 3.82 3.97% 3.50 BUKU 3 2.61 2.96 2.96 3.29 3.23% 3.19% BUKU 4 1.49 1.94 1.90 2.61 3.00

Industry 2.16 2.56 2.49 2.49 Jan Feb Mar Apr Mei Jun Jul Agt Sep Okt Nov Des

2012 2013 2014 2015 2016 Source: Bank Indonesia Source: Bank Indonesia Table 4.13 Total Downgraded Bonds (Pefindo Rating)

Periode 2016 2015 2014 2013 2012 2011 2010

Q1 6 2 4 0 5 0 1 Based on business scale, small businesses recorded Q2 12 7 2 1 3 0 3 the highest gross NPL ratio at 5.35%, followed by Q3 6 1 5 1 1 1 0 medium enterprises (5.01%) and micro enterprises Q4 0 3 4 0 1 1 1

Total 24 13 15 2 10 2 5 (2.75%). Based on bank group, however, BUKU 2

Source: Bank Indonesia banks posted the highest gross NPL ratio for MSME

115 FINANCIAL STABILITY REVIEW

loans at 8.29%, followed by BUKU 1 banks (5.55%), Graph 4.31 Lending and Deposit Rates BUKU 3 banks (5.09%) and BUKU 4 banks (3.37%).

Mining and Quarrying 9.07% 7.68% Graph 4.30 Gross NPL Ratio of MSME Loans by Business Transportations and 5.19% Telecommunications Scale 4.83% (%) Agriculture and Forestry 4.80% 7.00 4.67% 6.00 5.35% Wholesale and Retail 4.35% 5.00 5.01% 4.30% 4.58% 4.00 Manufacturing Industry 4.21% 3.00 3.03% 3.96% 2.75% 2.00 Financial Intermediation 2.90% 1.00 2.72% 0.00 Education 2.31% 2.10% Utilities 1.61% Jun-14 Jun-15 Jun-16 Oct-14 Oct-15 Feb-14 Feb-15 Feb-16 Apr-14 Apr-15 Apr-16 Dec-14 Dec-15 Dec-13 Aug-14 Aug-15 0.96% MSME Micro Small Medium Banking International Organisations 0.80% Industry Source: Monthly Commercial Bank Reports, 2016, processed 0% 2% 4% 6% 8% 10% 12%

Source: Monthly Commercial Bank reports, 2016, processed MSME credit quality deteriorated in nearly all economic sectors during the reporting period, Authority (OJK). At the end of the reporting quarter, most significantly the wholesale and retail sector the deposit rate on 1-month rupiah term deposits (4.35%) as well as the agricultural sector (4.80%). was lowered from 7.60% to 6.82%, while the rate Meanwhile, credit risk in the mining and quarrying on demand deposits was reduced from 2.10% to sector, which has escalated since the middle of 2.03% and savings deposits from 1.86% to 1.58%. 2014 in line with sliding international commodity prices, began to improve in the first semester of By bank group, all BUKU bank groups lowered 2016, dropping from 10.4% to 9.07%. deposit rates, except for BUKU 1 banks. BUKU 3 and 4 banks lowered their deposit rates in compliance 4.1.3. Market Risk with OJK interest rate capping policy. Market risk at banks in Indonesia originates from changes in market interest rates on: (i) lending and In line with lower deposit rates, the banks also deposit rates; (ii) SBN portfolio prices held by the lowered lending rates but to a lesser degree. Banks banking industry; and (iii) currency risk. lowered the rate on rupiah working capital loans Interest Rate Risk from 12.48% to 11.48%, on rupiah investment Interest rate risk from accumulating funds and loans from 12.12% to 11.49% and on consumer disbursing loans was relatively well mitigated loans from 13.88% to 13.83%. In general, lower because deposit rates were lowered at a faster deposit rates fed through to lower lending rates, pace than lending rates, which maintained bank which reduced the cost of intermediation against profitability. the backdrop of a lower BI Rate. Furthermore, the banks lowered interest rates on working capital In the first semester of 2016, the banks lowered loans and investment loans in order to stimulate most deposit rates in line with the reference BI Rate lending as demand for working capital loans and and interest capping policy of the Financial Services investment loans began to dwindle.

116 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 4.32 Lending and Deposit Rates

(%) 14 9

12 8.5 10 8

8 7.5

6 7 4 6.5 2 6 Jan-10 Jun-11 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-10 Sep-11 Sep-12 Sep-13 Sep-14 Sep-15 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14 Dec-15 Mar-11 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16

Spread (rhs) Lending Rate Deposit Rate

Table 4.14 Deposit Rates by BUKU Bank Group Table 4.15 Lending Rates by BUKU Bank Group

1-Month Rp Interest Rate Smt I Smt II Smt I Smt II Smt I Term Deposit on Rp Working Smt I Smt II Smt I Smt II Smt I 2014 2014 2015 2015 2016 Rate (%) Capital Loans 2014 2014 2015 2015 2016 (%) BUKU 1 9.00 9.17 8.72 8.67 7.59 BUKU 1 16.42 18.31 17.99 17.57 17.77 BUKU 2 8.24 9.11 8.12 7.90 7.21 BUKU 2 13.52 13.71 13.15 13.01 12.26 BUKU 3 8.67 8.91 8.20 8.13 7.03 BUKU 3 12.68 12.68 12.53 12.37 11.75 BUKU 4 7.77 7.95 7.00 6.76 6.22 BUKU 4 12.08 12.22 12.31 12.02 11.34 Industry 8.27 8.58 7.78 7.60 6.82 Industry 12.64 12.81 12.71 12.48 11.84 Rp Demand Smt I Smt II Smt I Smt II Smt I Deposit Rate 2014 2014 2015 2015 2016 (%) Interest Rate on Rp Smt I Smt II Smt I Smt II Smt II BUKU 1 2.83 2.59 2.87 3.06 3.08 Investment 2014 2014 2015 2015 2016 Loans (%) BUKU 2 2.74 2.50 2.61 2.36 2.54 BUKU 1 17.21 16.21 15.75 14.29 14.44 BUKU 3 2.49 2.52 2.59 2.49 2.66 BUKU 2 13.17 13.62 13.37 13.16 12.63 BUKU 4 1.92 1.90 1.74 1.75 1.42 BUKU 3 13.15 13.17 13.11 13.01 12.08 Industry 2.32 2.22 2.25 2.10 2.03 BUKU 4 11.05 11.25 11.25 11.19 10.72 Rp Savings Smt I Smt II Smt I Smt II Smt I Deposit Rate Industry 12.25 12.36 12.30 12.12 11.49 2014 2014 2015 2015 2016 (%)

BUKU 1 3.06 2.97 3.16 2.79 3.03 Interest Rate on Rp Smt I Smt II Smt I Smt II Smt I BUKU 2 3.08 3.03 2.92 2.66 2.12 Consumer 2014 2014 2015 2015 2016 Loans (%) BUKU 3 2.55 2.68 3.03 3.15 2.6 BUKU 1 14.16 14.03 14.03 13.99 14.31 BUKU 4 1.42 1.35 1.27 1.31 1.21 BUKU 2 12.86 13.27 13.54 13.49 13.11 Industry 1.88 1.87 1.85 1.86 1.58 BUKU 3 15.16 15.28 15.45 15.30 15.02 Source: Bank Indonesia BUKU 4 11.46 11.90 12.22 12.60 12.91

Industry 13.30 13.58 13.82 13.88 13.83

Source: Bank Indonesia

Moving forward, the downward bank interest rate Currency Risk trend is expected to persist after the BI Rate was Exchange rate volatility eased in the first semester of replaced by the BI 7-Day (Reverse) Repo Rate in 2016, as the issue of monetary policy normalisation August 2016. The BI 7-Day (Reverse) Repo Rate was in the United States gained clarity. The Brexit set at a level of 5.25% from June until August 2016, referendum was held in the first semester of 2016 and then lowered 25bps to 5.0% in September 2016 but the impact on exchange rates was relatively and another 25bps to 4.75% in October 2016. minimal and transient. Consequently, market risk

117 FINANCIAL STABILITY REVIEW

in the banking sector through the exchange rate Risk of Lower SBN Prices tended to remain low. Furthermore, the low net Banking industry risks originating from changes open position (NOP) was also indicative of mild to SBN prices were well mitigated in line with less currency risk. volatility and lower yields. In addition, the banks increased SBN placements by allocating available At the end of the first semester of 2016, the for sale (AFS) and hold to maturity (HTM), which banking industry recorded a long foreign currency demonstrates the banks’ proclivity for using SBN as position totalling Rp2.22 trillion, down slightly on a liquid asset and long-term investment instrument, the Rp4.36 trillion posted at the end of the second not to trade. The banks increased SBN holdings as semester of 2015. The decline was congruent with an alternative because credit growth decelerated. rupiah appreciation, strengthening from Rp13,795 per USD in December 2015 to Rp13,180 per USD in Consequently, the banks’ SBN portfolio increased June 2016. At the end of the first semester of 2016, 8.6% form Rp377.3 trillion at the end of the second the NOP to capital ratio increased from 1.24% to semester of 2015 to Rp409.6 trillion at the end of 1.52%, remaining far below the 20% threshold. the first semester of 2016. By bank group, BUKU 4 BUKU 2 banks maintained the highest NOP position banks controlled the largest SBN holdings, followed at 2.18%, followed by BUKU 4 banks (1.56%), BUKU by BUKU 3 and 2 banks. 1 (1.29%) and BUKU 3 (1.13%). Bu bank group, BUKU 3 and 4 banks favoured In terms of liabilities, the banks remained relatively AFS SBN, while BUKU 1 and 2 banks opted to secure against the risk of maturing debt. In general, expand the HTM SBN portfolio. Such conditions the value of short and long-term bank obligations demonstrate the disparate strategies of BUKU 3 and was relatively stable, reflecting bank prudence 4 banks, which hold SBN for liquidity purposes and when managing liabilities to the potential risk of occasionally liquidate the instrument, while BUKU mature debt. 1 and 2 banks hold SBN for long-term investment purposes. Graph 4.33 Total NOP and NOP Ratio by Bank Group

Total NOP 6.0 5.0 If required, BUKU 3 and 4 banks could readily sell 4.0 3.0 SBN and disburse the funds as credit without facing 2.0 Rp Trilion 1.0 accounting penalties. Meanwhile, the trading 0.0 -1.0 portfolios of all bank groups remained relatively -2.0 -3.0 unchanged. Buku 1 Buku 2 Buku 3 Buku 4

NOP Ratio 6% 4.1.4. Assessment of Banking Industry Foreign 5% 4% Loans 3% 2% Banking industry foreign loans have tracked a 1% 0% Dec-11 Jun-12 Dec-12 Jun-13 Dec-13 Jun-14 Dec-14 Jun-15 Dec-15 Jun-16 downward trend since the middle of 2014 in line

Buku 1 Buku 2 Buku 3 Buku 4 Industry with economic moderation. Therefore, the banks Source: Bank Indonesia

118 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

have utilised unabsorbed funds to reduce exposure to foreign loans.

Graph 4.34 SBN Yield Volatility

40 35 30 25 20 15 10 5 - 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126

Sem I 2014 Sem II 2014 Sem I 2015 Sem II 2015 Sem I 2016

Table 4.16 SBN Holding Value by Bank Group

Trading SBN Smt I Smt II Smt I Smt II Smt I Smt II Smt I (Rp, trillions) 2013 2013 2014 2014 2015 2015 2016

BUKU 1 0.11 0.04 0.10 0.03 0.23 0.26 0.02

BUKU 2 10.86 5.47 9.68 12.16 7.84 13.51 12.01

BUKU 3 13.86 9.57 17.18 11.32 15.93 17.31 21.47

BUKU 4 1.88 0.80 1.97 2.39 3.61 2.62 2.47

Industry 26.52 15.88 28.93 25.90 27.62 33.70 26.23

AFS SBN Smt I Smt II Smt I Smt II Smt I Smt II Smt I (Rp, trillions) 2013 2013 2014 2014 2015 2015 2016

BUKU 1 1.63 1.27 1.01 1.13 1.17 1.21 0.88

BUKU 2 11.86 15.10 18.60 19.09 25.44 27.92 27.51

BUKU 3 36.64 51.77 51.11 56.35 67.67 79.62 84.36

BUKU 4 114.48 108.10 123.26 123.14 96.44 110.74 126.21

Industry 164.61 176.23 193.98 199.71 190.73 219.50 238.96

HTM SBN Smt I Smt II Smt I Smt II Smt I Smt II Smt I (Rp, trillions) 2013 2013 2014 2014 2015 2015 2016

BUKU 1 1.22 1.57 1.99 2.35 2.58 2.67 2.64

BUKU 2 13.39 16.12 14.06 15.49 18.79 23.61 29.29

BUKU 3 7.04 11.51 14.24 18.25 21.47 30.97 28.55

BUKU 4 53.43 39.95 55.00 59.56 54.32 66.79 73.88

Industry 75.07 69.16 85.28 95.65 97.16 124.05 134.37

Source: Bank Indonesia, processed

119 FINANCIAL STABILITY REVIEW

Table 4.17 Share of SBN Holdings by Bank Group

Smt I Smt II Smt I Smt II Smt I Smt II Smt I BUKU 4 2013 2013 2014 2014 2015 2015 2016

Trading 1.10 0.54 1.09 1.29 2.34 1.46 1.22

AFS 67.43 72.62 68.39 66.53 62.47 61.47 62.31

HTM 31.46 26.84 30.51 32.18 35.19 37.07 36.47

Smt I Smt II Smt I Smt II Smt I Smt II Smt I BUKU 3 2013 2013 2014 2014 2015 2015 2016

Trading 23.84 13.14 20.82 13.17 15.16 13.53 16.14

AFS 63.89 71.06 61.93 65.59 64.40 62.25 62.65

HTM 12.27 15.80 17.25 21.24 20.44 24.22 21.21

Smt I Smt II Smt I Smt II Smt I Smt II Smt I BUKU 2 2013 2013 2014 2014 2015 2015 2016

Trading 30.06 14.90 22.87 26.02 15.06 20.77 17.45

AFS 32.85 41.16 43.93 40.84 48.86 42.93 39.98

HTM 37.09 43.95 33.20 33.14 36.08 36.30 42.57

Smt I Smt II Smt I Smt II Smt I Smt II Smt I BUKU 1 2013 2013 2014 2014 2015 2015 2016

Trading 3.65 1.38 3.09 0.83 5.87 6.34 0.58

AFS 55.04 43.98 32.56 32.16 29.44 29.28 24.95

HTM 41.31 54.64 64.35 67.01 64.69 64.38 74.46

Smt I Smt II Smt I Smt II Smt I Smt II Smt I Industry 2013 2013 2014 2014 2015 2015 2016

Trading 9.96 6.08 9.39 8.06 8.75 8.93 8.85

AFS 61.84 67.45 62.94 62.16 60.45 58.18 58.35

HTM 28.20 26.47 27.67 29.77 30.80 32.88 32.81

Source: Bank Indonesia

Banking industry foreign loans are classified based In June 2016, total outstanding foreign loans in on maturity, consisting of short-term foreign loans the banking industry stood at USD30.27 billion, (of up to one year) and long-term foreign loans with relatively stable interest rates but growth (of more than one year). Banking industry foreign decelerating from 2.35% (yoy) last period to loans can originate from an affiliated party, namely contract by -5.06%. The share of banking industry the parent company or business group, or from a foreign loans accounted for 18.34% of private non-affiliated party. Affiliated loans are usually sector foreign loans and 9.35% of total outstanding approved with more attractive terms and lower foreign loans in Indonesia. By borrower, National interest rates than non-affiliated loans. Pursuant Private Banks maintained the largest position of to prevailing regulations, however, banks are only foreign loans, totalling USD15.61 billion (51.57%), permitted to maintain short-term foreign loans to a followed by joint venture banks with USD7.06 maximum of 30% of bank capital. billion (23.33%), state-owned banks with USD5 billion (16.53%) and foreign bank branches with USD2.60 billion (8.57%).

120 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 4.35 Growth of Banking Industry Foreign Loans Graph 4.36 Foreign Loans in Indonesia

Million USD Million USD Million USD 35,000 40,00 180,000 350,000 35,00 30,000 160,000 300,000 30,00 140,000 250,000 25,000 25,00 120,000 200,000 20,000 20,00 15,00 100,000 15,000 10,00 150,000 80,000 10,000 5,00 0,00 60,000 100,000 5,000 -5,00 40,000 - -10,00 50,000 Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I 20,000 1* 2* 1** - - 2011 2012 2013 2014 2015 2016 Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Sem II Sem I Banking Industry Foreign Loans Growth of Banking 1* 2* 1** Industry Foreign Loans 2011 2012 2013 2014 2015 2016 (yoy) Government and Central Bank Private Total (rhs)

Graph 4.37 Foreign Loans by Borrower Graph 4.38 Private Foreign Loans

Million USD Million USD 18,000 180,000 16,000 160,000 14,000 140,000 12,000 120,000 10,000 100,000 8,000 80,000 6,000 60,000 4,000 40.000 2,000 20.000 0 0 SMT 1 SMT 2 SMT 1 SMT 2 SMT 1 SMT 2 SMT 1 SMT 2 SMT 1* SMT 2** SMT 1** SMT 1 SMT 2 SMT 1 SMT 2 SMT 1 SMT 2 SMT 1 SMT 2 SMT 1*

2011 2012 2013 2014* 2015 2016 SMT 2** SMT 1** 2011 2012 2013 2014* 2015 2015 State- Private Foreign Private Private Owned Joint National Banks Nonbanks Banks Venture Source: Bank Indonesia, processed Source: Bank Indonesia, processed

Graph 4.39 Maturity Profile of Long-Term Foreign Loans in the Graph 4.40 Maturity Composition of Long-Term Foreign Loans Year Banking Industry 0.92% 2.70% 2025 3,346.91

2024 15.12 3.26% 2025 12.91% 2023 114.53 2017 26.80% 2018 2021 336.93 2016 407.18 2020 19.95% 2019 2019 1,612.04 2020 2021 2018 2,044.96 23.86% 2023 2017 2024 2,978.92 16.38%

2016 1,629.86

Position per Position per 2,000 4,000 June 2016 June 2016 USD, Millions Source: Bank Indonesia, processed Source: Statistics Department, Bank Indonesia (DSta)

Based on maturity, foreign loans of less than banking industry currently stand at USD20 billion, three years dominated the banking industry, thus which is adequate for the banks to meet their triggering the risk of default in the near term. obligations in the form of mature foreign loans Nonetheless, foreign currency liquid assets in the from 2016 to 2019, totalling USD8.3 billion.

121 FINANCIAL STABILITY REVIEW

Bank Indonesia will continue to monitor foreign Graph 4.41 Return on Assets (ROA) by Bank Group (%)

loan developments, particularly in the private (%) sector. Such surveillance aims to mitigate potential 4.50 4.00 risks that could trigger macroeconomic instability 3.50 as well as promote the optimal role of foreign loans 3.00 2.50 2.31% to support development financing. 2.00

1.50 1.00

4.1.5. Profitability, Efficiency and Capital 0.50

0.00 Profitability 2014 - I 2014 - II 2015 - I 2015 - II 2016 - I Buku 1 Buku 2 Buku 3 Buku 4 Industry

The banks maintained profitability, evidenced by Source: SIP, processed only a slight decline in the return on assets (ROA) Table 4.18 NIM by Bank Group from 2.32% in the second semester of 2015 to 2014 2015 2016 Bank Group 2.31% in the reporting period. The stable ROA I II I II I against a backdrop of slower credit growth, as the BUKU 1 6.19 6.27 6.06 6.28 5.18 main source of bank income, and rising costs of BUKU 2 5.44 5.27 4.93 5.05 4.61 BUKU 3 4.49 4.52 4.29 4.43 5.02

reserves due to deteriorating credit quality (higher BUKU 4 6.35 6.28 6.18 6.29 6.51

NPL), was attributed to a higher net interest margin Industry 5.49 5.46 5.27 5.40 5.61

(NIM). A wider interest rate spread was the result Source: Bank Indonesia, Monthly Commercial Bank reports, processed of a deeper reduction to deposit rates than lending rates (in line with OJK capping policy and the lower for 77.12% of the total. Interest income from BI Rate). Furthermore, the wider interest rate securities and loans increased respectively by spread increased the net interest margin (NIM) at 23.69% and 2.07% on the previous period, while BUKU 3 and 4 banks. interest income from placements at Bank Indonesia contracted by 18.37%. Non-interest operating By bank group, BUKU 4 banks contributed to the income climbed 10.45% on the previous period, lower return on assets (ROA), contrasting the with provisions for impairment losses as the main higher ROA reported by BUKU 1, 2 and 3 banks. Net contributor. Fee-based income was observed to rise profit after tax in the first semester of 2016 stood 5.39%, accounting for 23.74% of total non-interest at Rp54.62 trillion, down slightly from the Rp53.83 operating income. trillion posted in the previous period. BUKU 2 and 3 banks recorded an increase in profit, while BUKU Interest operating expenses also increased, rising 1 and 4 banks experienced a decline due to higher 2.04% on the previous semester, dominated by cost reserves in line with rising non-performing expenses to a third party (51.79%), while operating loans (NPL). expenses excluding interest increased by 8.91%, dominated by provisions for impairment losses In terms of income, interest operating income grew (27.79%), followed by spot and derivatives (25.31%) 2.80% on the previous semester, with securities and payroll (22.05%). and lending as the main contributors, accounting

122 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 4.19 Banking Industry Profit/Loss (Rp, trillions)

Profit Before Tax Profit After Tax

Group 2014 2015 2016 2014 2015 2016

I II I II I I II I II I

BUKU 1 1.40 1.07 1.46 1.63 1.52 1.10 0.52 1.15 1.12 1.10

BUKU 2 8.76 7.05 7.12 6.41 8.61 7.06 4.76 5.29 4.72 6.58

BUKU 3 21.79 16.04 15.65 11.72 18.71 17.20 12.22 12.03 8.80 14.46

BUKU 4 41.52 45.94 40.16 49.28 41.05 33.07 36.23 32.38 39.20 32.47

Industry 73.47 70.11 64.39 69.04 69.89 58.43 53.72 50.84 52.83 54.62

Source: Bank Indonesia, Monthly Commercial Bank reports, processed (including Islamic banks) Note: P/L in semester II is the P/L data at yearend subtracted by P/L in semester I.

Table 4.20 Breakdown of Income Accounts

2014 2015 2016 Income Account Share I II I II I

Interest Operating Income 268.96 299.03 316.32 329.82 339.06 100%

Placements at Bank Indonesia 3.27 4.55 3.99 3.63 2.97 1%

Bonds 17.32 19.89 22.06 20.68 25.58 7.54%

Credit 193.30 210.60 219.53 231.10 235.89 69.57%

Non-Interest Operating Income 80.22 68.21 93.94 116.90 129.11 100%

Bond Sales 3.24 3.07 3.40 2.19 4.75 4%

Trading (Spot and Derivatives) 30.94 19.81 39.72 67.96 63.15 49%

Dividends, Commissions/Provisions/Fees 26.67 27.54 28.77 29.09 30.66 24%

Correction to Provisions for Impairment 13.38 9.61 15.79 8.13 23.05 18% Losses

Non-Operating Income 12.82 12.41 12.15 11.93 7.85 100%

Source: Bank Indonesia, Monthly Commercial Bank reports, processed

Table 4.21 Breakdown of Expense Accounts

2014 2015 2016 Expense Account Share I II I II I

Interest Operating Expense 136.06 157.78 168.99 169.02 172.46 100%

To Another Party 2.24 2.37 2.96 3.52 3.57 2%

To a Third Party (Nonbank) 79.56 93.37 94.76 92.31 89.31 52%

Bonds 3.51 3.49 3.92 4.04 3.83 2%

Loans Received 1.76 1.75 1.91 2.43 3.44 2%

Operating Expenses Excluding Interest 138.92 139.92 177.46 208.41 226.98 100%

Bond Losses 1.66 0.92 1.39 1.46 0.75 0.3%

Spot and Derivatives 27.18 16.70 35.92 62.19 57.46 25%

Insurance Premiums 4.76 5.13 5.82 6.11 6.50 3%

Provisions for Impairment Losses 27.38 27.70 44.44 42.22 63.08 28%

Payroll 39.62 41.13 45.20 44.08 50.05 22%

Non-Operating Expenses 13.56 11.83 11.57 12.18 6.70 100%

Source: Bank Indonesia, Monthly Commercial Bank reports, processed

123 FINANCIAL STABILITY REVIEW

Efficiency Efficiency was noted to decline despite the cost- Banking industry efficiency was observed to decline to-income ratio (CIR), as the ratio of operating in the reporting period, reflecting an increase in the expenses excluding interest to income, falling from BOPO efficiency ratio from 81.49% to 82.23%. BUKU 59.47% to 56.20%. The lower CIR was attributed to 1 and 4 banks confirmed a higher BOPO efficiency net interest income, for which growth outstripped ratio due to an increase in interest operating operating expenses excluding interest. Contrasting expenses, namely loans received, expenses to CIR and BOPO trends indicated that lower bank another bank as well as overheads in the form of efficiency was the result of business activities in provisions for impairment losses (typically higher the form of interest. in the first semester) and payroll. The share of interest operating expenses in the form of loans Capital received and interest expenses to another bank The banking industry maintained adequate capital, remained comparatively small in terms of total evidenced by a solid Capital Adequacy Ratio (CAR) operating expenses. that increased from 21.39% to 22.56% in the reporting period, which is well above the minimum Graph 4.42 BOPO Efficiency Ratio by Bank Group (%) threshold. Slower credit growth helped drive the (%) higher level of CAR as the banks implemented 100 90 more prudent lending against a backdrop of 80 82,23 70 economic moderation, thereby curbing growth of 60 50 40 risk-weighted assets (RWA). The high level of CAR 30 20 maintained in Indonesia helped the banking sector 10 0 meet the Basel III capital requirements, including 2014 - I 2014 - II 2015 - I 2015 - II 2016 - I the capital conservation buffer, countercyclical Buku 1 Buku 2 Buku 3 Buku 4 Industry

Source: Indonesian Banking Statistics, processed (excluding Islamic banks) capital buffer and capital surcharge for systemically important banks, which became effective at the Graph 4.43 CIR Ratio by Bank Group (%) beginning of 2016. In terms of composition, bank (%) 80 capital was again dominated by core capital (Tier 70 60 1), accounting for 88.83% of the total. 50 56,20 40 30 4.1.6. Banking Stress Tests 20 10 Stress tests were conducted to measure the 0 2014 - I 2014 - II 2015 - I 2015 - II 2016 - I resilience of bank capital (CAR) as an industry and

Buku 1 Buku 2 Buku 3 Buku 4 Industry by BUKU bank group. Stress tests were performed Source: Indonesian Banking Statistics, processed (excluding Islamic banks) using macroeconomic scenarios transmitted to credit risk and market risk (interest rates, exchange

124 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 4.44 Bank CAR (%) Graph 4.45 Ratio of Tier 1 Capital (%)

(Rp, Billions) (%) 4,500 23.00 22.50 4,000 22.56 22.00 24.00 22.56 3,500 21.50 22.00 3,000 21.00 20.00 20.04 2,500 20.50 18.00 2,000 20.00 16.00 19.50 1,500 14.00 19.00 12.00 1,000 18.50 10.00 500 18.00 - 17.50 2014-I 2015-I 2016-I 2014 - I 2014 - II 2015 - I 2015 - II 2016 - I 2014-II 2015-II

Capital Risk-Weighted Assets CAR CAR Tier 1 Source: Bank Indonesia, processed Source: Bank Indonesia, processed

Table 4.22 CAR by Bank Group

CAR tertinggi CAR terendah CAR rata-rata CAR

% 2014 2015 2016 2014 2015 2016 2014 2015 2016 2014 2015 2016

I II I II I I II I II I I II I II I I II I II I

BUKU 1 215.19 93.51 145.53 142.94 116.85 10.43 10.19 10.02 8.98 11.29 28.34 22.25 25.28 29.42 24.70 18.97 17.64 19.86 23.24 20.87

BUKU 2 88.71 68.01 61.48 121.23 138.42 12.81 10.68 12.11 14.67 11.65 24.78 23.87 22.53 26.23 28.22 21.41 20.91 19.96 22.40 22.35

BUKU 3 78.28 78.01 77.04 80.56 84.09 12.25 13.55 13.56 14.20 11.98 21.29 21.25 21.56 22.76 23.79 21.45 21.78 22.35 23.50 24.58

BUKU 4 18.63 17.89 20.16 20.16 21.79 15.85 16.59 17.23 18.61 19.26 17.01 17.08 18.66 19.29 20.89 17.01 17.12 18.78 19.26 21.06

Industry 19.45 19.57 20.28 21.39 22.56

Source: Bank Indonesia, processed rates and SBN prices) using balance sheet and Once all the external and domestic risks that financial performance data per June 2016. threaten the banking system have been considered, three risk scenarios are determined: (i) baseline Macroeconomic Scenarios (BL); (ii) v-shaped shock; and (iii) prolonged slow Prior to running the stress tests, several stress growth (PSG). The baseline scenario represents scenarios were created, which require knowledge the preliminary projection, assuming no imminent, of the exogenous risks (sources of shocks) that adverse economic shock. In other words, normal threaten the banking system. On the bank balance economic growth, without price (inflation) and sheet, such risks are reflected in the form of exchange rate disruptions. The BL scenario is credit risk, interest rate risk, currency risk and required as a benchmark for the stress tests. SBN price risk. The exogenous sources of risk can originate internationally/externally, including According to the v-shaped shock (VS) scenario, global commodity prices and global GDP growth, a significant economic shock is assumed to and/or domestically, such as inflation and weaker occur along with financial system instability. corporate performance. Notwithstanding the shock, however, a relatively rapid economic recovery persists. This scenario was

125 FINANCIAL STABILITY REVIEW

adopted in light of the 1998 crisis, when economic to 5.5% in 2017 and to 6.4% in 2018. The gradual growth, inflation and the exchange rate recovered but sustained NPL increase is congruent with the quickly after experiencing negative GDP growth. scenario of prolonged economic moderation. The VS scenario showed that industry NPL would rise The final scenario, namely PSG, assumes a significantly at the end of 2017 to 9.6% due to a prolonged global economic contraction, thus dramatic shock in the economy. Nevertheless, the hampering the recovery in Indonesia compared VS scenario assumes rapid economic recovery, to the VS scenario. The PSG scenario is based on therefore, industry NPL returns to 4.4% by the end the latest global economic developments, such as of 2018. The higher NPL would increase provisions the crisis in Europe, from which a rapid recovery for impairment losses, thus eroding profitability cannot be expected. and, ultimately, undermine CAR momentum.

Each scenario is tested using a structural model to Transmission of SBN Risk capture the interactions of domestic and external The transmission of SBN risk occurs through the shocks. The structural model then produces securities price channel on the bank assets side. variables as the main components of the scenario The assets experiencing shocks are available for stress tests, namely GDP growth, inflation and sale (AFS) and trading government securities the exchange rate for the upcoming three years (SBN), which are vulnerable to the risk of loss due (yearend 2018). a lower marked-to-market value. Lower AFS and trading SBN prices are based on shifts in the IDMA Transmission of Credit Risk index for each scenario. Under the BL scenario, Credit risk is calculated, using non-performing the IDMA index improves 10bps in 2016 and is loans (NPL) as a proxy, to test bank CAR resilience then stable until the end of 2018. According to the to economic moderation and its impact on gross PSG scenario, the IDMA index gradually declines NPL. According to the BL scenario, bank NPL will by 17bps in 2017 and 17bps in 2018. Per the VS remain stable and well below the 5% threshold at scenario, however, the IDMA index falls 18bps in the end of 2018 in line with economic stability. Per 2017 but then rebounds by 4bps in 2018. A lower the PSG scenario, however, industry NPL would rise SBN value based on the IDMA index would incur

Graph 4.46 Return on Assets (ROA) by Bank Group (%) Graph 4.47 Market Risk Scenario (SBN Prices)

(%) (bps) 12 BL PSG VS 15 BL PSG VS 10.08 9.6 10 10 5

8 0 6.4 -0.05 4.39 -2.13 5.5 -5 -1.55 6 4.4 -10 4 3.0 3.1 -15 2.8 2.8 2.8 -16.85 -20 -17.39 -18.42 2 -25 -24.89 0 -30 Q4 2016 Q4 2017 Q4 2018 Q4 2016 Q4 2017 Q4 2018

126 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

a cost to correct asset prices on the profit/loss to the BS scenario, interest rates are assumed to account, which would ultimately impact the Capital remain stable, thus avoiding additional risk on the Adequacy Ratio (CAR). balance sheet. Per the PSG scenario, interest rates would increase 500bps in 2016, 625bps in 2017 Transmission of Currency Risk and 125bps in 2018, totalling 1250bps over three Bank exposure to currency risk manifests on- years. Under the VS scenario, interest rates would balance sheet and off-balance sheet in terms of increase 1275bps in the first two years (yearend the net open position (NOP). Per the BL scenario, 2017) before finally decreasing 675bps in 2018. the exchange rate remains stable in line with solid Banks with a positive maturity gap on the balance economic fundamentals. According to the PSG sheet would profit from higher interest rates. In scenario, the rupiah depreciates gradually to its contrast, banks with a negative maturity gap would nadir at the end of 2018 with an index of 199. With incur losses, thus undermining CAR. the VS scenario, the rupiah depreciates sharply during the first two years, reaching a low point at Results of Aggregate Stress Tests the end of 2017 with an index of 177. Nonetheless, Using dynamic stress test scenarios, the impact of the economic recovery prompts an improvement in the various shocks from each respective scenario on the index to 162 at the end of 2018. If deep rupiah the banking system was tested periodically until the depreciation is experienced, banks maintaining a end of 2018. Based on the tests, the results showed net long position would benefit from the difference that the national banking industry is adequately in exchange rates. Conversely, banks with a net resilient, reflected in a CAR that remains well above short position would incur losses, thus undermining the 8% threshold until the end of the projection CAR. period (Q4/2018) for each scenario.

Graph 4.48 Currency Risk Scenarios Graph 4.49 Interest Rate Risk Scenarios

USD/IDR Index (bps) (2015=100) 1000 900 BL PSG VS 250 625 500 500 162 375 200 177 199 160 125 0 0 0 150 170 0 100 126 100 104 104 101 -500 50 -675

Q4 2016 Q4 2017 Q4 2018 - -1000 Q4 2016 Q4 2017 Q4 2018 BL PSG VS

Transmission of Interest Rate Risk Based on risk, credit risk dominated the losses Bank exposure to the risk of higher interest rates incurred according to both scenarios. Under the is measured by the exposure of short-term (less PSG scenario, credit risk contributed 81% of the than one year) rupiah-denominated net assets and total losses, compared to 93% per the VS scenario. liabilities based on the maturity profile. According

127 FINANCIAL STABILITY REVIEW

Graph 4.50 Results of the Aggregate Stress Tests

(%) (%) 25 100 1% 5% 6% 21.6 21.6 21.5 21.7 21.7 14% 20.6 19.7 3,1 19.0 19.1 80 20

60 15 40 10 20

5 0 PSV VS 0 -20 Q4 2016 Q4 2017 Q4 2018 Credit Interest Rates Exchange SBN BL PSG VS Rates

Results of Stress Tests by Bank Group (yearend 2017), BUKU 3 banks experience the Under the PSG scenario, all BUKU bank groups largest CAR decline, falling 3.40 points to 19.9%, maintained a level of CAR beyond the 8% threshold. followed by BUKU 2 banks, dropping 3.01 points to Nonetheless, BUKU 1 and 2 banks recorded the most 14.3%. Furthermore, BUKU 2 banks were shown notable CAR decline by the end of 2018, falling 3.56 to have the lowest CAR after experiencing distress. points and 2.69 points respectively to 16.7% and In general, however, the VS scenario stress tests 15.4%. Furthermore, BUKU 2 banks were shown to showed that all BUKU bank groups would maintain have the lowest CAR after experiencing distress. In a solid capital base despite intense economic general, however, all bank groups maintained an pressures. In the third year (yearend 2018), all adequate level of capital under this scenario but BUKU bank groups begin to recover, reflected by several small banks required a capital injection in increases in CAR by group. the case of a prolonged economic slowdown. As per both the PSG and VS scenarios, credit risk According to the VS scenario, the stress tests showed continued to dominate nearly every BUKU bank that all bank groups maintained a solid capital base group, indicating that credit risk remains the in the face of significant pressures, reflecting a primary source of potential risk in the banking level of CAR well above the 8% threshold for each system. BUKU group. At the peak of the economic pressures

Graph 4.51 Stress Tests by Bank Group (PSG Scenario) Graph 4.52. Stress Tests by Bank Group (VS Scenario) (%) (%) 25 23.4 25 23.3 21.9 21.721.3 20.3 22.0 20.8 20.6 19.9 19.9 20.120.1 18.0 20 17.7 20 18.8 17.1 16.7 16.0 17.3 16.4 15.2 15.4 14.3 15 15

10 10

5 5

0 0 BUKU 1 BUKU 2 BUKU 3 BUKU 4 BUKU 1 BUKU 2 BUKU 3 BUKU 4 Q4 2016 Q4 2017 Q4 2018 Q4 2016 Q4 2017 Q4 2018

128 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

An increase of interconnectedness between banks 4.2. The Nonbank Financial Industry and finance companies was observed as banks extended loans to finance companies. In contrast, The nonbank financial industry2 performed soundly interconnectedness between the banking sector and in the first semester of 2016. Finance companies insurance industry decreased as placements at banks reported slight performance gains as financing declined. growth accelerated after declining consistently since the second semester of 2013. An increase of finance 4.2.1. Finance Companies company funding supported the performance gains. Finance company financing increased 0.81% (yoy) in Although non-performing financing (NPF) remained the first semester of 2016, with consumer financing below the maximum threshold, a significant NPF bump remaining dominant, accounting for 70.04% of the during the reporting period demanded vigilance. total, followed by leasing (26.86%), factoring (3.06%) The increase in financing boosted finance company and credit cards (0.03%). By sector, the others sector profitability, albeit limitedly. Meanwhile, exposure to (primarily automotive financing) tended to dominate foreign currency risk decreased as finance companies finance company financing with a 48.64% share, were inclined to reduce external debt. down from 50.32% in the second semester of 2015. The smaller share was in line with weaker automotive The insurance industry also gained momentum, with sales data, falling from 3,305,993 units3 sold in the assets and investment accelerating on the previous second semester of 2015 to 2,962,888 units in the first period. Stronger performance was supported by less semester of 2016. business risk, indicated by an increase in the ratio of premiums to claims.

Graph 4.53 Finance Company Assets and Financing Graph 4.54 Finance Company Financing by Business Activity

(Rp Trilion) (Rp Trilion) 500 400 350 400 434 300 430 426 401 413 420 223 237 246 249 247 261 366 370 250 300 348 361 363 373 200 200 150 8 8 9 10 11 100 11 100 50 117 116 111 111 105 100 - Dec-13 Jun-14 Dec-14 Jun-15 Dec-15 Jun-16 Dec-13 Jun-14 Dec-14 Jun-15 Dec-15 Jun-16

Assets Financing Leasing Consumer Financing Factoring Credit Cards

Source: Bank Indonesia Source: Bank Indonesia

2 In this case, the nonbank financial industry includes finance companies and insurance 3 Source: www.gaikindo.or.id

129 FINANCIAL STABILITY REVIEW No. 27, September 2016

Financing volume at finance companies tended to Despite comparatively stable financing growth, credit remain stable despite the leasing business contracting risk at finance companies tended to increase in all by -9.68% (yoy) due to lower commodity prices, sectors, reflecting an increase in the NPF of finance including coal and crude palm oil (CPO), while companies from 1.45% to 2.20%. Non-performing leasing to the mining sector (including financing financing (NPF) increased most significantly in the heavy equipment) accounted for 10.88%. Consumer transportation sector, for which most financing objects financing accelerated from just 0.51% (yoy) in the were ships and trucks used to transport mining second semester of 2015 to 4.80% in the reporting commodities. Potential further increases to NPF period. Such conditions are congruent with household demand careful monitoring if the economic downturn consumption, which posted growth of 8.06% (yoy) in persists. Based on the results of simulations5, finance the first semester of 2016.4 Meanwhile, factoring and company profitability would only survive an increase of credit cards grew respectively at 17.5% and 150.06% NPF to 4.48%, assuming all current loans (collectability but the share of both remained negligible. of 1) would become doubtful (collectability of 2).

Foreign currency financing experienced negative Graph 4.56 Rasio NPF PP (%) growth of 12.42% (yoy) in the first semester of 2016, % NPF (%) 3 deteriorating from -5.31% (yoy) in the previous 2.5 2.20 semester and -9.52% (yoy) one year earlier. In contrast, 2

1.5 1.45 rupiah financing achieved 3.15% (yoy) growth in the 1.44 1 first semester, up from 0% in the previous period but 0.5 down from 4.94% in the first semester of 2015. The 0 portion of rupiah financing remained relatively stable, Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-12 Sep-13 Sep-14 Sep-15 Dec-12 Dec-13 Dec-14 Dec-15 Mar-12 Mar-13 Mar-14 Mar-15 Mar-16 increasing modestly from 85.57% to 86.97% of total Source: Bank Indonesia financing.

The total funding of finance companies grew by 1.17% Graph 4.55 Financing by Currency

(Rp Trilion) (yoy) in the reporting period, up from 0.07% (yoy) in the 400 second semester of 2015. Funding from domestic loans 55 55 52 49 64 61 300 was the main contributor, growing 8.13% (yoy) due to lower lending rates offered by finance companies to 200 324 300 311 314 311 285 the banking sector. Meanwhile, finance companies 100 were inclined to reduce their external debt burden. 0 Jun-13 Dec-13 Jun-14 Dec-14 Jun-15 Jun-16 Accordingly, external debt at finance companies Rupiah Foreign Currency Source: Bank Indonesia declined 21.36% (yoy) in the first semester of 2016, compared to a 6.24% decline in the previous period.

4 Source: Bank Indonesia GDP report, data per Q2/2016. 5 Using profit and loss data of finance companies per June 2016.

130 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Despite the decline, the portion of external debt Rp26.94 trillion. Most financing at the eight companies remained large at 26.83% because of relatively higher was denominated in rupiah, amounting to Rp86.02 rupiah lending rates than the rates available on foreign trillion, while foreign currency financing totalled just currency loans. At the end of the first semester of Rp2.42 trillion. Consequently, finance companies were 2016, 25% of finance company financing in the banking exposed to currency risk, which was mitigated through sector was approved with an interest rate of < 10%, up hedging. To that end, risk mitigation has also alleviated from 22.73% in the previous period. In contrast, an contagion risk from potential default on the foreign interest rate of > 10% was applied to around 75% of currency financing by finance companies at banks as loans from domestic banks, which raised the cost of the parent company. funds at finance companies considerably (Graph 4.59). Finance companies became more efficient, reflected As of June 2016, a total of 42 finance companies by a BOPO efficiency ratio that improved from 85.35% were indebted to the tune of Rp95.35 trillion. Of in the second semester of 2015 and 84.87% in the first the 42 finance companies, banks had a 25%-99% semester of 2015 to 82.71% in the reporting period. shareholding in eight. The total outstanding external Finance company profitability was relatively stable. The debt of the eight finance companies was recorded at return on assets (ROA) increased to 3.64% in the first

Graph 4.57 Funding and Financing Growth Graph 4.58 Sources of Funds

% (Rp Triliun) 20 400 351 355 338 345 346 350 329 37 39 40 47 15 300 33 35 53 51 53 56 61 67 250 10 200 101 109 114 121 107 95 5 150 1,17 100 142 142 141 136 138 147 0 (0,81 50 - -5 Des-13 Jun-14 Des-14 Jun-15 Des-15 Jun-16 Jun-14 Jun-15 Jun-16

Sep-14 Sep-15 Domestic Loans Offshore Loans Dec-13 Dec-14 Dec-15

Mar-14 Mar-15 Mar-16 Securities Total Funding Total Financing Capital Total Funding

Source: Bank Indonesia Source: Bank Indonesia

Graph 4.59 Share of FC Financing based on Lending Rate

% 60

50 46.43

40

30 28.57

20 25.00

10 Jun-13 Jun-14 Jun-15 Jun-15 Sep-12 Sep-13 Sep-14 Sep-15 Dec-13 Dec-14 Dec-15 Dec-12 Mar-13 Mar-14 Mar-15 Mar-15

<10% 10%-12% >12% Source: Bank Indonesia

131 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 4.60 External Debt at Finance Companies % % 40 40 35 28.40 30 30 20 25 10 20 - 15 (21.35) 10 (10) (20) 5 - (30) Jun-14 Jun-15 Jun-16 Sep-14 Sep-15 Dec-13 Dec-14 Dec-15 Mar-14 Mar-15 Mar-16

Portion of External Debt to Total Liabilities (%) Annual Growth of External Debt (rhs)

Source: Bank Indonesia

semester of 2016 from 3.32% in the second semester Greater bank lending to finance companies increased of 2015 and 3.43% one year earlier. Nevertheless, the interconnectedness between the two sectors in return on equity (ROE) declined slightly to 11.14% from the first semester of 2016. Bank lending to finance 11.49% and 12.53% respectively over the same period. companies accelerated to 8.76% (yoy) in the first semester of 2016, contrasting the 2.65% (yoy) decline Finance companies would be adequately resilient to in the previous period. Meanwhile, finance company rupiah depreciation per the results of simulations placements in the banking sector in the form of involving 30 finance companies with Net Foreign deposits (demand deposits, savings deposits and term Liabilities (NFL)6 and rupiah depreciation to Rp18,000 deposits) increased 37.30%, reversing the previous per USD. The simulations showed that seven finance 2.04% decrease. companies would experience negative equity, with 4.2.2. Insurance Companies two of the seven already in a current state of negative Total assets of the insurance industry increased 12.19% equity. (yoy) in the reporting period, accelerating from 6.39% Graph 4.61 ROA, ROE and BOPO of Finance Companies (yoy) in the second semester of 2015. In addition, the % % investment volume of the insurance industry grew 25 88 86 at 13.42% (yoy), increasing from 5.11% (yoy) in the 20 82.71 84 previous period, thereby raising the ratio of insurance 15 82 11.14 80 investments to 80.89%. 10 78 76 5 3.64 74 - 72 At the end of the reporting period, a total of 148

Jun-14 Jun-15 Jun-16 insurance companies were registered in Indonesia, Sep-14 Sep-15 Dec-13 Dec-14 Dec-15 Mar-14 Mar-15 Mar-16

ROA ROE BOPO consisting of insurance and reinsurance companies Source: Bank Indonesia with assets totalling Rp872.02 trillion. Most insurers

6 Net Foreign Liabilities (NFL) = foreign currency liabilities > foreign currency assets

132 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 4.23 Bank Interconnectedness with the Finance Industry

Component Dec-14 Jun-15 Dec-15 Jun-16 ∆ yoy % yoy Investments (Rp, billions) 26,811 23,340 25,531 24,801 1,460 6.26 Term, Demand & Savings Deposits 15,824 13,793 15,501 18,938 5,144 37.30 Spot and Derivatives 4,235 6,871 7,405 3,409 (3,462) (50.39) Banker’s Acceptances - - - - - 0.00 Securities Held by Finance Companies 4,644 453 447 156 (298) (65.66) Disbursed Loans 2,035 2,125 2,136 2,279 154 7.25 Loan Capital 73 99 41 20 (79) (79.75) Liabilities (Rp, billions) 126,356 122,915 123,012 133,685 10,770 8.76 Bank Debt 103,766 99,636 97,994 107,348 7,712 7.74 Spot and Derivatives 2,593 2,059 1,896 1,420 (639) (31.05) Securities Issued by Finance Companies 11,775 12,633 14,370 15,970 3,337 26.42 Banker’s Acceptances 5 35 2 - (35) (100.00) Investments from Banks 8,217 8,552 8,750 8,948 395 4.62

Source: Monthly Commercial Bank Reports were owned by private nationals and not listed on represent state-owned enterprises that are obliged to the Indonesia Stock Exchange. The total assets of the allocate assets to government securities (SBN), hence insurance industry were dominated by 54 life insurers elevating their investment ratios. with a 41.65% share, followed by two social insurance companies (29.07%), 89 general and reinsurance Business risk eased in the insurance industry, reflected companies (15.99%), as well as three compulsory by a bump in the gross claims to gross premiums ratio insurance companies (13.29%). to 155.74% in the first semester of 2016 from 145.14% in the second semester of 2015 and 140.17% one year All insurance subsectors improved in the reporting earlier. Less risk affected all insurance types, excluding period, including life insurance, general insurance and compulsory insurance as the increase in claims was not reinsurance, social insurance as well as compulsory offset by a corresponding increase of premium income. insurance. The most significant increase of investment Meanwhile, liquidity risk in the insurance industry was ratio was achieved by compulsory insurance, which relatively well mitigated, reflecting a current assets7 to

Graph 4.62 Insurance Industry Asset Share Graph 4.63 Insurance Industry Assets and Investments

(Rp Trillion) % 1.000 90 13.29% 900 82.83 81.94 85 800 80.77 80.02 79.79 80.89 78.22 80 872 700 755 777 804 600 692 705 75 41.65% 615 616 610 622 641 29.07% 500 542 70 509 505 400 65 300 60 200 15.99% 100 55 - 50 Life Insurance General and Reinsurance Jun-13 Dec-13 Jun-14 Dec-14 Jun-15 Des-15 Jun-16 Compulsory Insurance Social Insurance Assets Investments Ratio (rhs) Source: Financial Services Authority (OJK) Source: Financial Services Authority (OJK)

7 Current Assets = Total Assets – Strata Title Buildings or Land with Buildings for Own Use – Other Fixed Assets – Other Assets

133 FINANCIAL STABILITY REVIEW No. 27, September 2016

reporting period. At the end of the first semester of Table 4.24 Interconnectedness between the Banking Sector and Insurance Industry 2016, insurance placements in the banking industry Component Jun-15 Dec-15 Jun-16 declined 5.27% (yoy) or Rp7.62 trillion, contrasting Assets 328.00 329.68 363.16 Investments 280.18 283.20 313.02 Investment/Assets Ratio (rhs) 85.42 85.90 86.19 Graph 4.65. Insurance Indicators

1.400 3.00% General Insurance and Jun-15 Dec-15 Jun-16 Reinsurance (Rp T) 1.200 Assets 127.26 132.56 139.41 1.000 Investments 63.16 66.15 68.16 2.00% Investment/Assets Ratio (rhs) 49.63 49.90 48.89 800

600 Social Insurance (Rp T) Jun-15 Dec-15 Jun-16 1.00% Assets 217.65 233.61 253.52 400 Investments 204.55 215.33 235.83 200 Investment/Assets Ratio (rhs) 93.98 92.18 93.02 - 0.00% 2011 2012 2013 2014 2015 Compulsory Insurance (Rp T) Jun-15 Dec-15 Jun-16 Gross Premiums Assets 104.38 107.86 115.93 (Trillion Rp) Densitas (Rp Rb) Penetrasi (Rp Rb) Investments 74.03 76.62 88.36 *) Gross premiums represent annualised premiums in December 2015 Investment/Assets Ratio (rhs) 70.92 71.03 76.62 *) GDP as of December 2015 Penetration = Gross Premium/GDP Source : Monthly Commercial Bank Reports Density = Gross Premium/Total Population

Source: Financial Services Authority (OJK), Bank Indonesia, processed current liabilities8 ratio of more than 1, namely 1.69. Insurance industry reliance on external debt remained the previous positive growth of 12.80%. The insurance low, accounting for just 0.02% or USD68 million of industry reduced placements in the banking sector the total in the form of premium debt, claim debt, pursuant to OJK regulations requiring SBN investments. reinsurance debt, retrocession debt (reinsurance) and Meanwhile, bank placements in the insurance industry commission debt. recorded growth of 74.12% (yoy), down slightly from the 75.12% (yoy) posted in the previous semester. By In general, interconnectedness between the banking bank group, BUKU 1 banks had the highest degree sector and insurance industry tended to decline in the of interconnectedness with the insurance industry,

Graph 4.64 Gross Premiums and Claims Graph 4.66 Current Assets to Current Liabilities Ratio *) Including the Social Security (Rp Trillion) (%) Rp Trillion Management Agency (BPJS) 1.69 300 180 160.25 900 1.70 155.78 145.14 155.74 148.27 160 800 250 137.74 140.17 700 127.41 140 600 200 120 500 1.60 100 400 150 300 80 200 100 60 100 - 1.50 40 50

20 Jul-15 Jan-16 Jun-15 Jun-16 Oct-15 Feb-16 Apr-16 Sep-15 Dec-15 Nov-15 Mar-16 Aug-15 May-16 - - Dec-12 Jun-13 Dec-13 Jun-14 Dec-14 Jun-15 Dec-13 Jun-16 Current Aset Current Liabilities CA/CL (lhs) Source: Financial Services Authority (OJK) Gross Gross Ratio of Gross Claims to Premiums Claims Gross Premiums (rhs) Source: Financial Services Authority (OJK)

8 Current Liabilities = Total Liabilities

134 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 4.67 Insurance Industry External Debt Graph 4.68 Weighted Average Rupiah Deposit Rate of BUKU 1 Banks Million USD Billion USD % 140 340 323,789 12 120 300 8.39 10 100 250 8 80 68 200 6 60 150 6.14 4 40 100 2 20 50 0 - 0 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Sep-12 Sep-13 Sep-14 Sep-15 Dec-12 Dec-13 Dec-14 Dec-15 Mar-13 Mar-14 Mar-15 Mar-16 Jun-14 Jun-15 Jun-13 Jun-16 Sep-15 Sep-13 Sep-14 Dec-12 Dec-13 Dec-15 Dec-14 Mar-14 Mar-13 Mar-15 Mar-16 Weighted Average Rupiah Deposit Rate for the Insurance Industry Insurance Industry External Debt Total External Debt (rhs) Weighted Average Rupiah Deposit Rate (Total)

Source: Financial Services Authority (OJK), Bank Indonesia, processed Source: Bank Indonesia indicated by an increase of bank deposits and debt at Rp152.45 trillion (21.61%) and term deposits at security holdings by the insurance industry. The share Rp121.87 trillion (17.28%). The insurance industry of insurance industry deposits to total deposits at BUKU increased holdings of tradeable government securities 1 banks reached 7.72%, or 46.13% of total nonbank (SBN) in the reporting period in order to meet prevailing financial industry deposits held at BUKU 1 banks. OJK regulations9. Such conditions were the result of comparatively high interest rates offered by BUKU 1 banks to the insurance The profitability of the life insurance as well as general industry, exceeding the average rupiah deposit rate insurance and reinsurance subsectors decreased in (Graph 4.69). the first semester of 2016, evidenced by declines in ROA and ROE due to more rapid growth of assets and Total assets of the insurance industry increased. capital than profit stemming from lower investment Insurance industry assets were placed in various returns and rising operating costs. investment instruments, mainly government securities totalling Rp188.95 trillion (26.79%), followed by stocks In terms of capital, all public listed insurance companies

Table 4.25 Interconnectedness between the Banking Sector and Insurance Industry

Component Dec-14 Jun-15 Dec-15 Jun-16 ∆ yoy % yoy Investment (Rp, billions) 141,311 144,570 159,394 136,948 (7,622) (5.27) Term, Demand & Savings Deposits 130,407 132,765 147,675 124,626 (8,138) 6.13 Spot and Derivatives - - - - 0 - Banker’s Acceptances - - - - 0 0.00 Securities Held by Finance Companies 6,267 7,269 6,955 6,467 (802) (11.03) Disbursed Loans 514 513 513 512 (1) (0.26) Loan Capital 4,124 4,023 4,251 5,342 1,320 32.81 Liabilities (Rp, billions) 2,661 3,044 4,661 5,301 2,257 74.12 Bank Debt 694 689 537 1,176 487 70.76 Spot and Derivatives - - - 0 0 0.00 Securities Issued by Finance Companies - - - 0 - 0.00 Banker’s Acceptances - - - 0 - 0.00 Investments from Banks 1,967 2,356 4,123 4,125 1,769 75.10

Source : Monthly Commercial Bank Reports

9 OJK Regulation (POJK) No. 1/POJK.05/2016, dated 11th January 2016, concerning SBN Investments.

135 FINANCIAL STABILITY REVIEW No. 27, September 2016

have already met the minimum capital base maintained by the insurance industry is of Rp100 billion. Furthermore, most public listed expected to absorb the potential risks. insurance companies have also satisfied the minimum risk-based capital requirement of 120%. The solid

Table 4.26 Insurance Industry Assets and Financial Performance

Component Jun-15 Dec-15 Jun-16 Growth yoy Growth ytd Total Assets 777,29 803,71 872,02 21.19% (5.27) Total Investments 621,92 641,29 705,36 13.42% 9.99% Term Deposits 141,47 147,44 121,87 -13.85% -17.34 Stocks 139,75 140,21 152,45 9.09% 8.73 Sukuk or Bonds 67,71 71,98 89,04 31.49% 23.69% SBN 146,54 151,19 188,95 28.94% 24.98% SB 1,98 1,28 1,00 -49.55% -22.13% Mutual Funds 100,39 101,94 122,49 22.01% 20.16% Other Assets 24,08 27,25 29,57 22.79% 8.52% Non-Investment Assets 47,82 46,48 50,14 4.86% 7.88% Total Equity 320,49 342,57 369,86 15.40% 7.97% Total Expenses 50,21 96,43 67,64 34.70% -29.86 Profitability Jun-15 Dec-15 Jun-16 ∆ yoy ∆ ytd ROA 2,26 2,45 2,12 (0.14) (0.33) ROE 4,53 4,84 4,21 (0.32) (0.63)

Source: Monthly Commercial Bank Reports

Graph 4.69 Asset Composition of Public Listed Insurance Companies

(Rp Trillion) 800 700 600 500 400 300 200 100 - Jun-15 Dec-15 Jun-16

Term Deposits Stocks Sukuk or Bonds

SBN SB Mutual Funds Other Assets Source: Bank Indonesia

Table 4.27 Capital Adequacy of Public Listed Insurance Companies

Periode ABDA AHAP AmAG ASBI ASDM ASJT ASRM LPGI MREI PNIN ASMI VINS

2016 Tw I 305.64 241.68 123.23 302.53 212.58 160.24 139.25 221.54 252.67 2112.30 191.72 878.32

2015 Tw IV 290.55 216.06 - 130.87 181.43 174.37 329.82 234.31 296.35 - 206.49 913.51

2015 Tw I 226.48 181.50 560.53 82.40 197.52 146.37 437.86 298.17 360.39 - 131.45 -

Source: Bank Indonesia, processed

136 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Deposits 4.3. Islamic Banks Deposit growth accelerated significantly in the reporting period from 6.1% to 13.06%. Total deposits of Islamic Intermediation at Islamic banks tended to be more banks amounted to Rp241.34 trillion at the end of the procyclical than the conventional banking industry, first semester of 2016, thereby accounting for 5.28% of thus Islamic banks were harder hit by the current total deposits in the banking industry. By comparison, economic downturn. After decelerating in 2005/2006, deposit growth at Islamic banks outstripped that of Islamic bank financing took off significantly during conventional banks by 7.56%. 2009/2010 in line with the many additional Islamic banks that opened in pursuance of the Islamic Bank Term deposits continued to dominate Islamic bank Act (No. 21) of 2008. The additional Islamic banks deposits, accounting for 61.02%, but the share has contributed to the target share of 5% of the banking gradually been eroded since the first semester of industry. Nonetheless, financing growth at Islamic 2014. The share of savings products has also declined, banks has decelerated since the middle of 2013 and moderating slightly from 29.7% to 29.11% in the remains low to date. Currently, the market share of reporting period. In contrast, the share of demand the Islamic banking industry has increased slightly to deposits increased from 9.17% to 9.88%. Therefore, 4.81%.

Graph 4.70 Banking Industry Procyclicality

% Syariah % Syariah % Syariah 09-2001 05-2013 07-2013 0.9% 4.5% 3.8%

Expansion 120 followed by 30 slowdown 100 Expansion 30 80 Slowdown 60 15 40

20 20 0

-20 5 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Annual Islamic Financing Growth Annual Conventional Credit Growth NPF (rhs) NPL (rhs)

Source: Financial Services Authority (OJK), Bank Indonesia, processed

137 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 4.71 Asset Share of the Islamic Banking Industry

% MS % Delta 5.20 40 35 5.00 30 25 4.81 4.80 20 15 4.60 10 5 4.40 4.96 20 4.20 15 10 4.00 5 Jul-13 Jul-14 Jul-15 Jan-13 Jan-14 Jan-15 Jan-16 Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Sep-13 Sep-14 Sep-15 Dec-13 Dec-14 Dec-15 Nov-13 Nov-14 Nov-15 Mar-13 Mar-14 Mar-15 Mar-16 Agu-13 Agu-14 Agu-15 May-13 May-14 May-15 May-16

MS Nas (%) S-K Growth Delta Source: Financial Statements of Public Listed Insurance Companies, processed

Graph 4.72 Deposits

RPT % MS 260,00 45

240,00 40

220,00 35 241.34 30 200,00 25 180,00 20 160,00 15 13.06 140,00 10 120,00 5 100,00 0 Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15

Deposits Annual Deposit Growth (%) Source: Bank Indonesia

Graph 4.73 Deposit Share

% Delta % MS 30.00 5.40 5.28 25.00 5.20 20.00 5.00 15.00

10.00 4.80

5.00 7.56 4.60 0.00 4.40 -5.00

-10.00 4.20 Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15

MS Nas (%) S-K Growth Delta Source: Bank Indonesia

138 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

the customers of Islamic banks were observed to Compared to conventional financing growth, Islamic gradually diversify from long-term to shorter term financing was down 1.1%. Therefore, Islamic financing savings instruments. growth has never outpaced conventional financing, since the beginning of 2014. In fact, Islamic banks

Graph 4.74 Deposit Composition of Islamic Banks must be more expansive with their financing in order

(%) to support the real sector through sharia-compliant 100 90 financing. 80

70 62.96 62.84 61.13 61.13 61.02 60 Consumer financing continued to dominate Islamic 50 40 bank financing, valued at Rp85.01 trillion. Meanwhile, 30 28.59 29.70 29.11 20 27.92 28.38 working capital financing totalled Rp81.47 trillion and 10 9.12 10.28 9.17 9.88 0 8.78 investment financing Rp55.70 trillion. Jun-14 Dec-14 Jun-15 Dec-15 Jun-16 Demand Deposits Savings Deposits Term Deposits Source: Bank Indonesia In the first semester of 2016, the financing-to-deposit ratio (FDR) at Islamic banks declined from 92.15% to Financing 92.06% as the value of deposits outpaced financing Financing growth accelerated in the reporting period. in the previous semester. Insignificant financing Nominally, Islamic bank financing expanded from growth was one consequence of domestic economic Rp213 trillion to Rp222 trillion. Annually, growth moderation in 2015. In terms of conventional banks, accelerated from 6.86% to 7.85%. Consequently, the however, the loan-to-deposit ratio (LDR) improved after market share of Islamic banks increased from 5.25% to 2012 but then stagnated from 2014 onwards. Entering 5.33%. 2016, the FDR and LDR ratios were less disparate, with FDR recorded slightly higher than LDR.

Graph 4.75 Financing Performance Graph 4.76 Financing Share % Rp T % 40,00 6.0 220,00 60 35,00 5.9 210,00 222.17 50 30,00 5.8 200,00 25,00 5.7 40 5.6 190,00 20,00 30 15,00 5.5 180,00 5.33 30 10,00 5.4 170,00 5,00 5.3 20 -1.10 160,00 7.85 0,00 5.2 150,00 10 -5,00 5.1 -10,00 5.0 140,00 0 Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15 Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15 S-K Delta Growth Market Share Financing Annual Financing Growth (%) Source: Bank Indonesia, processed Source: Bank Indonesia, processed

139 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 4.77 FDR of Islamic Banks Graph 4.78 Financing by Type % Rp T 90,00 105 85.01

100 80,00 81.47 70,00 95 92.06 60,00 90 91.06 50,00 55.70 85 40,00

80 30,00

75 20,00 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Jun-13 Jun-14 Jun-15 Jun-16 Oct-12 Oct-13 Oct-14 Oct-15 Oct-13 Oct-14 Oct-15 Feb-12 Feb-13 Feb-14 Feb-15 Feb-16 Feb-13 Feb-14 Feb-15 Feb-16 Apr-12 Apr-13 Apr-14 Apr-15 Apr-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-12 Dec-13 Dec-14 Dec-15 Dec-13 Dec-14 Dec-15 Aug-12 Aug-13 Aug-14 Aug-15 Aug-13 Aug-14 Aug-15 FDR (%) LDR (%) Working Capital Investment Consumption Source: Bank Indonesia, processed

Risk Assessment of Islamic banks only because it was higher than conventional banks, Financing Risk but also because it exceeded the normal threshold. In the first semester of 2016, financing risk at Nevertheless, considering that the market share of conventional banks escalated, reflected by an increase Islamic bank financing is comparatively small, a build- in gross NPF from 4.34% to 5.05% in the reporting up of financing risk at Islamic banks does not have a period. The high level of non-performing financing significantly detrimental impact of financial system (NPF) at Islamic banks demanded extra vigilance, not stability.

Graph 4.79 Financing Risk at Islamic Banks Table 4.28 Financing Risk by Region

6.00 80 5.05 70 Share Region Sem I 2015 Sem II 2015 Sem I 2016 5.50 Sem I 2106 60 5.00 50 Bali and Nusa Tenggara 5.33% 5.16% 6.27% 2.65% 40 Java 3.95% 4.43% 4.91% 67.97% 4.50 30 Kalimantan 5.35% 6.14% 6.22% 6.48%

4.00 20 Papua dan Maluku 3.79% 4.02% 3.97% 0.61% 10 Sulawesi 2.95% 3.24% 2.85% 5.85% 3.50 7.11 0 Sumatera 5.92% 6.08% 5.87% 16.44% 3.00 -10 Jun-14 Jun-15 Jun-16 Oct-15 Feb-14 Feb-15 Feb-16 Apr-14 Apr-15 Apr-16 Okt-14 Dec-14 Dec-15 Aug-14 Aug-15

Gross NPF (%) NPF Growth (%)

Graph 4.80 Gross NPF by Economic Sector

14.00 13.23 11.86 Sem I 2015 12.00 Sem II 2015 10.00 7.97 Sem I 2016 7.44 8.00 6.57 6.13 6.00 5.17 4.09

4.00 2.70 3.02

2.00

0.00

Trade Mining Others Electricity Agriculture Construction Manufacturing Transportation Social Services Corporate Services Source: Bank Indonesia

140 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

By region, the highest level of non-performing financing Liquidity Risk (NPF) was reported by Islamic banks in Bali and Nusa Liquidity risk at Islamic banks was observed to ease in Tenggara (6.27%), followed by Kalimantan (6.22%) and terms of the LA/NCD ratio, which increased from 99% in Sumatera (5.87%). Although the level of NPF was high, the second semester of 2015 to 103.5%. Nevertheless, the three regions together accounted for a relatively according to the LA/Deposits ratio, liquidity risk at small portion of financing, thus the Islamic banks could Islamic banks increased slightly, as the ratio fell 1% mitigate the associated credit risk. In general, gross to 18.82%. In general, however, both ratios remained NPF ratios in Bali, Java and Kalimantan were observed above their respective thresholds, implying that Islamic to rise, with a combined share of 77%. Conversely, banks successfully mitigated the liquidity risks faced. NPF in Papua, Sulawesi and Sumatera improved, In the second semester of 2015, the LA/NCD ratio of accounting for 23% of the total. Consequently, overall Islamic banks was higher than that of conventional financing quality declined, particularly on the island of banks after receiving capital injections. Nonetheless, Java, where NPF levels have deteriorated since the first the LA/NCD ratio of conventional banks began to move semester of 2015. towards the level of Islamic banks at the end of the first semester of 2016. By economic sector, mining was the largest contributor to non-performing financing (NPF), increasing from Islamic Bank Capital and Efficiency 6.87% in the second semester of 2015 to 11.86% in Capital at Islamic banks declined to 14.75%, a level the subsequent period. In general, financing quality below that of conventional banks. The capital ratios decreased in all economic sectors during the reporting of Islamic banks decreased as Rp 88 billion of bank period, thus confirming that financing quality from capital was absorbed and risk-weighted assets (RWA) Islamic banks has deteriorated in the first half of 2016. increased Rp2.5 trillion. Islamic banks absorbed capital

Graph 4.81 Liquidity Comparison Graph 4.82 Liquidity at Islamic Banks

115 21 135 102.38 105 19 115 95 18.82 17 85 95 15 97.16 103.50 75 13 75 65 11 55 55 45 9

35 7 35 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Jun-12 Jun-13 Jun-14 Jun-15 Jun-16 Oct-12 Oct-13 Oct-14 Oct-15 Oct-12 Oct-13 Oct-14 Oct-15 Feb-12 Feb-13 Feb-14 Feb-15 Feb-16 Feb-12 Feb-13 Feb-14 Feb-15 Feb-16 Apr-12 Apr-13 Apr-14 Apr-15 Apr-16 Apr-12 Apr-13 Apr-14 Apr-15 Apr-16 Dec-12 Dec-13 Dec-14 Dec-15 Dec-12 Dec-13 Dec-14 Dec-15 Aug-12 Aug-13 Aug-14 Aug-15 Aug-12 Aug-13 Aug-14 Aug-15

LA/NCD of Islamic LA/NCD of LA/Deposits of LA/Deposits of Banks Conventional Banks Islamic Banks Conventional Banks

Source: Bank Indonesia, processed Source: Bank Indonesia, processed

141 FINANCIAL STABILITY REVIEW No. 27, September 2016

due to the heightened credit risk faced. On the other Graph 4.85 Financing Share hand, risk-weighted assets (RWA) increased as Islamic banks expanded their financing strategy. 29 4.0 3.5 24 3.0 19 Graph 4.83 Capital Adequacy Ratio 2.5 14 2.0 17 1.11 1.5 9 5.67 1.0 16 4 0.5

15 -1 - 14.72 Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15

14 Aug-13 Aug-14 Aug-15 ROA ROE 13 Source: Bank Indonesia

12 Stress Testing Islamic Banks Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15 Stress tests were performed to measure the capital Source: Bank Indonesia resilience of each respective Islamic bank. The stress tests included an assessment of capital resilience Efficiency to credit risk using balance sheet and financial Islamic bank efficiency was noted to improve in the first performance data per December 2015. semester of 2016. Accordingly, the BOPO efficiency ratio improved along with the ROA and ROE. The BOPO Credit risk was stress tested to measure capital efficiency ratio improved significantly from 94.38% resilience at Islamic banks to potential losses stemming to 92.36%. Meanwhile, the return on assets (ROA) from a build-up of credit risk, using gross NPL as a increased slightly from 0.84% to 1.11%. Likewise, ROE proxy. Scenario-based analysis, or macro stress tests, also increased in line with rising profits and declining were also used assuming a deviation of projected capital at Islamic banks. Consequently, the return economic growth from current GDP. The GDP baseline on equity (ROE) jumped from 3.59% to 5.67% in the was set at 4.7%, with 1.73% for the moderate scenario reporting period. and -18.26% for the severe or worst-case scenario. The Graph 4.84 BOPO Efficiency Ratio severe scenario applied a 1998-level of GDP growth,

95 when Indonesia was facing a devastating economic crisis. The stress tests using the baseline scenario 90 92.36 showed that all Islamic banks would maintain a Capital 85 Adequacy Ratio (CAR) of above 12%. The moderate 80 scenario also demonstrated that the CAR of no Islamic 75 bank would drop below the 8% threshold but three 70 banks would experience a Capital Adequacy Ratio Jun-13 Jun-14 Jun-15 Jun-16 Oct-13 Oct-14 Oct-15 Feb-13 Feb-14 Feb-15 Feb-16 Apr-13 Apr-14 Apr-15 Apr-16 Dec-13 Dec-14 Dec-15 Aug-13 Aug-14 Aug-15 (CAR) of 8-12%. According to the worst-case scenario, Source: Financial Services Authority (OJK) applying severe conditions, the CAR of five Islamic banks was shown to drop below 5%.

142 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 4.86 Stress Test NPL Increase

16.00 Existing 14.00 Sc Baseline 12.00 Sc Moderate 10.00 Sc Severe

ROE 8.00

6.00

4.00

2.00

0.00

-2.00 1 2 3 4 Source : Bank Indonesia, processed

Islamic Nonbank Financial Industry Islamic life insurance. The investment portfolio of the Takaful is a form of sharia-compliant insurance. In takaful industry mainly consisted of Islamic stocks the first semester of 2016, total assets of the takaful (41.14%) and term deposits (35.75%). The industry industry increased 15.42% from Rp26.51 trillion to was dominated by Islamic life insurance, accounting for Rp30.61 trillion (Graph 4.87), in particular due to 81.27% of market share in the reporting period.

Graph 4.87 Takaful Industry Assets Graph 4.88 Takaful Industry Investments Rp T 35 85.01 0.53% Term Deposits 30 9.51% Islamic Stocks 81.47 25 8.43% 26.80% Sukuk 20 Government Islamic Securities (SBSN) 4.63% 35.75% 15 55.70 Islamic Mutual Funds 10 Other Investments

5 23.86% 0 41.14%16.38% Jun-14 Jun-15 Jun-16 Oct-14 Oct-15 Feb-14 Feb-15 Feb-16 Apr-14 Apr-15 Apr-16 Dec-14 Dec-15 Aug-14 Aug-15

Islamic Reinsurance Islamic General Insurance Islamic Life Insurance Total Assets

Source: Financial Services Authority (OJK), processed Source: Financial Services Authority (OJK), processed

143 FINANCIAL STABILITY REVIEW No. 27, September 2016

Awarding Banks that Support Micro, Small Boks 4.1 and Medium Enterprises (MSME)

Micro, small and medium enterprises (MSME) play Bank Indonesia instituted macroprudential a crucial and strategic role in Indonesia’s economy. policy for the banking industry to allocate MSME According to the Ministry of Cooperatives and loans, namely Bank Indonesia Regulation (PBI) MSMEs, in 2013 MSMEs contributed 59.1% of No. 14/22/2012, which was amended by Bank Gross Domestic Product (GDP) and 14% of exports. Indonesia Regulation (PBI) No. 17/12/PBI/2015, Furthermore, MSMEs also absorbed 97.2% of and Circular Letter No. 15/35/DPAU, amended the labour force, while accounting for 99.99% by Bank Indonesia Circular Letter (SE) No. 17/19/ of business units in Indonesia. Nonetheless, the DPUM concerning the Disbursement of Loans or strategic role of MSMEs has not yet been balanced Financing by Commercial Banks and Technical by adequate financing support to the sector. Assistance for the Development of Micro, Small and Medium Enterprises (MSME). The legislation Against a backdrop of global and domestic economic regulates commercial bank lending policy to moderation, large companies, particularly MSMEs by setting a minimum ratio of MSME loans commodity-based firms, experienced deteriorating to total credit of 20%, starting at 5% in 2015, 10% performance and, therefore, decided to lay off in 2016, 15% in 2017 and 20% in 2018. Through the employees. In contrast, MSMEs, as grass-roots regulations, Bank Indonesia provides incentives businesses, were expected to maintain capacity to and disincentives to commercial banks to meet the grow, thereby supporting the local economy. To that MSME credit ratio. end, various efforts were required that strengthen MSMEs to maintain national economic stability as The incentives include account officer training, well as financial system stability. along with training for micro and small enterprises, credit ratings, as well as the presentation and In general, MSMEs continue to face the most publication of awards. On the other hand, the binding constraint of limited capital, which restricts disincentives for commercial banks failing to meet the capacity to grow. In addition, MSMEs also the MSME credit ratio include restrictions on confront several barriers to access formal financing checking account services at Bank Indonesia. from financial institutions, especially banks. The constraints are linked to a lack of capacity One incentive to show appreciation for commercial at MSMEs to meet the financing requirements banks that successfully meet the MSME credit ratio applied by financial institutions as well as a lack is through awards. Presenting awards not only of competence at financial institutions/banks to provides an additional incentive to the reserve extend MSME loans more optimally. requirement, but also encourages the banks to increase lending to MSMEs. Awards are presented

144 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

to commercial banks that meet the following on the manufacturing industry as the catalyst criteria: and complemented by the support of other 1. Attain the prevailing MSME credit or financing sectors. Congruently, micro and small enterprise ratio. In 2016, therefore, banks were required development is also directed towards the to meet an MSME credit or financing ratio of development of industrial clusters, technology no less than 5%; transfer and enhancing human resources. Therefore, bank support in the form of MSME lending is 2. Maintain a ratio of non-performing loans encouraged through the presentation of awards. (NPL)/non-performing financing (NPF) to total credit/financing of less than 5%; In general, the awards are assessed in three stages as follows: 3. Maintain a NPL/NPF ratio to total MSME credit Stage 1: Assessment of Meeting the Prevailing of no less than 5%; and MSME Credit ratio

4. Meet any other themes and criteria as Stage 2: Assessment of the Theme and stipulated. Determination of the Nominees

In 2016, the theme of the awards is “Creating MSME Stage 3: Assessment of Qualitative Aspects Competitiveness”, considering that, in pursuance of the Long-Term Development Plan (RPJP) for 2005- The assessment is carried out by a team consisting 2025, the direction of economic development in of national figures, Bank Indonesia staff, banking Indonesia is the creation of competiveness through experts, economic observers/academics, economic transformation from comparative government ministers and media representatives. advantage to sustainable competitive advantage The 2016 Awards were presented to four through the creation and application of knowledge commercial banks in two categories. For BUKU 1 and technology innovation. and 2 banks, awards were presented to PT Bank Tabungan Pensiunan Sharia as the winner and to PT Competitiveness is enhanced through value chain Bank Pembangunan Daerah Bali as the runner-up. development and innovation, strengthening For BUKU 3 and 4 banks, awards were presented industrial clusters and developing micro to PT (Persero) Tbk as the (local) economic foundations, with a focus winner and to PT (Persero) Tbk as the runner-up.

145 FINANCIAL STABILITY REVIEW No. 27, September 2016

Box Figure 4.1.1 Stages of Award Assessment

STAGE 1 STAGE 2 STAGE 3

118 Best Meeting MSME Meeting MSME Meeting MSME Commercial Nominees Commercial STAGE 1 Credit Regulations Credit Regulations Credit Regulations Banks Bank

- Ratio of MSME - Lender of MSME credit/financing ≤ 5% Loans Pursuant to the Assessment Assessment STAGE 2 - NPL/NPF of MSME Current Theme of Thematic of Qualitative Credit/Financing < 5% - NPL/NPF of thematic Criteria Aspects - NPL/NPF of Total MSME Credit/ Credit < 5% Financing < 5%

The 2016 Awards are expected to provide inspiration and encourage other banks to increase their respective share of MSME loans. In addition, the awards are a tangible form of Bank Indonesia support to economic development programs in Indonesia, in particular the local economy through micro, small and medium enterprises (MSME).

146 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box 4.2 Liquidity Coverage Ratio (LCR)

One significant improvement to banking High Quality Liquid Assets standards/regulations is the countermeasures LCR = to mitigate liquidity risk. The Basel Committee Net Cash Outflow Over the Next 30 Calendar Days on Banking Supervision (BCBS) formulated regulatory foundations in the Principles for Sound The use of HQLA in the LCR ensures that banks hold Liquidity Management and Supervision (BCBS, sufficient assets that can easily and immediately 2008) in 2008, otherwise known as the Sound be converted with little or no loss of market value. Principles. Furthermore, BCBS strengthened the In addition to measurements on the funding side, bank liquidity framework by applying a Liquidity LCR is also calculated on the expenses side by Coverage Ratio (LCR). LCR implementation by the estimating the net flow, namely the difference financial authorities is one way in which banks between the outflow and inflow. Inflow is limited can prudently manage liquidity. The LCR set by to 75% of outflow, which always returns a positive BCBS aims to enhance bank liquidity resilience in LCR value, thus safeguarding bank liquidity. In the near term through a minimum ratio of high reality, HQLA standards and net flows are based on quality liquid assets (HQLA) to net cash outflow for the discretion of the respective financial authority the upcoming 30 days of 100%, calculated under due to differences in the asset recording and stress conditions. HQLA are liquid assets that can classification system in each jurisdiction. Financial be converted easily and immediately into cash at authorities are authorised to raise the minimum little of no loss of value through haircut, outflow LCR ratio as necessary. Nonetheless, banks and inflow rate adjustments. As an asset becomes operating internationally are required to meet the less liquid, a larger haircut is required. As deposits minimum international standards. become less stable, the outflow rate increases, or the expected portion of withdrawals increases. LCR was implemented in Indonesia through OJK As inflows become less stable, a smaller inflow Regulation (POJK) No. 11/POJK.03/2015, dated rate is provided or the portion acknowledged 23rd December 2015, concerning the Liquidity as inflow decreases. The LCR will improve bank Coverage Ratio (LCR). Furthermore, the Financial capacity to operate under liquidity distress for at Services Authority (OJK) implemented a very least the next 30 days. In addition, the LCR will also similar LCR ratio to the standards set by the Basel reduce bank dependence on sources of liquidity Committee on Banking Supervision (BCBS). It is that automatically become expensive in the case important to note, however, that, in practice, it is of a financial or economic shock, thus mitigating difficult to obtain a consistent interpretation of LCR contagion risk that could potentially lead to measurements by each respective bank due to the systemic risk.

147 FINANCIAL STABILITY REVIEW No. 27, September 2016

confidential information held by each respective it would be prudent to lower the minimum LCR bank, for example the portion of deposits requirements for banks in order to absorb liquidity considered stable, leading to a lower outflow risk. rate, which lowers outflow expectations for the Box Graph 4.2.1 A Comparison Between e-LCR and h-LCR

upcoming 30 days. Consequently, Bank Indonesia 600%

developed an e-LCR (or estimated-LCR) indicator 500%

using data extracted from the Monthly Commercial 400%

Bank Reports, which is more conservative than the 300%

banks’ measurements. In other words, the e-LCR 200% is nearly always lower than the LCR reported by 100% commercial banks to OJK. This aims to illustrate 0% Jun-13 Jun-14 Oct-14 Feb-13 Feb-14 Feb-15 Apr-13 Apr-14 Apr-15 Okt-13 Dec-13 Dec-14 liquidity movements at individual banks in order Aug-13 Aug-14 e-LCR h-LCR for Bank Indonesia to monitor bank performance for internal macroprudential assessment purposes. LCR tends to be a microprudential liquidity In addition, if the e-LCR has already been shown to instrument. Nevertheless, there is a school of meet the minimum requirements, the respective thought that considers the reformed liquidity bank will certainly be able to absorb more liquidity regulations under Basel III to fundamentally risk for the next 30 days than implied by the e-LCR. be categorised as microprudential and macroprudential instruments simultaneously. In Through research conducted in 2015, Bank addition to the minimum LCR requirements, Basel Indonesia also developed an ex-post h-LCR III also mandates a minimum Net Stable Funding (historical-LCR) indicator, namely the ratio of HQLA Ratio to overcome liquidity risk on the funding side, to net cash outflow in the previous 30 calendar days. or long-term liquidity. The h-LCR indicator was developed for research purposes and to observe the ability of e-LCR to Over time, profit-taking by banks is also reflected represent the respective bank’s ability to meet its in the liquidity ratio. Bank Indonesia research has liquidity demand in the near term. The research observed that when liquidity and the economy found that the e-LCR was more often higher than boom, the banks tend to attenuate liquidity, the h-LCR, implying that bank liquidity could always favouring a more profitable but higher-risk portfolio. meet demand for the next 30 days under stress Such conditions show that bank procyclicality can conditions. Nevertheless, when the taper tantrum influence liquidity risk. Therefore, macroprudential occurred in July 2013, the h-LCR sank below the policy provides an opportunity to ensure the e-LCR, indicating that, under stress conditions, banks absorb risk when liquidity and the economy experience a bust period.

148 Households Bank Indonesia Policy Financial System The Financial And The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

149

In the first semester of 2016, the payment system, as a component of financial system infrastructure, remained secure, reliable and efficient, thus supporting monetary and financial system stability as well as facilitating economic activities. Sound payment system performance was the result of Bank Indonesia policy to constantly improve the performance of the payment system operated by Bank Indonesia and the industry. The BI-operated payment system contained low settlement and liquidity risks, met reliability and availability targets, and implemented payment infrastructure for retail and large-value transaction services. Meanwhile, the use of noncash payment instruments increased in the industry-operated payment system.

Public access to and use of financial services in Indonesia have increased, reflected by gains in the Financial Inclusion Index and increased utilisation of digital financial services (DFS) as the number of DFS agents and e-money transactions at such agents increased.

Bank Indonesia will continue to consistently set policy and conduct supervision in order to mitigate payment system risk and enhance the development and socialisation of digital financial services to expand public access.

STRENGTHENING FINANCIAL SYSTEM 5INFRASTRUCTURE FINANCIAL STABILITY REVIEW No. 27, September 2016

Rp Payment System Performance, Operated by Bank Indonesia and the Industry, Supported Monetary and Financial System Stability Rp Payment System

BI-Operated Industry-Operated Payment Payment System Payment System Rp System Indicators

Value Value Checking Account Rp56,166.98 trillion Rp2,879.93 trillion Balance Transaction Volume Transaction Volume Rp308,94 triliun Rp2,990.33 million Turnover Ratio 64.60 million Rp 1.01 Card-Based Payment BI-RTGS Instruments Transaction Queue Value Value Value Rp53,857.29 trillion Rp2,876.75 trillion 64.58% Transaction Volume Transaction Volume Transaction Volume Rp2.96 million Rp2,533002 million 36.06%

BI-SSSS Value Payment System Risk Rp24,722.03 trillion Transaction Volume 0.15 million Settlement Risk Low Operational Risk • Unsettled transactions accounted for • A secure, reliable and efficient payment system was maintained National Clearing System 0.00028% of total transactions or (SKNBI) 0.00004% of total volume Value Systemic Risk Rp2,309.69 trillion Liquidity Risk • Potential systemic risk accumulated • The number of counterparties of the Transaction Volume • No use of the Intraday Liquidity 61.64 million Facility (ILF) recorded 10 banks in Indonesia with the largest number of counterparties increased to 2,710

Rp Digital Financial Services (DFS)

Public access to and use of digital financial services increased in Indonesia Rp Transaction Value Rp6.39 billion Composite Financial Inclusion Index Rp 0.38

Rp Most commonly performed customer DFS Operators transactions by DFS agents 5 Banks • Top up • Cash withdrawals DFS Agents • Fund transfers to savings account 101,689

152 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Second Generation, Phase II, National Clearing System 5.1.Payment System Performance (SKNBI) to feature bulk payments. The policies had a number of positive outcomes, demonstrable through In the first semester of 2016, solid payment system more secure, reliable and efficient use of payment performance facilitated economic activities and system infrastructure. supported national financial system stability. The payment systems operated by Bank Indonesia and the The industry-operated payment system also performed industry were secure, reliable and efficient despite well, indicated by no significant disruptions, thanks increases of transaction volume and value. to the various Bank Indonesia initiatives to promote noncash payment instruments in the national interest Bank Indonesia operated a secure payment system, while prioritising consumer protection. To mitigate indicated by low settlement risk and adequate liquidity risk in the industry-operated payment system, Bank in the reporting period. Furthermore, payment system Indonesia promulgated several payment system reliability and availability targets were attained, while policies and regulations and coordinated with efficiency was achieved through the implementation various institutions and the industry, while actively of payment system infrastructure in the form of the supervising the payment system. Furthermore, National Clearing System (SKNBI) for retail services Bank Indonesia also introduced noncash payment as well as the Bank Indonesia – Real Time Gross instruments and a consumer protection function open Settlement (BI-RTGS) system and Bank Indonesia – to the public. Consequently, public financial literacy Scripless Securities Settlement System (BI-SSSS) for and confidence in noncash payment instruments is large value services. expected to increase and, in turn, expand the use of such instruments. Sound payment system performance was the result of various BI efforts to mitigate risk and enhance To improve transaction security in the payment system, operational performance through a variety of policies specifically for ATM/debit cards, Bank Indonesia issued and regulations, infrastructure development and Bank Indonesia Circular Letter (SEBI) No. 18/15/DKSP, payment system surveillance. The salient policies dated 20th June 2016, concerning National Chip instituted in the first half of 2016 include: (i)the Technology Standards Management for ATM/debit use of Central Bank Money (CeBM) to settle security cards in the first semester of 2016. The circular letter transactions on the capital market; (ii) providing was a follow-up to Bank Indonesia Circular Letter electronic and online checking account management (SEBI) No. 17/52/DKSP , dated 30th December 2015, services to strategic partners (government, banks, on the Implementation of National Chip Standards international institutions and other institutions), and Use of 6-Digit Personal Identification Numbers known as the Bank Indonesia Government Electronic for ATM/debit cards and Credit Cards Issued in Banking System (BIG-eB); and (iii) developing the Indonesia, which mandated further regulations on the

2 Bank Indonesia Circular Letter (SEBI) No. 17/52/DKSP, dated 30th December 2015, on the Implementation of National Chip Standards and Use of 6-Digit Personal Identification Numbers for ATM/debit cards and Credit Cards Issued in Indonesia as a follow-up to Bank Indonesia Circular Letter (SEBI) No. 17/51/DKSP, dated 30th December 2015 as the third amendment to Bank Indonesia Circular Letter (SEBI) No. 11/10/DKSP, dated 13th April 2016, concerning the Management of Card-Based Payment Instruments.

153 FINANCIAL STABILITY REVIEW No. 27, September 2016

ownership and determination of national standards as scope of payment system services. In the first half of well as regulations on the duties, responsibilities and 2016, the industry-operated payment system settled management policy of the national standards. 2,990.33 million transactions worth Rp2,879.33 trillion, up 16.51% and 18.93% respectively on the The various BI endeavours outlined above helped same period one year earlier. the payments systems operated by Bank Indonesia and the industry to achieve a transaction volume of In pursuance of its mandated duties to regulate and 3,054.93 million, worth Rp59,046.91 trillion, in the maintain payment system availability, Bank Indonesia first semester of 2016. is also authorised to supervise all licensed service providers, with the issuers of card-based payment instruments and electronic money as the objects of the 5.1.1. Bank Indonesia Operated Payment System supervision. Surveillance entails offsite supervision The Bank Indonesia operated payment system based on the reports submitted to Bank Indonesia successfully settled 64.60 million transactions in the as well as onsite inspections. In general, the scope first half of 2016, increasing 6.39% on the same period of the supervision includes compliance to prevailing one year earlier, while transaction value moderated regulations, the application of Anti-Money Laundering slightly by 3.90% to Rp56,166.99 trillion over the same and Terrorism Financing Prevention, as well as internal period. Transaction volume was boosted by national control. clearing transactions, while the value declined due to the BI-RTGS system. The transaction volume of the National Clearing System (SKNBI) and the transaction value of the BI-RTGS system accounted for 95.42% and 95.89% respectively of the BI-operated payment 5.2 Payment System Transaction Performance system. In terms of settlement, the RTGS and SSSS

systems were operated optimally, reflected by 99.99% In the first semester of 2016, the volume of payment reliability in the reporting period, up from 99.96% one system transactions was observed to increase 16.27% year earlier. but transaction value experienced a 2.97% decline. Transaction volume was buoyed by card-based 5.1.2 Industry Operated Payment System payment instruments, particularly ATM and ATM/debit The industry-operated payment system achieved cards, while transaction value declined due to RTGS positive growth in terms of the instruments in transactions. Most transaction volume originated circulation and the use of noncash instruments. Such from ATM and ATM/debit cards, while transaction developments were reflected by an increase in the value was still dominated by the BI-RTGS system. All use of card-based instruments and electronic money transactions processed through the BI-RTGS, BI-SSSS as Bank Indonesia promoted noncash payment and SKNBI systems as well as card-based payment instruments. Furthermore, Bank Indonesia also instruments and electronic money are presented in coordinated with other payment system operators Table 5.1 to balance infrastructure coverage and expand the

154 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Table 5.1 BI-RTGS, BI-SSSS and SKNBI, Card-Based Instruments and Electronic Money

VALUE VOLUME

S1 2015 S1 2016 S1 2015 S1 2016

Δ (%) TRANS- TRANS- Δ (%) RP, TRILLIONS RP, TRILLIONS ACTIONS, ACTIONS, MILLIONS MILLIONS BI-RTGS 56.968,42 53.857,29 -5.46% 5,73 2,96 -48.36%

BI-SSSS* 16.455,82 24.772,03 50.54% 0,09 0,15 62.41%

SKNBI 1.475,50 2.309,69 56.54% 54,99 61,64 12.10%

Card-Based Instruments 2.419,34 2.876,75 18.91% 2.347,07 2682,23 14.28%

ATM & ATM/debit cards 2.488,21 2.737,05 10.00% 2211,84 2533,02 14.52% Credit Cards 133,40 139,70 4.72% 135,22 149,22 10.35% Electronic Money 2,28 3,17 39.51% 219,57 308,10 40.32% BI PS 58.443,92 56.166,98 -3.90% 60,72 64,60 6.39% Industry PS 2.421,62 2.879,93 18.93% 2.566,64 2.990,33 16.51% Total SP 60.865,54 59.046,91 -2.99% 2.627,36 3.054,93 16.27% Notes: *) BI-SSSS transactions were settled through the BI-RTGS system, therefore, SSSS transaction value and volume were already included in the RTGS system.

Source: Payment System Statistics, January 2016, Bank Indonesia

Payment transactions settled through the BI- which plummeted 57.42% on the same period of the RTGS system included monetary operations (MO), previous year. government, customer and capital market transactions along with interbank money market interbank foreign Payment system transactions settled through the Bank currency trade transactions in rupiah and foreign Indonesia – Scripless Securities Settlement System (BI- currency transactions between banks and Bank SSSS) increased during the reporting period in terms Indonesia in rupiah and other currencies. Compared of volume and value. BI-SSSS transaction volume to the same period one year earlier, transaction recorded a 62.41% gain to 0.15 million transactions, activity in the RTGS system tracked a downward trend while transaction value increased 50.54% to in terms of volume and value. Accordingly, transaction Rp24,772.03 trillion. volume fell 48.36%, from 5.73 million to 2.96 million transactions, while transaction value decreased Transaction activity through the National Clearing 5.46%, from Rp56,968.42 trillion to Rp53,857.29 System (SKNBI) also increased in the reporting period trillion. In general, the declines were precipitated by in terms of volume and value. SKN transaction value Bank Indonesia policy to raise the transaction floor surged 56.54% to Rp2,309.69 trillion, while volume in the RTGS system to above Rp500 million after climbed 12.10% to 61.64 million transactions, primarily implementation of the second-generation BI-RTSG stemming from credit clearing, namely credit transfers system in the fourth quarter of 2015. Furthermore, between clearing participants’ customers. transaction value was undermined by monetary operations, for which the value was observed to Concerning the industry-operated payment system fall by 18.89% on the same period one year earlier. and compared to the same period of 2015, card- On the other hand, transaction volume decreased based payment instruments and electronic money primarily due to transactions between customers, experienced solid gains in terms of volume and value,

155 FINANCIAL STABILITY REVIEW No. 27, September 2016

increasing 14.28% to 2,682.23 million transactions and Nonetheless, the decline did not signal tighter liquidity 18.91% to Rp2,876.75 trillion respectively. On the other conditions but was the result of Bank Indonesia hand, electronic money also recorded strong growth, lowering the primary reserve requirement in rupiah increasing 40.32% to 308.10 million transactions and from 7.5% to 6.5%, effective from 16th March 2016. 39.51% to Rp3.17 trillion respectively. 5.3.2. Turnover Ratio2 The turnover ratio (TOR) was recorded at 1.07 in the The rapid expansion of card-based payment first semester of 2016, up 5.28% on the previous instruments and electronic money was in line with period (Graph 5.1). TOR increased on a decline in widespread education activities aimed at the public the account balance prompted by the lower primary concerning the use of noncash instruments. In addition, reserve requirement in rupiah. Bank Indonesia constantly strives to expand the use of such instruments through various endeavours and All bank groups reported increases in the turnover policies. In the first semester of 2016, for example, ratio, except BUKU 4 banks that experienced a 6.41% Bank Indonesia cooperated with the Jakarta provincial decline. TOR at BUKU 3, 2 and 1 banks increased by government to host the Smart Money Smart City 16.03%, 11.37% and 16.06% respectively. Festival as part of the National Noncash Movement

(GNNT), held from 2nd to 4th June 2016 at the Golf Graph 5.1 Turnover Ratio by Bank Group

Driving Range in Senayan, Jakarta. At the event, the 2.50

Jakarta Food Info application was launched along 2.00 with the soft launching of the Jakarta One card by the 1.50 Governor of Bank Indonesia, Agus D.W. Martowardojo, 1.00 0.50 and Governor of DKI Jakarta, Basuki Tjahja Purnama, 0.00 who also opened the festival. Furthermore, Bank Sem I Sem II Sem I Sem II Sem I Sem II Sem I 2013 2014 2015 2016 Indonesia also continuously urges payment system BUKU 1 BUKU 2 BUKU 3 BUKU 4 Industry service providers to enhance consumer protection, Source: Bank Indonesia thus raising public confidence in noncash instruments. 5.3.3. Queued Transactions3 A total of 9,278 transactions were queued worth Rp439.86 trillion in the first semester of 2016, 5.3. Payment System Indicators equivalent to 0.3% of BI-RTGS transaction volume and 0.7% of transaction value. The queue ratios were 5.3.1. Account Balance comparatively low despite a moderate increase on The account balance of BI-RTGS participants recorded the previous period. Notwithstanding, all queued a 13.6% decline in the reporting period, from Rp308.94 transactions were settled on the same day, thus trillion to Rp266.79 trillion compared to yearend 2015. demonstrating how liquidity risk and settlement

2 The turnover ratio (TOR) is a comparison between outgoing transactions and the current balance of RTGS participants. TOR measures the relative ability of RTGS participants to meet payment system transaction liabilities. A TOR value of more than 1.00 indicates that a participant cannot meet its liabilities merely from the opening balance but also relies on incoming transactions from other RTGS participants. 3 Queued transactions are those queued in the Bank Indonesia – Real Time Gross Settlement (BI-RTGS) system due to insufficient funds at the respective bank to settle a transaction when it is received. The transaction is, however, still settled on the same day.

156 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 5.2 Queued Transactions

Lower the floor of RTGS transactions from Rp500 Trillions 800 million to Rp100million 30

700 25 600 20 500

400 15

300 10 200 5 100

0 0 04 11 18 25 01 09 16 23 01 08 16 23 31 07 14 21 28 09 16 23 30 06 13 20 27 04 15 22 29 Jan-16 Feb-16 Mar-16 Apr-16 May-16 Jun-16 Jul-16

Vol Nom (rhs, Rp) Source: Bank Indonesia risk were mitigated in the RTGS system. Queued on the 0.002% and 0.001% posted in the previous transactions in the first semester of 2016 are presented period. in Graph 5.2. 5.4.2. Liquidity Risk5 Industry-wide, the increase of queued transactions Liquidity risk in the payment system was contained in since the beginning of June 2016 was the result of the first semester of 2016. Bank Indonesia received Bank Indonesia policy to lower the floor of RTGS no requests for the Intraday Liquidity Facility transactions from Rp500 million to Rp100 million. (ILF), which is a funding facility provided by Bank Indonesia to participating banks in the form ofa securities repurchase agreement (repo). The Intraday 5.4. Payment System Risks and Liquidity Facility (ILF) is available to participating Mitigation Efforts banks upon approval from Bank Indonesia and is provided automatically when the account balance 5.4.1. Settlement Risk4 of a participating bank is insufficient to execute its Settlement risk was contained in the first semester outgoing transactions. Thereafter, the ILF is settled of 2016, indicated by the small volume of unsettled automatically upon receipt of incoming transactions. transactions in the window time of the BI-RTGS system. Bank Indonesia received no requests for the facility The value of unsettled transactions was recorded at during the first semester of 2016, indicating that Rp14,904.22 billion in the reporting period, equivalent no participating banks suffered short-term liquidity to just 0.00028% of the total. In terms of volume, shortfalls due to a mismatch between incoming and however, only 112 transactions were not settled out outgoing transactions. of a total of 2,960,111, accounting for 0.00004%. The ratios of unsettled transactions decreased significantly

4 From a participant’s perspective, settlement risk could emerge due to late and failure-to-settle payment transactions while waiting for incoming transfers from other participants. From the operator’s perspective, however, settlement risk is not an issue because RTGS participants apply the principle of no money no game, where settlement transactions are only processed if sufficient funds are available. 5 Liquidity Risk Occurs in the Payment System when an RTGS participant has insufficient funds to meet the liabilities on time despite potentially fulfilling the liabilities in the subsequent window time.

157 FINANCIAL STABILITY REVIEW No. 27, September 2016

5.4.3. Operational Risk6 Adjustments were made to the backup systems for Operational risk was well mitigated during the first BI-RTGS, BI-SSSS and SKNBI during the reporting semester of 2016, with Bank Indonesia focused on period at the Data Recovery Centre (DRC) in line with operating a secure, reliable and efficient payment implementation of the second-generation systems. system, considering that operational risk in the payment system could exacerbate liquidity risk and, 5.4.4. Systemic Risk7 ultimately, disrupt financial system stability. Systemic risk is the risk of default at one or more banks due to systemic events. In the financial system, systemic Bank Indonesia constantly strives to minimise risk can be measured by the interconnectedness of operational risk in the payment system by sustainably RTGS participants and observed from the number implementing a Business Continuity Plan (BCP) that of counterparties of each respective participating includes the provision of a backup system that is bank. A larger number of counterparties implies continuously on standby to replace the primary greater risk. By looking at the 10 banks with the most production system in its entirety as required. counterparties in recent periods, potential systemic Furthermore, to mitigate operational risk, Bank risk in the BI-RTGS system was shown to increase in Indonesia also periodically checks the infrastructural the first semester of 2016 compared to the previous preparedness of BI-RTGS, BI-SSSS and the National period but decrease on the position one year earlier as Clearing System (SKNBI). In the first semester of 2016, the number of counterparties fluctuated from 2,745 periodic testing in the form of monitoring and partial in the first semester of 2015 to 2,478 in the second trials of the backup systems were conducted once, semester of 2015 and to 2,710 in the reporting period. while the backup front office (BFO) was monitored A list of the 10 banks with the most counterparties is three times to ensure infrastructural preparedness. presented in Table 5.2.

Table 5.2 Ten Large Banks with Most Counterparties

2013 2014 2015 2016

Sem I Sem II Sem I Sem II Sem I Sem II Sem I Rating Counter- Counter- Counter- Counter- Counter- Counter- Counter- Bank party Bank party Bank party Bank party Bank party Bank party Bank party in-out in-out in-out in-out in-out in-out in-out

1 BUKU 4 293 BUKU 4 290 BUKU 4 288 BUKU 4 290 BUKU 4 284 BUKU 4 272 BUKU 4 280

2 BUKU 4 292 BUKU 4 289 BUKU 4 288 BUKU 4 289 BUKU 4 283 BUKU 4 265 BUKU 4 280

3 BUKU 4 292 BUKU 4 289 BUKU 4 288 BUKU 4 289 BUKU 4 281 BUKU 4 262 BUKU 4 278

4 BUKU 4 292 Syariah 287 BUKU 4 286 Syariah 287 BUKU 4 281 BUKU 4 256 BUKU 4 276

5 BUKU 3 286 BUKU 4 286 BUKU 3 284 BUKU 4 286 BUKU 3 272 BUKU 3 243 BUKU 3 270 6 Syariah 286 BUKU 3 283 BUKU 3 280 BUKU 3 283 BUKU 3 272 BUKU 3 242 BUKU 3 268 7 BUKU 3 283 BUKU 3 280 Syariah 280 BUKU 3 280 BUKU 3 271 BUKU 3 239 BUKU 3 266 8 BUKU 3 282 BUKU 3 280 BUKU 3 279 BUKU 3 280 BUKU 2 269 BUKU 3 239 Syariah 266 9 Syariah 282 BUKU 2 276 BUKU 2 278 BUKU 2 276 BUKU 3 266 BUKU 3 236 BUKU 3 264 10 BUKU 4 281 BUKU 3 275 BUKU 3 276 BUKU 3 275 BUKU 3 266 BUKU 3 224 BUKU 3 262

6 Operational risk originates from operating factors, including system and network issues. 7 Systemic risk is the risk of default at one or more financial institutions due to systemic events in the form of shocks that impact one or more institutions and then spread through contagion, or shocks that simultaneously affect several large institutions (De Brandt and Hartman, 200, and Zebua, 2010, in the Monetary and Economic Bulletin, October 2013).

158 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

If any of the banks considered at risk were to Determinants of financial inclusion differ from country experience default, contagion risk would spill over to to country, including geographical conditions, public other participants in the RTGS system, which could awareness and infrastructure availability in rural areas. potentially undermine financial system stability. When calculating the Indonesia Financial Inclusion Consequently, Bank Indonesia conducts special Composite Index (IKKI), Bank Indonesia uses three surveillance of systemic banks as part of its efforts to indicators for two dimensions of financial inclusion, maintain financial system stability. namely (i) the access dimension that looks at the availability of banking services (BS), such as branch offices, ATMs and so on; (ii) the banking penetration (BP) dimension; as well as (iii) the usage of the banking 5.5. Digital Financial Services and system (BU). The Sarma method (2012) applies an Financial Inclusion index of between 0 and 1, where a value of 1 indicates complete financial inclusion and a value of 0 indicates 5.5.1. Indonesia Financial Inclusion Composite complete financial exclusion. Using the Sarma method Index (IKKI) (2012), the Indonesia Financial Inclusion Composite One benchmark of financial inclusion in a country is Index (IKKI) was recorded at 0.38 (medium) in the the Financial Inclusion Index, which is calculated using first semester of 2016, up 5.2% on the position in several methods that vary by country and organisation, December 2015, which shows that public access to including the Alliance for Financial Inclusion (AFI), and use of financial services in Indonesia is increasing, International Monetary Fund (IMF) and different albeit still categorised as medium. economists such as Sarma (2008, 2010, 2012), Crisil and Chi-Winds. Bank Indonesia adopted the method proposed by Sarma (2012) to calculate the Indonesia 5.5.2. Digital Financial Services (DFS) Financial Inclusion Composite Index (IKKI) along with Building on the momentum achieved in the previous the technique developed by AFI. period, digital financial services (DFS) continued

Graph 5.3 Indonesia Financial Inclusion Composite Index (IKKI)

0.40 0.38 0.36 Jun-16 : 0.38 0.34 Thresholds: 0.32 Low (0-0.3); 0.30 Medium (0.3-0.6); Jun-15 : 0.31 High (0.6-1) 0.28 0.26 0.24 0.22 0.20 Jul Jul Jan Jan Jan Jun Jun Jun Oct Oct Feb Feb Feb Apr Apr Apr Sep Sep Dec Dec Nov Nov Mar Mar Mar Aug Aug May May May 2014 2015 2016

159 FINANCIAL STABILITY REVIEW No. 27, September 2016

Figure 5.1 DFS Agents in Indonesia

3 DFS Agents in di 1 Regencies/Cities 14 DFS Agents in di 3 Regencies/Cities

79.943 DFS Agents in 30.713 DFS Agents in 446 Regencies/Cities 375 Regencies/Cities

to expand in the first half of 2016 as the number of followed by Bank Mandiri with 375. Meanwhile, CIMB operators and agents increased along with e-money Niaga has DFS agents in three regencies/cities and BCA transactions at DFS agents. maintains its focus on Jakarta.

i. DFS Operators ii. DFS Agents Five banks are currently licensed as DFS operators, The number of DFS agents increased significantly in namely BRI, Bank Mandiri, BNI, CIMB NIAGA and BCA, the first semester of 2016, growing 46.2% to 101,689 with four currently in operation (BRI, Bank Mandiri, agents on the rapid expansion of business agents CIMB Niaga and BCA). Of the five DFS operators, three (78.1%). Most DFS agents (82.1%) are individuals, (BRI, Bank Mandiri and BCA) are licensed to utilise consisting of grocery stores, small shops/stalls, individual and business DFS agents, while the other telephone credit sellers and Payment Point Online two (CIMB Niaga and BNI) favour business agents. Bank (PPOB), while business agents include retailers In terms of coverage, BRI has the broadest network and cooperatives (18.9%). of DFS agents, extending to 446 regencies/cities,

Graph 5.4 Total DFS Agents in 2016 Table 5.3 Total Individual and Business DFS Agents in Semester I – 2016 120,000 101,689 90,691 Periode 2016 Individual Agents Business Agents 100,000 83,982 89,101 77,911 80,000 73,534 January 63,810 9,724 February 67,970 9,941 60,000

40,000 March 73,790 10,192 April 78,641 10,460 20,000 May 80,745 9,946 0 January February March April May June June 84,374 17,315 Source: Bank Indonesia, June 2016, processed

160 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

iii. Transactions at DFS Agents skewed utilisation of e-money transactions demands E-money transactions through DFS agents were more education and socialisation activities inthe observed to grow 18.8% (ytd) to Rp 6.39 billion in public sphere to build awareness about the different the first semester of 2016. The regencies/cities of transactions available through DFS agents. Probolinggo, Bogor and East Jakarta recorded the largest total value of electronic money transactions In addition to transaction value, the number of in the reporting period. Unchanged from the previous e-money accounts opened by the public at DFS agents semester, there are currently six types of e-money also increased, as illustrated in Graph 5.7. The number transactions, with top up, cash out and person-to- of e-money account holders increased 7.04% (ytd) to account transfers the most popular. The composition 1,226,126 in the first semester of 2016, but the value of e-money transactions did change, however, with has not shown significant gains (Graph 5.6). cash-out transactions declining significantly from 40% to 20%. Meanwhile, the share of top-up transactions iv. DFS Development: Pilot Project and person-to-account transfers increased Developing digital financial services (DFS) in Indonesia, respectively from 31% and 14% to 47% and 20%. The since 2015, Bank Indonesia has run DFS pilot projects

Graph 5.5 Respective Shares of E-Money Transactions at DFS Agents in Semester I – 2016

Transfer Government to Person (G2P) 0% Initial 2%

Transfer Person to Account 20%

Transfer person 9% Top Up 47% Payment 2%

Cas-Out 20%

Graph 5.6 E-Money Float at DFS Agents Graph 5.7 Total E-Money Account Holders at DFS Agents

Jun-16 42.95 Jun-16 1.226,126

Mei-16 43.29 Mei-16 1.218,476

Apr-16 43.19 Apr-16 1.218,896

Mar-16 43.15 Mar-16 1.183,139

Feb-16 43.09 Feb-16 1.165,010

Jan-16 43.11 Jan-16 1.151,571

Source: Bank Indonesia, June 2016, processed

161 FINANCIAL STABILITY REVIEW No. 27, September 2016

at pesantren (Islamic boarding schools) and disbursed c. Cellular signal strength was weak at Daarut government social assistance to the public. In the first Tauhiid. semester of 2016, pilot projects were implemented at Daarut Tauhiid Islamic boarding school in d. Employees were unable to transact due to and Al-Mawaddah girls’ Islamic boarding school in East expired SIM cards. Java in conjunction with several telecommunications companies, namely PT Telekomunikasi, PT XL Axiata e. Customers were also inconvenienced by other and PT Indosat Ooredoo. issues, including forgotten PINs or expired SIM cards, which had to be resolved at the nearest The pilot project at Daarut Tauhiid was well received provider office because the agents were and ran smoothly but several implementation incapable. constraints/weaknesses were found that must be overcome in future projects as follows: f. The benefits and advantages of DFS services were a. Agents were unable to process registrations not well known in the surrounding communities. without assistance from telecommunications Therefore, each telecom company periodically companies. sets up an information centre to provide and explain DFS products. Furthermore, a manual b. Customers found e-money services slightly has also been written explaining the transaction inconvenient due to a lack of familiarity using process. cellular telephones for such transactions. Consequently, customers felt the payment The pilot project at Al-Mawaddah is still at the process was too time-consuming. preparation stage, including educating the employees, students and surrounding community. The pilot project is set to begin in September 2016.

162 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Boks 5.1 Disbursement of Noncash Social Assistance Funds

Social assistance is a government program to help banks disbursing government social assistance poor and disadvantaged families. The effective, and, therefore, provide simplicity and convenience, efficient and on-target disbursement of social while simultaneously expanding public access. assistance funds benefits all parties involved from upstream to downstream. The conventional The cooperation and synergy between Bank method of disbursing social assistance using Indonesia and the Government, ministries, cash has several salient weaknesses, including a banking sector and relevant authorities aims to protracted disbursement process that is difficult disburse social assistance funds based on the 6T to control and, therefore, often falls behind target principles, namely Tepat Sasaran, Tepat Jumlah, and is difficult to build up statistics, vulnerable to Tepat Harga, Tepat Wkatu, Tepat Quality and fraudulent behaviour and so on. Tepat Administrasi, which roughly translates into English as On Target, Right Total, Right Price, On Considering the weaknesses and in an effort to Time, Right Quality and Right Administration. The expand the noncash movement, Bank Indonesia 6T principles are in line with the noncash social proposed a solution by converting social assistance disbursement model proposed by Bank assistance disbursements from cash to noncash, Indonesia and submitted to the Limited Cabinet which was shown to be more effective, efficient Meeting held in April 2016, consisting of four and on target. Therefore, synergy was required salient aspects, namely: (i) bulk registration and between Bank Indonesia and the Government, account opening; (ii) education and socialisation; government ministries, the banking sector and (iii) assistance fund disbursements; and (iv) relevant authorities to facilitate noncash social assistance fund withdrawals by the recipient. assistance disbursements through electronic Consistent with the four aspects, sustainable money accounts. Consequently, social assistance social assistance disbursement could be realised, payments were possible to collect from approved where the public would conveniently receive the DFS agents, which were later expanded to include payments, the banking sector would maintain bank branches and ATMs. business sustainability, agents would notice an increase of income and the Government would Bank Indonesia also took the initiative to develop meet the 6T principles. social assistance disbursements through the HIMBARA payment system and to empower the A pilot project to disburse social assistance funds, public through e-Warongs as agents of digital with the support of HIMBARA payment system financial services (DFS), which helped create interoperability and interconnectivity, was run interoperability and interconnectivity between to illustrate the vast potential and synergy of the

163 FINANCIAL STABILITY REVIEW No. 27, September 2016

Association of State-Owned Banks (HIMBARA), which consisted of 114,000 DFS agents and branchless banking throughout Indonesia per June 2016. By creating interoperability and interconnectivity between the disbursing banks, the public benefitted directly through simplicity and convenience as well as greater access via the network of ATMs, EDCs and DFS agents/branchless banking available to HIMBARA. Greater access would also expand social assistance payments and, therefore, lead to public betterment.

Bank Indonesia also welcomed public empowerment through e-warongs. Extending the banks’ reach, e-warongs play an important role in expanding disbursements due to their direct presence in the community. Nevertheless, prudential principles and consumer protection must also be prioritised by the banking industry when expanding the agent network. Furthermore, Bank Indonesia stresses the importance of five key requirements of becoming a DFS agent: (i) capacity, reputation and integrity; (ii) local resident or business entity; (iii) operating for at least two years; (iv) pass bank due diligence; and (v) maintain a bank deposit account. The requirements are necessary not only to ensure effective and efficient disbursement activity but also to ensure security and prevent an additional burden on the public and national economy.

164 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

165

Bank Indonesia maintained accommodative and countercyclical macroprudential policy during the first half of 2016 to stimulate economic growth through bank lending, while preserving financial system stability. Despite maintaining financial system stability, onerous global and domestic risks remained, primarily in the form of heightened credit risk and decelerating bank intermediation.

During this period, Bank Indonesia assessed the Loan (Financing) to Value Ratio and RR-loan to funding ratio (RR-LFR) and prepared adjustments as required. Furthermore, Bank Indonesia maintained the countercyclical buffer rate at 0% as part of the overall policy mix that included lowering the BI Rate and also reformulating the policy rate transmitted to banking rates, while instituting payment system and money supply policy to create economic growth momentum. In addition, Bank Indonesia strengthened policy coordination with the Government and other relevant authorities through regulations concerning the Prevention and Resolution of Financial System Crises.

BANK INDONESIA POLICY RESPONSE TO SUPPORT FINANCIAL6 SYSTEM STABILITY FINANCIAL STABILITY REVIEW No. 27, September 2016

Macroprudential Policy aims to Maintain Financial System Stability and Stimulate Bank Intermediation as part of the more general Bank Indonesia Policy Mix

Assessment of the RR-loan to funding ratio (RR-LFR) and adjustments to Rp checking account services to meet the MSME loan requirement

MSME RR-loan to funding ratio (RR-LFR)

Rp

Loan-To-Value Ratio (LTV) For Property Loans And Downpayments On Automotive Loans

Assessment of the LTV/FTV (loan-to-value/financing-to- value) ratios for property loans and downpayments on automotive loans

Set the CCB Rate at 0%

Bank Indonesia set the countercyclical capital buffer (CCB) rate at 0% as a preventative measure to systemic risk originating from excessive credit growth

Strengthening coordination between Bank Indonesia, the Government and relevant Authorities

POLICY RESPONSE

168 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Bank Indonesia maintained an accommodative and in the first semester of 2016, including loosening countercyclical macroprudential policy stance in the LTV/FTV (loan-to-value/financing-to-value) the first half of 2016 to stimulate economic growth ratios for property loans and downpayments on through bank credit growth, while maintaining automotive loans, honing the RR-loan to funding financial system stability. In addition, the monetary ratio (RR-LFR) and adjusting checking account and macroprudential policy mix, combined with services to meet the MSME credit requirement, payment system policy and money supply, were as well as issuing regulations requiring banks to maintained by Bank Indonesia to create economic maintain a countercyclical capital buffer (CCB). growth momentum. Strengthening the newly implemented polices, Economic growth in Indonesia remained sluggish Bank Indonesia assessed and refined its existing but began to accelerate in the second quarter macroprudential policy stance. Consequently, the of 2016. The global and domestic risks faced, LTV/FTV regulation was adjusted along with the however, continued to loom large. Global economic floor of the RR-loan to funding ratio (RR-LFR). moderation persisted due to low international Bank Indonesia also conducted macro regulation commodity prices and a build-up of risk on global and supervision of financial service institutions financial markets after the Brexit referendum in and focused on assessing potential systemic risk in UK. Furthermore, domestic risk stemmed from the the financial industry, while stress testing financial financial cycle, which remained in a contractionary institution resilience in order to create financial phase, procyclical bank lending, a balance of system stability. payments (BOP) deficit, an indebted corporate sector with foreign loans, large non-resident Congruent with macroprudential policy, Bank holdings of securities, and limited fiscal space. Indonesia also sought to strengthen coordination with other authorities, including joint formulation Macroprudential policy has a complex transmission and promulgation of the Financial System Crisis mechanism that contains a time lag prior to reaching Prevention and Handling (PPKSK) Act on 15th April its goal. The various macroprudential policies 2016, which reinforced coordination between the instituted by Bank Indonesia during the second half authorities and helped to create financial system of 2015 prevented further property credit declines stability.

169 FINANCIAL STABILITY REVIEW No. 27, September 2016

which compelled Bank Indonesia to refine property 6.1 Assessment of the LTV/FTV (loan-to- credit policy through Bank Indonesia Regulation value/financing-to-value) Ratios for (PBI) No. 17/10/PBI/2015, dated 18th June 2015, Property Loans and Downpayments concerning the Loan-to-Value/Financing-to-Value on Automotive Loans Ratio for Property Loans and Downpayments on Automotive Loans as follows: Sluggish sales data and slower rising house prices were accompanied by fewer applications for housing loans, a trend that has persisted since 2013 and

Table 6.1 LTV/FTV Ratios for Banks to Meet Prevailing NPL/NPF Requirements for Total Credit or Financing

PROPERTY LOANS AND FINANCING BASED ON MUHARABAH AND ISTISHNA CONTRACTS PROPERTY LOANS AND FINANCING PROPERTY TYPE 2 (m ) I II III dst

House Type > 70 80% 70% 60% Type 22 – 70 - 80% 70% Type ≤ 21 - - - Apartment Type > 70 80% 70% 60% Type 22 – 70 90% 80% 70% Type ≤ 21 - 80% 70% Home Store/Home Office - 80% 70%

Source: Bank Indonesia

PROPERTY FINANCIG BASED ON MMQ AND IMBY CONTRACTS FASILITAS KP & PP PROPERTY TYPE 2 (m ) I II III dst

House Type > 70 85% 75% 65% Type 22 - 70 - 80% 70% Type ≤ 21 - - - Apartment Type > 70 85% 75% 65% Type 22 - 70 90% 80% 70% Type ≤ 21 - 80% 70% Home Store/Home Office - 80% 70%

Source: Bank Indonesia

170 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

In general, business players in the property sector, Overall, the policies managed to prevent further along with homebuyers using loans, responded declines of housing loans, with growth observed favourably to the looser LTV policy, reflecting to increase from 6.46% (yoy) in the first semester stronger property credit growth, particularly real of 2015 to 7.62% (yoy) in the reporting period. By estate, in the first half of 2016, accelerating from property type, property credit growth was strongest 18.32% in the first semester of 2015 to 28.29% for houses of 22-70m2 as well as flats/apartments (yoy) in the reporting period. of up to 21m2, posting 14.47% (yoy) and 16.14% (yoy) respectively, up from 9.87% (yoy) and 0.77% (yoy) at the end of June 2015.

Graph 6.1 Performance of Housing Loans Graph 6.2 Housing Loan Growth

yoy (%) yoy (%) LTV 2012 LTV 2013 LTV 2015 50.0 LTV 2012 LTV 2013 LTV 2015 110.0 90.00 70.00 45.0 50.00 30.00 14,47 40.0 10.00 -10.00 4,18 35.0 -30.00 -5,56 28.89% 30.0 House of ≤ 21m2 House of > 70m2 House of 22-70m2

25.0 yoy (%) 20.0 290.0 266.0 15.0 16.41% 240.0 215.0 10.0 8.89% 190.0 165.0 5.0 7.62% 140.0 16,14 115.0 Jun 15 : 6.46% 90.0 1,71 0.0 65.0 1,64 40.0 -281 15.0 Jul-14 Jul-15 Jul-12 Jul-13 Jun-16 Mar-14 Nov-14 Mar-15 Nov-15 Mar-16 Nov-12 Mar-13

Nop-11 Nop-12 Nop-13 10.0

Housing Loans Total Credit Jan-14 Jun-14 Jun-16 Oct-12 Feb-16 Apr-15 Sep-15 Mar-13 Nov-14 May-12 Real Estate Construction Agus-13 Flats/Apt s.d 21m2 Flats/Apt >70m2 Source: Bank Indonesia Home Store/Home Office Flats/Apt 22-70m2

Source: Bank Indonesia

Table 6.2 Property Credit, Housing Loans, Flat/Apartment Loans

Annual Growth (%, yoy) Annual Growth (%, yoy) Annual Growth (%, yoy) Loan House Type House Type Jun‘ 15 Jun’ 16 Jun‘ 15 Jun’ 16 Jun‘ 15 Jun’ 16

Construction 38.34 16.41 Housing Loans 2.67 -5.56 Flats/ Apt sd TIpe 21 0.77 16.14 Tipe 21 Real Estate 18.32 28.29 Housing Loans 9.87 14.47 Flats/ Apt TIpe 22 3.49 -1.64 22 - 70 sd 70 Housing Loans 6.46 7.62 Housing Loans 9.87 4.18 Flats/ Apt TIpe > 70 -4.42 -2.81 > 70 Total Credit 10.38 8.89 Home Store / Home 4.01 1.71 Office

Source: Bank Indonesia

171 FINANCIAL STABILITY REVIEW No. 27, September 2016

Nonetheless, stronger growth of property loans was of houses, especially flats/apartments larger than accompanied by heightened risk. Property credit 21m2. The highest level of NPL affected houses risk tended to increase in the reporting period to ≥70m2, contrasting loans for flats/apartments 2.67%, compared to 2.59% in the first semester of ≥70m2, which contained the lowest NPL. 2015 and 2.34% in the second semester of 2015. Such developments were consistent with the total By location, more than 60% of housing loans NPL increase in the banking industry to 3.05%. were concentrated on the island of Java, Property loans for home stores/home offices dominated by West Java with 24.51%, followed contained the most risk with NPL recorded at by Jakarta with 16.69%. That trend is in line 3.81%, followed by loans for houses and then with greater infrastructure availability on Java loans for flats/apartments. The NPL of loans for compared to the other islands of the archipelago, flats/apartments was generally lower than that which drives property sector development.

Graph 6.3 NPL of Housing Loans Graph 6.4 NPL of Loans for Flats/Apartments

NPL (%) NPL (%) 5.0 LTV 2012 LTV 2013 LTV 2015 5.0 LTV 2012 LTV 2013 LTV 2015 4.5 4.5 3.81 4.0 4.0 3.5 3.5 2.70 3.0 2.67 3.0 2.5 2.0 3.64 2.5 1.5 1.92 2.63 2.0 2.55 1.0 1.10 1.5 0.5 0.0 1.0 Jul-14 Jan-12 Jun-16 Jun-12 Oct-15 Feb-14 Apr-13 Sep-13 Des-14 Mar-16 Jul-14 Jul-15 Jul-12 Jul-13 Nop-13 May-15 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jun-16 Oct-14 Oct-15 Oct-12 Oct-13 Apr-12 Apr-13 Apr-14 Apr-15 Apr-16

2 Houses of 22-70m2 Total Housing Loans Home Store/Home Office Flats/Apartment ≤ 21m ≤ 21m2 > 70m2 22 – 70m2 > 70m2

Source: Bank Indonesia Source: Bank Indonesia

Table 6.3 NPL Growth of Property Loans for Houses and Flats/Apartments

NPL, % (Yoy) NPL, % (Yoy) NPL of Housing Loans NPL of Loans for Flats/Apartments Jun‘ 15 Jun’ 16 Jun‘ 15 Jun’ 16

Houses ≤ 21 2.04 2.70 Flats/Apartments ≤ Tipe 21 1.12 1.10 Houses 22 - 70 2.92 2.55 Flat/ Apt Tipe 22 sd 70 1.72 1.92 Houses > 70 3.02 2.63 Flat/ Apt Tipe > 70 3.39 3.54 3.11 3.81

Source: Bank Indonesia

172 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

All provinces managed to exploit the looser LTV policy in 2015, with Bali and Jakarta the only 6.2 Assessment of the RR-loan to exceptions, where housing loan growth slipped into funding ratio (RR-LFR) and negative territory at -3.21% and -1.08% respectively adjustments to the checking account services to meet the MSME for the period from June 2015 to June 2016. loan requirement

On the other hand, NPL crept above the 5% threshold in just two provinces, namely North Sumatra and Against a backdrop of sluggish bank intermediation, East Kalimantan at 5.47% and 5.38% respectively, Bank Indonesia adjusted the RR-loan to funding due to spillover from lower international policy (RR-LFR). The macroprudential policy move commodity prices that compromised the mining stimulated bank intermediation, encouraged the sector and supporting industries in both provinces. banks to seek alternative sources of funds to third- party deposits and helped deepen the financial Bank Indonesia strengthened LTV/FTV policy markets. The policy was refined by adding certain to stimulate domestic demand and create bank-issued securities to the calculation of the loan- economic growth momentum. Furthermore, to-deposit ratio (LDR), thereby expanding the ratio. Bank Indonesia focused policy on the property sector due to the sector’s large multiplier In practice, the policy has, thus far, failed to effect when catalysing economic growth. significantly reverse slower credit growth,

Table 6.4 NPL Growth of Property Loans for Flats/Apartments

June 2016 June 16 - Jun 15 Housing Loan NPL (%) Housing Loan NPL No. Province Annual Share of Share of Annual NPL + 2 Credit NPL + 2 Credit Credit Total Housing Total Credit NPL (%) Credit NPL (%) (%) (Rp, billions) (%) Growth (%) Loans (%) (%) Growth (%)

1 West Java 93,071 8.83 24.51 17.10 2.70 12.30 12,040 6.03 (0.31) (1.87) 2 Jakarta 63,366 (1.73) 16.69 4.73 2.18 8.79 (1,832) (1.08) 0.78 1.10 3 East Java 40,561 4.51 10.68 9.21 1.84 8.57 3,228 4.13 0.00 (1.09) 4 Banten 39,616 6.37 10.43 15.86 1.64 9.22 4,444 6.27 (0.11) (1.24) 5 Central Java 19,427 0.06 5.12 7.38 2.28 10.50 1,002 5.38 (0.31) (1.23) 6 North Sumatera 14,084 (0.99) 3.71 7.94 5.47 15.02 83 1.58 0.44 (0.66) 7 South Sulawesi 13,191 (1.08) 3.47 12.25 3.98 14.49 649 6.26 (0.23) (2.59) 8 Bali 12,450 6.47 3.28 14.96 1.45 6.84 393 (3.21) 0.67 1.60 9 East Kalimantan 8,067 (1.49) 2.12 7.62 5.38 16.46 349 6.01 1.10 0.91 10 South 8,040 10.44 2.12 16.55 3.84 15.57 814 0.83 0.09 (1.63) Kalimantan Subtotal 311,873 7.28 82.13 9.28 2.55 10.79 21,172 0.82 0.12 (0.69) Other Provinces 67,846 9.22 17.87 8.44 3.20 12.70 5,725 2.75 (0.15) (1.66) Total 379,719 7.62 100.00 9.12 2.67 11.13 26,896 1.16 (0.07) (0.85)

Source: Bank Indonesia

173 FINANCIAL STABILITY REVIEW No. 27, September 2016

decelerating from 10.38% (yoy) in the first semester target ratio through non-oil and gas export loans. of 2015 and 10.45% (yoy) at yearend 2015 to 8.89% (yoy) at the end of the first semester of 2016. On In general, MSME loan growth accelerated from the other hand, deposit growth also slowed over 6.78% (yoy) in the first semester of 2015 and 8.01% the same period, from 12.65% (yoy) and 7.26% (yoy) at yearend 2015 to 8.28% (yoy) at the end of (yoy) to 5.90% (yoy), which represents a deeper the first semester of 2016. By loan type, growth decline than credit growth. Furthermore, the of non-KUR loans actually decelerated, while other components of funding, such as securities, People’s Business Loans (KUR) grew significantly, have not taken off significantly, leading to LDR which prevented a deeper MSME credit decline. and LFR ratios in the banking industry that were Accordingly, non-KUR loans declined by Rp18 higher than when the RR-LFR was introduced. trillion, while KUR loans enjoyed a Rp54.8 trillion surge. Nonetheless, relatively high MSME credit risk The RR-LFR was also utilised to stimulate lending remained, despite moderating from 4.65% in the to micro, small and medium enterprises (MSME). first semester of 2015 and 4.20% at yearend 2015 Effective since 1st August 2015, Bank Indonesia to 4.58% at the end of the first semester of 2016. loosened the LFR ceiling from 92% to 94% for banks achieving the MSME lending target in Adjustments to the RR-loan to funding ratio (RR- advance of the requirements, while maintaining LFR) were part of the Bank Indonesia policy loan quality. In contrast, banks failing to meet the mix. In the monetary sector, Bank Indonesia MSME lending ratio faced sanctions in the form of eased policy through reductions to the limited checking account services, commencing in policy rate and primary reserve requirement, February 2016. Foreign banks and joint-venture which aimed to bolster bank liquidity and, banks are permitted, however, to meet the MSME therefore, stimulate national economic growth.

Graph 6.5 Bank Intermediation

4,400 29

4,300 28 4,200

4,100 27

4,000 26 3,900

3,800 25

3,700 24 3,600

3,500 23 3 4 1234 1234 1234 1234 1234 1234 1234 1234 1234 1234 1234 3 4 1234 1234 1234 1234 1234 1234 1234 1234 1234 1234 1234

Jul-15 Aug-15 Jan-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 Mar-16 Jun-16 Jul-15 Aug-15 Jan-15 Oct-15 Nov-15 Dec-15 Jan-16 Feb-16 Mar-16 Apr-16 Mar-16 Jun-16

LFR LDR Deposits Credit Bank-Issued Securities (rhs)

Source: Bank Indonesia Source: Bank Indonesia

174 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 6.6 MSME Credit Growth and NPL Graph 6.7 MSME Loans

Credit Growth NPL MSME Credit ≥ 5% 100 98 102 102 102 25.0% 5.0%

40 37 38 42 45

20.0% 4.0%

60 61 64 60 57 15.0% 3.0%

10.0% 2.0% MSME Credit ≥ 5% 20 18 16 16 16 9 8 9 5.0% 1.0% 12 12 10 11 7 4 4 Jun-14 Jun-15 Jun-16 Jun-14 Jun-15 Jun-16 Sep-14 Sep-15 Sep-14 Sep-15 Dec-13 Dec-13 Dec-14 Dec-15 Dec-14 Dec-15 Mar-14 Mar-15 Mar-16 Mar-14 Mar-15 Mar-16 NPL of Total Credit and MSME Loans ≥ 5%

MSME Non-MSME Non-MSME NPL of Total Credit and MSME Loans < 5%

Source: Bank Indonesia Source: Bank Indonesia

Optimising the looser monetary policy stance, The monetary and macroprudential policy mix Bank Indonesia honed macroprudential policy by is expected to strengthen efforts to stimulate raising the floor of the RR-loan to funding ratio domestic demand and, thus, economic growth (RR-LFR) from 78% to 80%, effective from 24th momentum, while maintaining macroeconomic August 2016, in order to catalyse credit growth. stability despite global economic moderation.

Graph 6.8 Looser Monetary Policy, Bank Liquidity and Credit Growth

8.25% 8.00% 7.75% 7.50% 7.25% 7.00% 6.75% 6.50% 6.25% 25.0% 22.5% 20.0% 17.5% 15.0% 12.5% 10.0% 7.5% Des-14 Des-15 Sep-14 Sep-15 Mar-15 Mar-16 Jun-14 Jun-15 Jun-16 Des-13 Mar-14

Primary RR BI Rate LA/Deposits Credit Growth

Source: Bank Indonesia

175 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 6.9 Ceiling and Floor of the RR-Loan to Funding Ratio (RR-LFR)

24 August 16 80% 92% LFR 3 August 15 78% 92%

31 December 13 78% 92% LDR

1 March 11 78% 100%

Source: Bank Indonesia

economic indicators, banking indicators and asset 6.3 Setting the Countercyclical Capital price indicators2, which confirmed that the national Buffer (CCB) Rate at 0% economy currently remains in a decelerating phase.

Bank Indonesia set the countercyclical capital Leading Indicator buffer (CCB) at 0% in May 2016 for the second time The leading indicator and anchor of the since issuing the CCB regulation1. The decision was countercyclical capital buffer (CCB), namely the based on the leading indicator, namely the credit- credit-to-GDP gap, continued to decrease. Since to-GDP gap, which signalled no excessive credit the third quarter of 2014, the leading indicator growth and was corroborated by other supporting has signalled low risk of excessive credit growth. indicators, consisting of macroprudential indicators, Therefore, Bank Indonesia has set the CCB rate at 0%,

Graph 6.10 Credit-to-GDP Gap Graph 6.11 CCB Rate per the Leading Indicator

10 2.50

8 2.00 High risk of Excessive Credit Growth 6 1.50

4 Risk of Excessive Credit Growth 1.00

2 0.50 Low Risk of Excessive Credit Growth 0 0.00

-2 2004Q2 2004Q4 2005Q2 2005Q4 2006Q2 2006Q4 2007Q2 2007Q4 2008Q2 2008Q4 2009Q2 2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 2015Q2 2015Q4 2016Q2 2004Q2 2004Q4 2005Q2 2005Q4 2006Q2 2006Q4 2007Q2 2007Q4 2008Q2 2008Q4 2009Q2 2009Q4 2010Q2 2010Q4 2011Q2 2011Q4 2012Q2 2012Q4 2013Q2 2013Q4 2014Q2 2014Q4 2015Q2 2015Q4 2016Q2

Crisis Credit-to-GDP Gap L H

Source: Bank Indonesia Source: Bank Indonesia

1 Bank Indonesia Regulation (PBI) No. 17/22/PBI/2015, dated 23rd December 2015, concerning the Countercyclical Capital Buffer (CCB) 2 The CCB is determined by the leading indicator, supporting indicators and professional judgement. The considerations underlying the selection of indicators is detailed in FSR No. 24, March 2015.

176 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

considering the current slowdown of credit growth ii. Macroeconomic Indicators despite a slight recovery at the end of the first quarter At the end of the second quarter of 2016, GDP of 2016 to 8.71% (yoy), while GDP growth achieved growth recovered to 5.18% (yoy) from 4.92% 4.91% (yoy) in the same period. Such conditions (yoy) in the previous period. Meanwhile, inflation persisted into the subsequent period, although decelerated over the same period from 4.45% to economic growth was observed to accelerate. 3.45%. Other macroeconomic indicators include the exchange rate and external debt. The rupiah Supporting Indicators appreciated slightly during the first half of 2016, In general, the information obtained from the while the growth of external debt slowed as supporting indicators showed that the Indonesian demand for foreign loans to support economic economy is currently experiencing a slowdown, activities subsided. which supports the leading indicator as follows: The macroeconomic indicators showed that the i. Macroprudential Indicators economy is currently recovering. Therefore, The financial cycle in Indonesia remains ina the CCB rate of 0% would not encumber the contractionary phase as illustrated in Graph 6.12. banking industry when supplementing capital. The contraction was caused by a credit slump as Consequently, the banking sector could focus on a major component of the financial cycle. The intermediation to stimulate economic growth. slowdown, however, was also indicative of no potential systemic risk originating from excessive credit growth.

Graph 6.12 Financial Cycle and Business Cycle

1995Q2Q 1998Q2 2007Q2 0.08 0.02

0.06 0.01 2005Q2Q 0.04 2013Q3Q 0.01 0.02

(0.02) (0.01) 2006Q3 2007Q2 2005Q1 2005Q4 2010Q2 2011Q1 2011Q4 2014Q1 2014Q4 2015Q3 2016Q2 2009Q3 2008Q1 2008Q4 1993Q4 1994Q3 1995Q2 1996Q1 1996Q4 1997Q3 1998Q2 1999Q1 1999Q4 2000Q3 2001Q2 2002Q1 2002Q4 2003Q3 2004Q2 2012Q3 2013Q2

(0.04) (0.01) 2009Q3Q (0.06)

(0.02) (0.08) 2000Q2Q

(0.10) (0.02) 1999Q2 2009Q3

Financial Cycle (rhs) Bsuiness Cycle (rhs) Financial Cycle Peak Financial Cycle Trough Crisis

Source: Bank Indonesia

177 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 6.13 Real GDP Growth Graph 6.14 Inflation (yoy)

8.0 18 7.0 14 6.0 12

5.0 10 8 4.0 6 3.0 4 2.0 2 1.0 0 2001Q2 2002Q1 2002Q4 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2 2010Q2 2011Q1 2011Q4 2011Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3

Real GDP (yoy) Crisis CPI (yoy) Crisis

Source: Bank Indonesia Source: Bank Indonesia

Graph 6.15 USD/IDR Exchange Rate Graph 6.16 Private External Debt in Rupiah (yoy)

15500 50

14500 40 30 13500 20 12500 10 11500 0 -10 10500 -20 9500 -30 8500 -40 7500 -50 2002Q1 2002Q3 2003Q1 2003Q3 2004Q1 2004Q3 2005Q1 2005Q3 2006Q1 2006Q3 2007Q1 2007Q3 2008Q1 2008Q3 2009Q1 2009Q3 2010Q1 2010Q3 2011Q1 2011Q3 2012Q1 2012Q3 2013Q1 2013Q3 2014Q1 2014Q3 2015Q1 2015Q3 2016Q1 2001Q2 2002Q1 2002Q4 2002Q4 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2

Exchange Rate (USD/IDR) Crisis Private External Debt (yoy) Crisis

Source: Bank Indonesia Source: Bank Indonesia

iii. Banking Indicators Slower credit growth reduced potential systemic The impact of bank lending procyclicality in the risk from excessive bank lending. Weaker deposit economy was reflected by deteriorating banking growth was attributed to the economic downturn, industry performance and economic moderation. which squeezed corporate and household The bank intermediation function, namely credit and performance. The economic slowdown also deposit growth, continued to slow. Furthermore, undermined borrower repayment capacity to the credit quality tended to decline in line with higher banks, thus elevating the gross NPL ratio, leading to NPL and profitability (ROA) decreased. relatively stagnant bank profitability (ROA) at 2.26% during the first semester of 2016.

178 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Graph 6.17 Annual Credit Growth Graph 6.18 Annual Deposit Growth

40 25 35 30 20 25 15 20 15 10 10 5 5 0 0 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2014Q3 2016Q2 2001Q2 2002Q1 2002Q4 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2 2002Q1 2002Q4 2003Q3 2004Q2 2005Q1 2005Q4

Credit (%yoy) Crisis Deposit Growth (yoy) Crisis

Source: Bank Indonesia Source: Bank Indonesia

Graph 6.19 Non-Performing Loans (%) Graph 6.20 Return on Assets (%)

20 4

15

3 10

5 2 0

-5 1 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2 2001Q2 2002Q1 2002Q4 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2

ROA (%) Crisis NPL (%) Crisis

Source: Bank Indonesia Source: Bank Indonesia

Notwithstanding, the banks maintained a high iv Asset Price Indicators and stable Capital Adequacy Ratio (CAR), which Consistent with economic moderation and slower was indicative of less lending and, therefore, bank credit growth, JCI volatility was comparatively demonstrates the vast untapped potential to stable during the reporting period, reflecting low increase the intermediation function. Furthermore, pressures on the capital market. Consequently, a the persistently high CAR to absorb risk also CCB rate of 0% was appropriate to the prevailing obviated the need for additional capital buffers, so conditions. the CCB rate was set at 0% again in the reporting period.

179 FINANCIAL STABILITY REVIEW No. 27, September 2016

Graph 6.21 Capital Adequacy Ratio (%) Graph 6.22 JCI Volatility

30 0.25

0.20 25

0.15 20

0.10

15 0.05

10 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2 2001Q2 2002Q1 2002Q4 2003Q3 2004Q2 2005Q1 2005Q4 2006Q3 2007Q2 2008Q1 2008Q4 2009Q3 2010Q2 2011Q1 2011Q4 2012Q3 2013Q2 2014Q1 2014Q4 2015Q3 2016Q2

CAR (%) Crisis JCI Volatility Crisis

Source: Bank Indonesia Source: Bank Indonesia

Broad cooperation and coordination exists between 6.4. Policy Coordination between BI and OJK, covering: (i) task implementation at Bank Indonesia and the Other both institutions; (ii) information exchange as Authorities well as management of the bank and finance In response to the global and domestic economic company reporting system by BI and OJK; (iii) use developments and challenges faced, Bank Indonesia of Bank Indonesia’s assets and documentation by proactively coordinated with other authorities to OJK; and (iv) management of the BI officers and maintain financial system stability and monetary employees assigned to OJK pursuant to the BI- stability in line with fiscal and microprudential policy, OJK Joint Decree signed on 18th October 2013. thereby creating synergy to stimulate sustainable economic growth based on economic fundamentals. In the first semester of 2016, particularly in the second quarter, coordination between Bank The main role of the BI ex-officio member at both Indonesia and the Financial Services Authority institutions is to bridge coordination and cooperation (OJK) focused on several implementation guidelines between the authorities. In more detail, the ex- as a follow-up to the Financial System Crisis officio members at OJK and LPS are tasked with3: (i) Prevention and Handling (PPKSK) Act, including delivering the principal and strategic policies and/ jointly determining systemically important banks or strategic view of Bank Indonesia; (ii) informing (SIB) and the coordination mechanism for the the BI Board of Governors of policies at the other Short-Term Liquidity Facility (PLJP). Meanwhile, institution that could influence the tasks, function coordination between Bank Indonesia and the or authority of Bank Indonesia; and (iii) supporting Deposit Insurance Corporation (LPS), as contained and facilitating coordination, cooperation and policy in the Memorandum of Understanding (MoU) harmonisation between the institutions involved. signed by BI and LPS, covers: (i) handling the

3 Bank Indonesia Board of Governors Regulation No. 17/5/PDG/2015, dated 9th July 2015, concerning the Duties of the Ex-Officio Member.

180 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

default of non-systemic banks by revoking the operating license; (ii) funding to maintain bank solvency; (iii) data and/or information exchange; (iv) developing staff competences; (v) conducting joint research, reviews and/or surveys; (vi) performing joint socialisation and/or education activities; (vii) assigning employees; and/or (viii) executing other duties pursuant to prevailing regulations, including support for the National Noncash Movement (GNNT), financial market deepening and broadening financial access.

In terms of the PPKSK Act, Bank Indonesia and the Deposit Insurance Corporation (LPS) are currently preparing a Cooperation Agreement to regulate the selling mechanism for LPS- held SBN to Bank Indonesia to resolve solvency issues at systemic banks and non-systemic banks under crisis conditions in the financial system.

In broader terms, the PPKSK Act (No. 9) of 2016, dated 15th April 2016, represents a solid foundation to strengthen coordination between the four members of the Financial System Stability Committee to prevent and resolve crises, namely the Ministry of Finance, Bank Indonesia, Financial Services Authority (OJK) and Deposit Insurance Corporation (LPS). Such coordination involves: (i) monitoring and maintaining financial system stability; (ii) handling financial system crises; and (iii) handling issues at systemic banks under normal and crisis conditions.

181 FINANCIAL STABILITY REVIEW No. 27, September 2016

Transmission of the BI 7-Day (Reverse) Repo Rate Box 6.1 to Bank Interest Rates

The BI Board of Governors decided on 21st used to control inflation, changes in economic April 2016 to reformulate the monetary policy fundamentals prompted several challenges to operational framework, to become effective monetary policy transmission in the economy. as of 19th August 2016. Accordingly, Bank On one hand, the BI Rate was persistently high in Indonesia replaced its policy rate, the BI Rate, response to heightened inflationary pressures. with the BI 7-Day (Reverse) Repo Rate. On the other hand, however, the overnight (O/N) interbank rate, as the operational target Pursuant to the Bank Indonesia Act, BI is charged of monetary policy, had declined significantly with creating and maintaining rupiah stability. due to a deluge of non-resident capital into This is achieved through monetary policy to the country after the global financial crisis in attain the inflation target. Since 2005, Bank 2009. Furthermore, after 2010, the BI Rate, Indonesia has applied the Inflation Targeting as the policy rate, had deviated from the O/N Framework (ITF) as a guide for monetary interbank rate, as the operational target of policy and the BI Rate was used as the policy monetary policy (refer to Box Graph 6.1.1). rate. Although the BI Rate was successfully

Box Graph 6.1.1 The development of interest rate policy and the operational target of monetary policy

Avg Interbank BI Rate DF O/N LF O/N (%) Day O/N (eop) (eop) (eop) 14 Dec 08 6.69 6.75 6.25 7.25 Sept 09 6.69 6.75 6.25 7.25 Dec 13 6.15 7.50 5.75 7.50 12 Dec 14 6.05 7.75 5.75 8.00 Dec 15 6.20 7.50 5.50 8.00 Jan 16 5.55 7.25 5.25 7.75 10 Feb 16 5.28 7.00 5.00 7.50 Mar 16 5.00 6.75 4.75 7.25

8

6

4

2

0 Jul -08 Jul -13 Jan -11 Jan -16 Jun -11 Oct -09 Oct -14 Feb -13 Apr -12 Sep -12 Dec -08 Dec -13 Nov -11 Mar -10 Mar -15 Aug -10 Aug -15 May -09 May -14

BI Rate DF O/N LF O/N Interbank O/N

Source : Bank Indonesia, processed

182 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

The monetary policy operational framework instrument requires a relatively deep market to was reformulated to strengthen the ensure it is referenced by the market because the effectiveness of monetary policy transmission instrument is attractive and, therefore, regularly and support financial market deepening. The transacted. In addition, the interest rate of the new operational framework was designed so reference instrument must correlate closely that the policy rate is transactional and has a with the operational target, other market rates greater influence over short-term interest rates and the foreign exchange market to guarantee on the money markets. Therefore, monetary effective monetary policy transmission. policy could be more effectively transmitted to longer-term interest rates and yields on The operational target must meet several financial markets, which would ultimately boost considerations underlying the monetary macroeconomic and real sector performance. operations rate selected as the policy rate. The change of policy rate, however, did not The rate selected as the operational target is imply a change to monetary policy stance, chosen as the reference rate by the markets and which remains consistent with achieving reflected by transaction volume and number of macroeconomic stability. market players transacting. To safeguard the effectiveness of monetary policy transmission, When selecting the new policy rate, Bank the central bank must maintain strong control Indonesia considered numerous factors, namely over the rate stipulated as the operational that the new rate should be transactional, target. Furthermore, the operational target have a deep market and close relationship must have clear transmission channels to other with the operational target of monetary market rates. The tenor of the rate used as policy. A transactional policy rate amplifies the operational target does not have to be the monetary policy signals and supports financial same as the tenor of the reference instrument. market deepening as transactional activities To ensure control and effective transmission, on financial markets increase. A policy rate however, the tenors of the reference rate that can be transacted through monetary and operation target should not be too operations between Bank Indonesia and market disparate. Based on the considerations, the players would also be a strong reference for overnight interbank rate was maintained as the price discovery and other financial market operational target. transactions. Furthermore, a reference

183 FINANCIAL STABILITY REVIEW No. 27, September 2016

Implementation of the BI 7-Day (Reverse) Repo market deepening, in particular transactions Rate was accompanied by normalisation of and interest rate structure formation, on the the interest rate corridor. The Lending Facility interbank money market for tenors of 3 – 12 and Deposit Facility continued to serve as the months. To that end, monetary operations upper bound (ceiling) and lower bound (floor) were strengthened in tandem with measures to of the interest rate corridor. LF and DF form a accelerate financial market deepening. symmetrical corridor either side of the BI 7-Day (Reverse) Repo Rate at 75bps respectively. Dalam upaya memperkuat kerangka Under the old monetary operational framework, operasi moneter tersebut, Bank Indonesia the LF was closer to the policy (BI) rate than akan mempercepat pelaksanaan program the DF, leading to an asymmetric corridor. pendalaman pasar keuangan. Langkah- Meanwhile, Bank Indonesia’s decision to select a langkah yang ditempuh antara lain mencakup: symmetrical corridor signalled its neutral stance (1) memperkuat peran suku bunga Jakarta to bank liquidity and, therefore, forced the Interbank Offered Rate (JIBOR) bagi banking industry to optimally manage liquidity terbentuknya struktur suku bunga di pasar uang in line with economic dynamics/demand. In untuk tenor dari overnight sampai dengan 12 addition, creating a symmetrical corridor by bulan; (2) mempercepat transaksi Repo dengan lowering the LF rate strengthened the position mendorong bank-bank berpartisipasi ke dalam of LF instruments as liquidity support for General Master Repo Agreement (GMRA); (3) banks in need of short-term liquidity. Reducing mengurangi segmentasi dan meningkatkan the cost of being illiquid is also expected to kapasitas transaksi pasar dengan mendorong provide space for banks to utilise longer-term perbankan untuk lebih membuka akses placements on the financial markets, which also counterparty. supports financial market deepening. Replacing the BI Rate with the BI 7-Day (Reverse) The three goals of strengthening the monetary Repo Rate did not change the monetary policy operational framework are as follows: policy stance maintained by Bank Indonesia, (i) Strengthening monetary policy signals by considering that both rates are part of the same utilising the BI 7-Day (Reverse) Repo Rate as interest rate structure of monetary operations. the main reference rate for other interest rates The policy rate was merely changed from the BI on the financial markets; (ii) Strengthening the Rate, equivalent to a tenor of 12 months, to the effectiveness of monetary policy transmission BI 7-Day (Reverse) Repo Rate, with a tenor of through its impact on money market rates and 7 days. The interest rate structure would only banking rates; and (iii) Promoting financial change if Bank Indonesia changed its monetary

184 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Box Graph 6.1.2 Interest Rate Corridor

8.25 19 Agustus 2016

7.75 New Policy Operational LF Rate 7.25% Framework

7.25

6.75

BI Rate 6.50% LF Rate 6.00% 6.25

DF Rate 4.50% 5.75 BI 7DDR 5.25% 75 Bps

5.25

DF Rate 4.50% 75 Bps 4.75

4.25

Jan 16 Feb 16 Mar 16 Apr 16 May 16 Jun 16 Jul 16 Aug 16

Old Monetary Policy Operational New Monetary Policy Operational Framework Framework Policy Rate BI Rate BI 7-Day (Reverse) Repo Rate

Reflected in MO Tenors 12 months 1 week

Standing Facilities LF (Ceiling), DF (Floor) LF (Ceiling), DF (Floor)

Corridor Asymmetric (50bps + 200bos) Symmetrical (75bps + 75bps)

Source: Bank Indonesia, processed

policy stance, as occurred in January, February, Strengthening the monetary policy operational March and June 2016. In contrast, in months framework, Bank Indonesia will accelerate when the monetary policy stance was not financial market deepening programs through changed, the term structure also remained the the following measures: (i) strengthening the same (Box Graph 6.1.3). role of the Jakarta Interbank Offered Rate

Box Graph 6.1.3 Interest Rate Term Structure (TS)

6.50% 6.40% 6.30%

6.10%

5.70% 5.45% 5.25% 1 Week 2 Weeks 1 Month 3 Months 6 Months 9 Months 1 Months

TS Jan’16 TS Feb’16 TS Mar’16 TS Jun’16

Source: Bank Indonesia, processed

185 FINANCIAL STABILITY REVIEW No. 27, September 2016

(JIBOR) to form the interest rate structure on the money market for tenors of overnight to 12 months; (ii) accelerating repo transactions by encouraging banks to participate in the Global Master Repurchase Agreement (GMRA); and (iii) reducing segmentation and enhancing market transaction capacity to help banks expand counterparty access.

Congruent with establishing the BI 7-Day (Reverse) Repo Rate as the new policy rate at the BI BOG meeting in August 2016, Bank Indonesia will continue to publish the interest rate structure of monetary operations. For the time being, however, to support interest rate guidance for the markets, monetary operations will continue to apply fixed rate tenders (FRT) for auctions of all monetary instrument tenors. Gradually, however, FRT will be replaced with the variable rate tender (VRT) mechanism.

186 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

Financial Sector Assessment Program: Maintaining Box 6.2 Global Financial Stability

Background financial system stability. FSAP was initiated in Maintaining financial system stability has caught 1999 by the International Monetary Fund (IMF) the attention of policymakers for a long time. and World Bank after lessons from financial This has become increasingly important in the crises evidenced a contagion effect from the global financial system, which has demonstrated financial sector in one country to another. FSAP greater interaction between economic sectors is, therefore, a comprehensive mechanism to and progressively more complex systems. assess financial sector stability and soundness as An example of two-way interaction between well as the potential contribution to economic performance and soundness is the financial development and growth. sector with the macroeconomy and real sector. The financial sector of a country is assessed The 2007/2008 global financial crisis in order to identify the main fragilities and strengthened confidence in the close links vulnerabilities of a financial system. The early between the financial sector and economic identification of such exposures, particularly performance in general. The crisis proved potential systemic risk and interconnectedness that disruptions/shocks in the financial sector between economic sectors, is expected to could spill over and undermine macroeconomic enhance a jurisdiction’s ability to better mitigate performance. The relationship has become risk and, therefore, prevent financial system more complex as the global economy has instability. become more integrated. Exploiting greater integration has, however, also increased cross- To assess the stability and soundness of a border spillover. Therefore, the development of financial sector, FSAP evaluates three key areas. a comprehensive surveillance framework and First, the sources, probabilities and potential globally agreed policy is expected to minimise impacts of the main risks to near-term financial the risks, while promoting a more structured system stability. Second, the financial stability global financial system. policy framework. In this case, the resilience of the banking sector and other nonbank FSAP Framework financial sectors is assessed, including using The Financial Sector Assessment Program, stress tests, analysis of interconnectedness otherwise known as FSAP, is a program run by between financial institutions as well as international organisations to maintain global cross-border spillover. The microprudential

187 FINANCIAL STABILITY REVIEW No. 27, September 2016

and macroprudential policy frameworks required to routinely take part in FSAP every are also assessed, along with the quality of five years. That total was increased to 29 in 2013 supervision over banks and nonbanks, as well as based on several criteria, including the size of supervision of financial market infrastructures the financial sector and interconnectedness and conformity to international standards. with financial sectors in other countries. Third, capacity of the relevant authorities to manage and mitigate financial crises if the Although FSAP is not mandatory, considering risks materialise. To that end, the supervisory the huge benefits in the national and global authority, regulator and policymakers are interest, numerous countries participate in FSAP. assessed in terms of their ability to respond to Since its introduction in 1999, approximately systemic pressures in the financial sector, while 150 countries have participated. In fact, many simultaneously implementing the financial jurisdictions have assessed their financial sector safety net. twice under FSAP. Currently, G20 member states, including Indonesia, are committed to In addition to assessing aspects of stability, periodic evaluations under FSAP. FSAP also evaluates aspects of financial sector development. Each jurisdiction assesses its FSAP in Indonesia requirements for further financial sector Indonesia first conducted FSAP in 2009/2010. development in terms of the institutions, Furthermore, congruent with commitment to markets, infrastructure and inclusiveness. The routine assessments, Indonesia will perform its assessment intends to capture quality aspects second FSAP assessment in 2016/2017. of the payment system legal framework, constraints to competitiveness, financial sector Increasing national coordination to improve efficiency, financial inclusion and the sector’s a more effective FSAP, while mitigating the contribution to economic development. various risks, especially reputational risk and financial risk, the National FSAP Task Force was FSAP Participants set up through coordination with the Financial All countries are eligible to request participation Services Authority (OJK). The team consists of in the FSAP assessments. In 2010, however, members from the Ministry of Finance, Bank the IMF designated 25 countries as having Indonesia, Financial Services Authority (OJK) a systemically important financial sector, and Deposit Insurance Corporation (LPS) and from which contagion could spread to other is made up of seven functional sub-teams, the jurisdictions. The 25 countries, therefore, are Communication and Socialisation Sub-Team

188 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

and the Secretariat. The seven functional sub- teams include Risk Analysis and Stress Testing; Macroprudential Policy; Liquidity Management; Microprudential Surveillance; Financial Safety Net, Crisis Management and Resolution; Financial Deepening; as well as Financial Inclusion.

189 FINANCIAL STABILITY REVIEW No. 27, September 2016

Financial Market Development and Deepening Boks 6.3 Coordination Forum (FK-PPPK)

Deep, active, liquid, inclusive and efficient amnesty. Fourth, the role of intermediaries financial markets are vitally important to on financial markets must be strengthened, increase the availability of development particularly the role of primary dealers/brokers funds through financial market mechanisms, to increase liquidity and improve efficiency to enhance the effective implementation of when setting prices. Fifth, market infrastructure various fiscal and monetary policies as well as development is required, including a trading to provide a means of managing liquidity and platform, central counterparty (CCP), custody risks. as well as an integrated and efficient automated settlement process. Sixth, the regulations Financial market development in Indonesia across different authorities must be refined and unfortunately lacks behind that of other peer harmonised. countries, leaving six aspects to be addressed immediately. Considering that the financial markets in Indonesia are diverse and fall under the First, the issuers of financial instruments need supervisory auspices of various authorities, any to be addressed through efforts to enhance efforts to accelerate market development and efficiency and expand issuances of securities. deepening require a common understanding Second, improvements are required in terms and close coordination between the relevant of the investors through efforts to expand the authorities. Consequently, Bank Indonesia, domestic investor base, including institutional OJK and the Ministry of Finance have signed investors (pension funds, insurance industry, a Memorandum of Understanding (MoU) investment managers) and retail investors. concerning Coordinated Financial Market Third, greater diversity of investment Development and Deepening to Support instruments on the money market and foreign National Development Financing. exchange market is required. In addition to expanding the range of instruments available, The goal of the MoU is to coordinate and more hedging instruments are also urgently synergise task implementation and the required. Bank Indonesia is gradually issuing jurisdiction of each respective authority in measured regulations concerning derivative terms of formulating a national financial transactions for use as hedging instruments market development and deepening strategy and in response to increased inflow to domestic to support national development financing. The markets because of the recently enacted tax

190 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

MoU covers three main areas. First, coordinated Several meetings have been held since the financial market development and deepening Memorandum of Understanding (MoU) was through cooperation to plan and accelerate signed on 8th April 2016 to prepare the work policy implementation. Second, data and program, including the formation of a working information exchange towards harmonisation, group and agreeing several priority topics for including the financial market development discussion at the high-level meetings. The and deepening work program as well as meetings are held at least twice annually to relevant laws and regulations. Third, propose exchange ideas and discuss various national recommendations to overcome the financial development financing issues along with efforts market development and deepening problems to develop the financial markets in Indonesia. faced by the institutions/authorities. The forum’s current priority is unifying the

Box Figure 6.3.1 FK-PPPK Organisational Structure

Steering Committee Minister of Finance, BI Governor, OJK Chairman

IMPLEMENTATION TEAM

SECRETARIAT

Working Group – Working Group – Instruments and Working Group – Infrastructure and Policy Harmonisation Investor Base Institutions

Chair: MoF Chair: OJK Chair: BI Co-Chair OJK Co-Chair BI Co-Chair MoF

Source: Bank Indonesia

191 FINANCIAL STABILITY REVIEW No. 27, September 2016

visions of the three leading authorities through preparation of a National Financial Market Development Strategy/Roadmap.

Next, Central Counterparty Clearing (CCP) must be established to increase transactions and reduce risks on the financial markets, which also reflects Indonesia’s commitment per the G20 Pittsburgh Summit in September 2009, while also honing regulations that hinder financial market development (for example, taxes on repo transactions).

192 Households Bank Indonesia Policy Financial System The Financial and The Corporate Banks and Nonbank Strengthening Financial Response to Support Financial Stability Markets Sector Financial Institutions System Infrastructure System Stability

193 ARTICLE 1 Systemic Risk Measurement Framework Article 1 Systemic Risk Measurement Framework

ARTICLE 1 Systemic Risk Measurement Framework Cicilia A. Harun1, Sagita Rachmanira2, dan Raquela Renanda3

Systemic risk cannot be mitigated using a single varies depending upon the interests of the research indicator or method alone but requires comprehensive or policy implementation. In general, however, measurement tools. To that end, Bank Indonesia systemic risk can be defined from three different developed a systemic risk measurement framework perspectives or a combination of the three, namely: (i) to identify, monitor and measure risk as a reference the magnitude of risk sources, for example, a sudden for macroprudential supervision and policymaking, shock and the probability of systemic risk occurring; including the future development of systemic risk (ii) the risk formation (transmission) process, such as measurement tools. In this paper, a systemic risk the interconnectedness of financial system elements measurement framework is proposed covering three and the contagion/domino effect; and (iii) the impacts main aspects, namely: (i) the types of measurement that emerge, including the impact of systemic risk on tools; (ii) the dimensions of the measurement tools; the economy and a loss of confidence. and (iii) the measurement tools based on the phases of systemic risk formation. In addition, the paper also Group-of-Ten discussions concerning systemic risk discusses the formation of systemic risk in the context in 2001 are a solid example of systemic risk defined of the financial cycle. In general, sound measurement from the viewpoint of risk sources and the impacts tools are expected to detect signals of imbalances and that emerge. At the discussions, the G-10 defined evaluate potential losses. systemic risk as risks that can erode economic value or confidence and increase uncertainty in the financial JEL Classification: E58, G01 system, thus potentially undermining the economy. Keywords: systemic risk, measurement of systemic Systemic risk can accumulate suddenly and without risk, macroprudential warning, or build up gradually in the absence of an appropriate policy response. The fallout of systemic 1. Introduction risk on the economy can be seen through an increasing Systemic risk is potential instability originating number of payment system shocks, credit flows and from contagion in part or all of the financial system lower asset prices. Referring to those discussions, due to interactions of size, business complexity systemic risk mitigation efforts became the primary interconnectedness between institutions and/or focus of maintaining financial system stability. In financial markets as well as procyclicality4. According to addition, there are at least two other supporting several research papers, the definition of systemic risk arguments. First, financial fragility in the financial

The opinions expressed in this paper do not represent the monetary policy stance of Bank Indonesia. The authors are responsible for any unintentional errors. 1 Senior Economic Researcher, Macroprudential Policy Department, Bank Indonesia. Email: [email protected] 2 Economic Researcher, Macroprudential Policy Department, Bank Indonesia. Email: [email protected] 3 Research Fellow, Macroprudential Policy Department, Bank Indonesia. Email: [email protected] 4 Per the definition contained in Bank Indonesia Regulation (PBI) No. 16/11/PBI/2014 concerning Macroprudential Regulation and Supervision

195 FINANCIAL STABILITY REVIEW No. 27, September 2016

system to systemic risk. Second, financial crisis a single indicator but requires several supporting experience, especially Indonesia’s financial system indicators. Systemic risk mitigation is also similar. after the 1997/98 Asian Crisis and the 2008 Global To prevent a build-up of systemic risk, a range of Financial Crisis (GFC). monitoring indicators are required along with systemic risk measurement methods and tools that can detect In response, financial authorities in various jurisdictions signals of imbalances and evaluate potential losses. began to prioritise efforts to enhance the resilience of This is congruent with the research findings of the Basel financial institutions and financial markets as well as Committee on Banking Supervision (BCBS) (2012), efforts to limit the build-up of systemic risk in order namely that there is currently no comprehensive to prevent further crises. This was accompanied by quantitative method (model) to measure systemic risk the development of a macroprudential approach to in the financial system, apart from the models and maintaining financial system stability. Macroprudential methods that assess one or more aspects of systemic policy instruments, as complements to monetary and risk separately. microprudential policy, began to appear in various countries with the ultimate goal of minimising systemic Such discussions have led to various studies and risk. Meanwhile, the authorities also began to develop reviews to identify monitoring indicators and methods/ a macroprudential approach to supervision in order to tools to measure systemic risk. The main contribution enhance the resilience of financial institutions. of the reviews has been to produce a systemic risk identification, monitoring and measurement Similar developments occurred in Indonesia’s framework as a reference for macroprudential financial system. As the macroprudential authority, supervision and policymaking at Bank Indonesia, Bank Indonesia formulates macroprudential policy otherwise known as the systemic risk measurement and performs macroprudential supervision with the framework. Identification is a necessary element as a overarching goal of mitigating systemic risk. To that reference when developing future indicators as well end, the series of activities required are contained as methods/tools. The reference is required to ensure in the Macroprudential Policy Framework (Harun systemic risk is measured using appropriate indicators & Rachmanira, 2013; Harun & Rachmanira, 2015). and methods, thus avoiding erroneous interpretations Pursuant to that policy framework, systemic risk is – such as bias, over-estimation or underestimation – mitigated through an operational macroprudential of systemic risk building up in the financial system. supervision strategy that includes monitoring, stress Systemic risk measurement errors can also appear identification, risk assessment and risk signalling; if the assessment scope is inadequate to draw as well as the development of appropriate policy conclusions about systemic risk. instruments.

Differing from monetary policy that has a measurable policy target (for instance the exchange rate and interest rates) and indicators, achieving financial system stability cannot be measured merely using

196 Article 1 Systemic Risk Measurement Framework

2. Characteristics of Systemic Risk Measurement Tools increasingly popular among financial authorities and In their research, Blancher et al (2013) defined a systemic financial institutions, to measure the gap between risk formation process consisting of three phases, potential losses under stress conditions or default to with each phase requiring a different measurement risk absorption ability, is the liquidity or capital buffer. In tool. The first phase is the build-up of systemic risk this second phase, the most commonly used methods and a symptom is overheating in the financial system, to measure systemic risk in the financial system by denoted by an asset price boom, persistently high financial authorities and financial institutions are credit growth or rapid financial innovation. Systemic known as loss given default or stress testing. risk measurement tools in this first phase focus on assessing the probability of systemic impacts and early The third and final phase is referred to as amplification warning indicators to detect the onset of financial and propagation as the crisis impacts spread between crisis. The methodology’s characteristics in the first financial institutions, financial markets and other phase are to focus on certain economic sectors in the sectors and even to financial systems in other financial system or focus on certain indicators that countries. The systemic risk measurement tools in represent profit-taking behaviour by market players. this phase focus on interconnectedness and exposure An example measurement for the first phase is the concentration in the financial system, potential probability of a crisis occurring using the credit-to- fire sales of financial assets and an assessment of GDP ratio to assess the financial cycle. cross-border exposures. In other words, the most appropriate measurement methods are: (i) an The second phase is when the shock has materialised. assessment of the systemic impact of default of one This phase represents the onset of a crisis, signified by element in the financial system, known as systemic shocks/pressures in the financial system (for example, impact analysis; and (ii) an assessment of losses due a GDP/fiscal ratio shock, exchange rate pressures, to contagion (contagion analysis). property price pressures, default at a systemically important financial institution - SIFI). Measurement In other research (Gunadi et al, 2014), the tools at this phase focus on assessing potential losses transmission of systemic risk is explained from a in the financial system and real sector assuming stress different perspective, namely through the balance or default. An assessment method that is becoming sheet, financial market, real sector, infrastructure

Article Figure 1.1 Phases of Systemic Risk

Amplification and Propagation

Shock Materialisation

Systemic Risk Build-up Phase

Source: Blancher et al (2013)

197 FINANCIAL STABILITY REVIEW No. 27, September 2016

and market confidence channels (refer to Article indicators, the infrastructure channel uses payment Figure 1.3). Furthermore, the measurement tools system indicators, and the market confidence channel are identified using the indicators available in each uses consumer confidence indicators obtained from respective systemic risk propagation channel. For surveys. example, the balance sheet channel uses the balance sheets of financial institutions, the financial market Pursuant to prevailing theory, discussions on the channel uses price index indicators, the real sector characteristics of systemic risk measurement tools channel uses corporate and household performance can be explained using two approaches, namely

Article Figure 1.2 Systemic Risk Transmission

SHOCK SOURCE

External Domestic

• Exogenous • Common/systematic • Endogenours • Idrosyncratic

CHANNELS

Transmission Period: Balance Financial Real Market Transmission Analys : • Short Term Sheet Market Sector Confidence Infrastructure • Short Term • Long Term • Long Term

Transmission Risk Transmission Credit Liquidity Market Operational Measurement can be Risk Risk Risk Risk Phase : based on: • Build Up Period • Size • Risk • Interconnetedness Materialization- • Complexity Period

Effect on Bank Landing

Systemic Risk

Potential Impact

Temporary Structural

(Gunadi.et.all.2014)

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monitoring indicators and measurement methods/ economic activity, when expanding or contracting. tools as follows: One example of a procyclical indicator is procyclical bank credit growth with the economic cycle. 2.1. Monitoring Indicators b. Countercyclical indicators are indicators that move Indicators represent a means to monitor conditions in the opposite direction to the business cycle or and developments. In terms of maintaining financial aggregate economic activity. system stability through systemic risk mitigation, c. Acyclical indicators are indicators that move indicators can be used to monitor and identify signals without a clear correlation to the business cycle. of imbalances in the macroprudential supervision Such indicators are rare because they often cannot process, or to monitor the implementation of explain behaviours and conditions in the financial macroprudential policy instruments. Therefore, clear system. understanding of the indicators will influence the accuracy of supervision and appropriateness of policy Time-Based Monitoring Indicators implementation. Based on the interpretation time, namely by comparing turning point (peak and trough) indicators Per Wolken (2013), indicators used to identify the to the turning points of the business cycle, Abel build-up of systemic risk should meet the following and Bernanke (2001) grouped indicators into three requirements: (i) relevance, the indicators should categories as follows: be able to accurately illustrate conditions in the real a. Leading indicators are indicators that tend to move economy and financial system; (ii) collectable, the before the aggregate economy moves, implying that indicators should be used continuously in the long the peaks and troughs of the indicator occur prior term; (iii) comprehensive and dynamic, the indicators to the peaks and troughs of the aggregate economy. should cover the entire financial system but also An example of a leading indicator is market return, adjust over time; (iv) forward looking, the indicators which will decline before the economy slows and should be early warning indicators in order to provide vice versa. In terms of utilisation, leading indicators sufficient time for the authorities to take action; and are used to predict future economic trends as early (v) accurate, the indicators should transmit signals warning indicators. with the smallest error possible, including erroneous b. Coincident indicators are indicators with peaks signals. In more detail, the discussion on the and troughs that coincide with the peaks and characteristics of systemic risk monitoring indicators is troughs of the business cycle. Differing from presented as follows: leading indicators, coincident indicators provide information on current economic conditions. Direction-Based Monitoring Indicators c. Lagging indicators are indicators with peaks and Abel and Bernanke (2001) grouped indicators based troughs that lag behind the peaks and troughs of on direction, using the business cycle as a reference the business cycle. For example, corporate profit as follows: is an indicator of corporate performance and a. Procyclical indicators are indicators that move in the unemployment typically changes several periods same direction as the business cycle or aggregate after changes in the business cycle.

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Determinant-Based Monitoring Indicators mechanisms, namely imbalances (Caballero, 2009), Based on the processes that form them, the indicators spillover to the real economy (G-10, 2001), correlated can be categorised as single indicators or composite exposure (Acharya, Pedersen, Philippon and indictors. Richardson, 2010), information disruptions (Mishkin, a. Single indicators are created based on data using 2007), asset price bubbles (Rosengren, 2010), and simple management methods. In general, single feedback behaviour (Kapadia, Drehmann, Elliott and indicators are used to detect a movement or specific Sterne, 2009). condition in the financial system. An example of a single indicator is the NPL ratio as a proxy of credit The variety of mechanisms used to measure systemic risk, and the liquid assets to deposits ratio as an risk demonstrates that more than one measurement indicator of liquidity risk. is required to capture the complexity of the financial b. Composite indicators are formed by combining system. Therefore, a robust framework is required several indicators based on a given model (OECD, to supervise and control financial system stability 2008). Composite indicators can detect the that combines several perspectives and continuous interaction of single indicators, thus illustrating processes to evaluate the constantly developing interactions between sectors in the financial financial system and systemic risks that adapt to system (Gadanecz & Jayaram, 2009). The use of changes in the financial system. Several other central several indicators as a composite indicator normally banks have developed analysis frameworks to measure applies weights and is calculated in the form of an systemic risk, such as the Risk Assessment Model of index. An example of a composite indicator is the Systemic Institutions (RAMSI) developed by the Bank of Financial System Stability Index (FSSI), which is used England, the Systemic Risk Model (SRM) developed by by Bank Indonesia to evaluate financial system the Oesterreichische Nationalbank (OeNB) in Austria, stability in terms of macroprudential supervision. the Macro Financial Risk Assessment Framework (MFRAF) developed by the Bank of Canada, and the 2.2. Measurement Method Systemic Risk Assessment Model for Macroprudential In addition to monitoring indicators, policymakers Policy (SAMP) developed by the Bank of Korea (BoK). can also mitigate the build-up of systemic risk 3. The Systemic Risk Measurement Framework at Bank using measurement tools/methods. Systemic risk Indonesia measurement methods/tools represent models The Systemic Risk Measurement Framework (KPRS) developed to observe the potential impacts that represents part of the general Macroprudential Policy could emerge from risk. Examples of systemic risk Framework. In general, the KPRS at Bank Indonesia is measurement methods/tools include conditional illustrated in Article Figure 1.4. Based on the diagram, value at risk (CoVaR), marginal expected shortfall there are three main classifications of systemic risk (MES) and network analysis. Although categorised as measurement tools at Bank Indonesia. The first is systemic risk measurement tools, the use of such tools based on the type of measurement tool, namely in the varies depending on the aspect of systemic risk to be form of an indicator and the development of certain measured. For example, several previous research measurement methods. The second is based on the papers measured systemic risk through more specific cross-section and time-series dimensions. The third is

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Article Figure 1.3 Systemic Risk Measurement Framework

Systemic Risk Measurement Framework

Types of Measurement Tools Dimensions Phases of Systemic Risk Formation

1. Monitoring Indicators 1. Cross-Section 1. Source of disruption appears 2. Model Based 2. Time Series 2. Source propagates to become a risk 3. Systemic event

based on the phase of systemic risk formation, namely financial system performance. For example, the NPL when the source of disruption appears, when the ratio and Capital Adequacy Ratio (CAR). source propagates to the financial system, and finally, the potential impact of the systemic event. At the systemic risk identification and assessment stage, the indicators have already fundamentally been 3.1. Types of Measurement Tools processed according to certain methods depending Systemic risk measurement tools come in the form on the risks to be identified and assessed. This of indicators as well as the further development methodology also contains several interpretations of systemic risk measurement methods. In terms and assumptions by researchers who have developed of macroprudential supervision, indicators can be pertinent methodologies to produce measures of used for monitoring, stress identification and risk specific risks. For instance, the data is usually assumed assessment purposes. In general, the indicators used to follow a normal distribution for statistical models. for monitoring are simple indicators, originating Nonetheless, several systemic risk measurement from the financial statements of financial institutions models do not assume a normal distribution, favouring as well as publicly available financial market data. clustering for example. These indicators are used to detect micro-financial vulnerabilities, along with idiosyncratic and systematic In addition to the indicators, systemic risk identification shocks. In addition to financial system indicators, and assessment also requires more complex monitoring under the auspices of macroprudential measurement methods to represent the variables supervision also requires the collection of micro- to be measured. According to several measurement financial data to detect vulnerabilities and shocks from methods, systemic risk must be measured by macroeconomic conditions. At the monitoring phase, combining or transmitting a number of indicators. the data is processed as simple ratios to illustrate Such developments involve formulating a composite

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index that combines several performance indicators Measuring systemic risk using the time-series in the financial system, as has been implemented at a dimension represents the development of one number of central banks. Accordingly Bank Indonesia indicator of systemic risk over time. In that context, developed the Financial System Stability Index (FSSI) measurements over time can utilise relatively low (Gunadi et al, 2013 and Gunadi et al, 2015). frequency indicators, quarterly for instance, but can also use higher frequency indicators, such as Systemic risk measurement methods (models) were financial market indicators that change from minute also developed using the transmission of several to minute or even from second to second. At a indicators through the development of several lower frequency, systemic risk is generally measured modules or models (RAMSI, SRM, MFRAF AND SAMP). using intermediation imbalances along with risk- The advantage of building a model is that systemic taking behaviour. For example, Drehmann et al risk can be transmitted systematically to the entire (2012) developed an indicator of the financial cycle financial system, taking into consideration all the to represent risk-taking behaviour among market necessary aspects of systemic risk measurement. In players in reaction to economic conditions. In general, contrast, the fundamental weakness of the model is this lower frequency indicator was used to capture that it is data driven, which would therefore inherently procyclical behaviour at financial agents. An example rely on the availability of financial system data. While of a higher frequency indicator is asset price volatility a data gap exists in terms of financial system stability, on the financial markets, which represents market risk. the systemic risk measurement model must be used prudently due to aspects of the financial system and Cross-sectional indicators are used to measure systemic risk transmission channels not being fully systemic risk at a specific time and capture different represented in the model. elements of the financial system. For example, capital indicators of individual banks at a given time would 3.2. Measurement Tool Dimensions represent banking sector resilience at that time. From a macroprudential perspective, risk can be Similarly, banking industry NPL, as an aggregate of grouped into two dimensions, namely time series NPL at individual banks, would represent credit risk and cross section. The time-series dimension in the banking sector. Cross-sectional indicators are emphasises how risks in the financial system evolve used to detect financial system risk originating from over time, including evolution with economic concentration risk linked to a specific portfolio or sectors (procyclicality). Meanwhile, the cross-section certain business or economic sector. In addition, risk dimension focuses on how the risks are distributed in from the contagion effect due to interconnectedness the financial system during a given period, originating between financial agents also requires cross-sectional from concentration risk and/or interlinkages in the data. For instance, interbank stress testing requires financial system (contagion risk). Consequently, the interbank exposure data from all banks at a specific problems that arise in one financial institution could time in order to measure the impact of default at one adversely impact other financial institutions directly bank on the other banks. Thereafter, several systemic and indirectly. risk measurement methods combine data from both

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dimensions using panel data to simultaneously obtain terms of detecting the shock, particularly if the shock the dynamics of both dimensions stems from a new form of interaction in the financial system and is, therefore, not covered by the existing 3.3. Phases of Systemic Risk Formation EWS. Meanwhile, a vulnerability is a characteristic Systemic risk forms through three stages as illustrated of elements of the financial system in the form of in Article Figure 1.4, namely: (i) sources of disruption a fragility that amplifies and propagates the initial appear, involving a combination of a shock and shock, potentially exacerbating the shock in the deteriorating risk profile (vulnerability), often referred financial system. there are two types of vulnerability to as the build-up phase; (ii) the sources propagate in the financial system: namely a vulnerability in the into the financial system to become risks; and (iii) form of a fundamental characteristic of each element the potential impact of the systemic even is then (for example a maturity mismatch at a financial measured. institution); as well as a vulnerability that surfaces due to the business activities of financial system elements In the first phase, systemic risk measurement tools (cumulative behaviour), such as a concentration of are used to identify the sources of disruption. In this lending in a certain economic sector, for example. case, the sources of disruption can be grouped into In general, vulnerabilities can be identified by risk two categories, namely shocks and vulnerabilities. profiling the behaviour of each element in the financial Risk will materialise when the shock interacts with system, namely by measuring the performance and the vulnerability; and will have a systemic impact risks5. Identifying the vulnerabilities involves the if not offset by adequate resilience. According to time-series and cross-section dimensions using the Bernanke (2013), a shock is a specific event that financial system risk approach, namely credit risk, triggers (accompanies) a crisis (the proximate causes). liquidity risk, market risk and operational risk (Article Meanwhile, a vulnerability is associated with pre- Figure 1.4). The identification of vulnerabilities using existing features of the financial system that could the credit risk approach reflects risks that emerge amplify and accelerate shock propagation. Thereafter, from the intermediation function in the financial systemic risk is formed through interaction between system. Meanwhile, the market risk approach is the external shock and internal vulnerability, which measured due to the interconnectedness of financial is considered a characteristic of the financial system system elements through the assets traded on itself. financial markets that transmit asset prices, interest rates and exchange rates (for foreign currency assets). Shocks are identified (Article Figure 1.4) by measuring The liquidity risk approach represents the ability stress indicators in the financial system and using an of financial system elements to meet short-term Early Warning System (EWS) that typically consists of obligations. The operational risk approach links the prompt and near-crisis indicators as leading indicators. functions of the financial system in terms of providing Nonetheless, the EWS may contain weaknesses in financial services, such as providing a medium for the

5 Pursuant to Bank Indonesia Regulation (PBI) No. 16/11/PBI/2015 concerning Macroprudential Regulation and Supervision, the financial system consists of financial institutions, financial markets, financial infrastructure as well as non-financial companies and households, which interact with one another through funding and/or providing economic financing. Based on that definition, financial system elements are financial institutions, including banks and nonbanks, financial markets and infrastructures, as well as non-financial institutions and households

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payment system, financing to economic sectors and elements have inherent resilience to absorb facilities to manage liquidity using local or foreign the risks. For example, when global liquidity currencies. pressures appeared in the fourth quarter of 2008, the national banking industry in Indonesia could At the second phase of systemic risk formation, the absorb the risks system-wide because there were risks will materialise in the financial system when a no vulnerabilities to materialise the systemic risk; shock interacts with the vulnerabilities (Article Figure c. If there is no shock but a vulnerability, the 1.5). Interaction between the two sources of disruption probability of systemic risk materialising in the produces a combination of probabilities as follows: financial system increases. Nevertheless, similar to a. a. If there are no shocks or vulnerabilities, the previous combination, a financial crisis may still potential systemic risk will not materialise; be avoided due to the lack of a trigger to expose b. b. If there is a shock but no vulnerabilities, the the vulnerability. Consequently, the vulnerability probability of systemic risk materialising increases has materialised due to an accumulation of risk due to possible unknown vulnerabilities. A financial originating from risk-taking behaviour when the crisis may still be averted because financial system financial cycle is enjoying an upswing;

Article Figure 1.4 Systemic Risk Formation

Source of disruption Vulnerability (Risk Profile) 2

1 Dimension Type of Risk

Shock Cross Section : - Market Risk - concentration risk - Credit Risk - contagion risk - Liquidity Risk Time series : - Operational Risk - procyclicality risk

Transmission

Risk of Financial System 3

4 Impact

No Resilient? Check Systemic Risk Yes Liquidity & Solvelency Buffer Stable Financial System Potential Impact

Temporary Structural

Sources of Disruption; Transmission; Impact

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d. If there is a simultaneous shock and vulnerability, elements. Per banking stress testing, the credit, the probability of systemic risk increases depending market, liquidity and operational risks are translated on the magnitude of the shock and severity of into losses that must be absorbed by the banking the vulnerability. If the vulnerability is found in a sector. In that context, bank resilience to the risks faced dominant financial sector, such as the banking is measured based on capital, namely that the level sector in most emerging market economies, of capital exceeds the level required by the regulator systemic risk will materialise6. after deducting the losses generated by the stress tests. A similar procedure is used to stress test other Article Figure 1.5 Interaction between the Shock and Vulnerability financial system elements, including the nonbank financial industry, corporate sector and households. Vulnerability

No Yes In general, if the financial system elements can Increased absorb the risks (Article Figure 1.4), there is a greater No potential probability No systemic risk of potential systemic risk probability that financial system instability will be avoided. In other words, the financial system will Shock Increased withstand the shock without adversely impacting the probability Potential of potential systemic risk economy. If a financial system element experiences a Yes systemic risk materialises problem, however, systemic risk formation moves on to the next phase, namely measuring the potential impact of the systemic event through systemic If potential systemic risk materialises, one impact analysis. Systemic impact analysis is an ad methodology or measurement tool available is hoc approach to measuring the impact of default at stress tests. Stress tests apply extreme but plausible one financial system element on the overall system scenarios. Furthermore, data on the vulnerabilities (Harun, 2013 and Harun et al, 20147). The results of of financial system elements is also required, namely the systemic impact analysis are used to determine in the form of balance sheet data and P/L reports whether default at one element of the financial system (depending of the financial sector being measured). will have a systemic impact or not. If the impact is Sound stress tests also consider the interactions of systemic, mechanisms should be considered pursuant financial system elements, thereby capturing financial to prevailing regulations. If not, the financial system system dynamics and producing realistic results. In element must enter a resolution process to protect addition, the stress tests also include a contagion the interests of the depositors and creditors. module and second-round impact module.

3.4. Systemic Risk and the Financial Cycle After the systemic risk has been transmitted in If linked to the financial cycle, the sources of the systemic risk measurement value, the value in disruption typically appear during the build-up phase, translated into a loss that is borne by financial system

6 The risk materialises when the shock interacts with the vulnerability (Bank of Canada, 2014) 7 Harun, 2013 and Harun et al, 2014 are internal Bank Indonesia research papers that are not published

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when the markets favour profit-taking behaviour financial cycle, when the cycle hits a trough (Article despite the prudential regulations in place. In terms Figure 1.6). At this stage, the problems that arise in of the financial cycle, this phase occurs during an one sector or element of the financial system tend upswing period (Article Figure 1.6). In that context, to propagate and are transmitted to other sectors systemic risk measurement should focus on financial or elements. Therefore, systemic risk measurement system imbalances as well as stress indicators that during this phase generally applies cross-sectional can signal the financial cycle is nearing a peak, which indicators. The best indicators are those that reveal is interpreted as excessive risk-taking behaviour. physical exposure links between financial system Drehmann et al (2012) modelled the financial cycles elements, including each individual element, namely of several advanced countries and found that financial financial institutions and corporations. One method crises generally occur around two years after the that can be applied to measure the impact of problems financial cycle has peaked. at one bank on other banks is contagion analysis using

Article Figure 1.6. Financial Cycle Phases interbank stress testing.

Peak During the propagation phase, Global-Systemically Propagation Systemic Build-Up and Event Important Banks (G-SIB) represent an important Phase Amplification Phase indicator of systemic risk measurement. The indicator was formed to create a list of banks around the world that, if experiencing problems, could Trough Trough potentially trigger a systemic impact in the global Fundamentally, indictors of imbalances refer to financial system. The G-SIB indicator is comprised of lower frequency time-series indicators (monthly to size, interconnectedness, sustainability, complexity quarterly). Several central banks use property prices and cross-border exposure of Global Systemically as a proxy to detect imbalances based on the premise Important Financial Institutions (BCBS, 2011 – GSIB that property prices are driven by speculative investor Document). During the propagation phase, the G-SIB behaviour (primarily households) funded by housing sub-indicators applied to D-SIB (without measuring loans. In addition, property prices are also driven cross-border exposures because only the impact on the by increased demand for basic necessities as public domestic economy is observed) are those that require purchasing power increases in line with stronger monitoring for each individual bank, to observe the economic growth. The imbalances detected here are potential propagation of problems. Measurements of linked to bank lending procyclicality. The formation of the potential propagation of problems are reviewed financial cycle indicators, as discussed previously, also using systemic impact analysis. aims to detect imbalances in the financial system due to the markets’ perception of economic conditions The final phase is the systemic event, otherwise known and risk-taking behaviour. as when the shock has materialised. This phase is associated with a financial crisis. Although the central Sources of disruption that have already materialised bank and financial authorities may have already into risk will spread through propagation mechanisms. developed an EWS, a systemic event can fundamentally This phase occurs after and between the peaks of the only be detected through backward-looking analysis.

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Central banks and financial authorities have never scenarios to simulate through stress testing. Stress accurately predicted the onset of a crisis, despite the tests, primarily to measure solvency and liquidity financial cycle providing information on the peak and under stress, are commonly used in the banking past data indicating that crises generally occur two industry, producing a gap due to a capital or liquidity years after the financial cycle has peaked. Therefore, buffer that must be utilised to absorb the losses a systemic event represents a brief period in the originating from the systemic event being tested. propagation phase, when the shock and vulnerability A buffer is defined as the residual amount over the collide to form systemic risk. minimum requirement. The results of stress tests have a number of determinants. Extreme but plausible After a systemic event has occurred, a U or V-shaped scenarios provide reasonable levels of stress to test downswing is expected. A U-shaped downswing the resilience of financial institutions against a severe would be deeper and last longer in the financial cycle, systemic event, supported by previous experience. accompanied by a protracted recovery period, which Data availability and model design to measure the could lead to a structural impact. On the other hand, reaction of financial institutions to the systemic event a V-shaped downswing would have a shorter duration will determine the objectivity of the stress test results. and faster recovery. In the financial cycle, systemic Sometimes, biases can appear due to insufficient events do not necessarily have to occur because during historical and granular data; or an inadequate model. the downswing, market players automatically adjust In practice, stress tests are already recommended for their portfolios to reduce potential losses. Depending mandatory activities at a financial institution to ensure on the resilience of financial system elements, the an adequate capital buffer and liquidity. central bank and financial authorities will strive for a shallower downswing by preparing instruments to 4. Conclusion prevent the onset of a financial crisis that would incur Efforts to mitigate systemic risk cannot rely merely a high-cost recovery. on a single indicator or one measurement method. In other words, a range of comprehensive systemic During this phase, high-frequency near-crisis indicators risk measurement tools are required. As the and stress indicators, for example indexes that macroprudential authority, Bank Indonesia constantly illustrate general conditions in the financial system or develops indicators, methods and tools to mitigate liquidity indicators, are critical to gauge the ability of systemic risk, which are expected to create efficient financial system elements to meet their short-term supervision and appropriate policy instruments to obligations. If a crisis has already begun, the central support financial system stability. To that end, the bank will activate Crisis Management Protocol (CMP), Systemic Risk Measurement Framework (KPRS) which can mandate higher frequency reporting by can be used as guidelines or a reference when financial institutions. identifying existing systemic risk measurement tools. To complement KPRS formulation, additional future Anticipating a systemic event by ensuring adequate research is required, primarily to develop several capacity to absorb risk, the financial authorities or systemic risk measurement methods currently not financial institutions could create systemic event available to Bank Indonesia.

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The objectivity of systemic risk measurement is determined by the indicators and methods applied. Erroneous data and methodologies could undermine risk mitigation efforts or the macroprudential policy prescription or policy to handle the crisis. A common perception regarding the methods and indicators to measure certain risks in the financial system at each phase is required to avoid differing opinions when determining financial system stability. This is critical, especially if the financial system is experiencing distress and requires accurate and rapid resolution.

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Bibliography Abel, Andrew., and Bernanke, Ben., 2001, “Macroeconomics, 4th Edition”, Addison Wesley Longman Inc. Acharya, V., L. Pedersen, T. Philippon, and M. Richardson, 2010, “Measuring Systemic Risk”, Working Paper , New York Univertsity. Bank Indonesia, 2015, “Kajian Stabilitas Keuangan No. 25”. Bank of Canada, 2014, “Financial System Review”, pp. 1-2, June Basel Committee on Banking Supervision, 2011, “Global Systemically Important Banks: Assessment Methodology and the Additional Loss Absorbency Requirement”, Bank for International Settlements. ______, 2012, “ Model and Tools for Macroprudential Analysis,” BIS Working Paper No. 12, Bank for International Settlements. Baumohl, B., 2013, “The Secrets of Economic Indicators: Hidden Clues to Future Economic Trends and Investment Opportunities”, Pearson Education, Inc. Bernanke, Ben., 2013, “Monitoring the Financial System,” speech at the 49th Annual Conference on Bank Structure and Competition, Board of Governors of the Federal Reserve System, May. Billio, M., M. Getmansky, A. W. Lo, and L. Pelizzon, 2010, “Econometric Measures of Systemic Risk in the Finance and Insurance Sectors”, NBER Working Paper 16223, NBER. Blancher, N., S. Mitra., H. Morsy., A. Otani., T. Severo., and L. Valderma., 2013, “Systemic Risk Monitoring(“SysMo”) Toolkit – A User Guide”, IMF Working Paper No. 13/168, July. Boss, M., Krenn, G., Puhr, C., and Summer, M., 2006, “Systemic Risk Monitor: A Model for Systemic Risk Analysis and Stress testing of Banking Systems”, Financial Stability Report 11, Oesterreichische Nationalbank, pp. 83-95, June. Burrows, O., Learmonth, D., and McKeown, J., 2012, “RAMSI: a top-down stress-testing model”, Financial Stability Paper No. 17, , September. Caballero, R. J., 2009, “The ‘Other’ Imbalance and the Financial Crisis”, MIT Department of Economics Working Paper No. 09-32, Massachusetts Institute of Technology. Cicilia, A. H., 2013, “Analisis Dampak Sistemik di Indonesia”, Internal Working Paper, Bank Indonesia. Cicilia, A. H., Derianto, Elis., Agusman., Rulina, Ita., 2015, “ A Framework of Systemic Impact Analysis”, Bank Indonesia, forthcoming. Drehmann, M., Claudio B., Kostas, T., 2012, “Characterising the Financial Cycle: Don’t Lose Sight of the Medium Term!” BIS Working Paper No. 380, Bank for International Settlements, June. European Central Bank (ECB), 2010, “Financial Networks and Financial Stability”, Financial Stability Reviews, pp. 138-146, June. Gadanecz, B., and Jayaram, K., 2009, “Measure of Financial Stability – a Review”, IFC Bulletin No 31. pp. 365- 380, July. Gauthier, C., and Souissi, M., 2012, “Understanding Systemic Risk in the Banking Sector: A MacroFinancial Risk Assessment Framework”, Bank of Canada Review, Financial Stability Department, Bank of Canada, pp.29-38. Group of Ten, 2001, “Report on Consolidation in the Financial Sector”, International Monetary Fund, January. Gunadi, I., Aditya, A.T., dan Cicilia, A. H., 2013, “Penggunaan Indeks Stabilitas Sistem Keuangan (ISSK) dalam Pelaksanaan Surveilans Makroprudensial”, Working Paper Bank Indonesia, Departemen Kebijakan

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Makroprudensial, Bank Indonesia. ______, 2015, “Penyempurnaan Indeks Stabilitas Sistem Keuangan (ISSK)”, Working Paper Bank Indonesia, Departemen Kebijakan Makroprudensial, Bank Indonesia. Gunadi, I., Cicilia, A.H., Sagita, R., dan Tevy, C., 2014, “Identifikasi Transmisi Risiko Sistemik dalam Sistem Keuangan Indonesia”, Working Paper Bank Indonesia, Departemen Kebijakan Makroprudensial, Bank Indonesia. Harun, Cicilia., and Sagita Rachmanira, 2013, “Kerangka Kebijakan Makroprudensial Indonesia”, Working Paper Bank Indonesia, Departemen Kebijakan Makroprudensial, Bank Indonesia ______, 2015, “Revisit Kerangka Kebijakan Makroprudensial Indonesia”, Working Paper Bank Indonesia, Departemen Kebijakan Makroprudensial, Bank Indonesia. Jong, H.L., Ji, H. B., Sejin, Y., and Dongkyu, C., 2013, “Systemic Risk Assessment Model for Macroprudential Policy”, Macroprudential Analysis Department, Bank of Korea. Kapadia, S., M. Drehmann, J. Elliott, and G. Sterne, 2009, “Liquidity Risk, Cash Flow Constraints, and Systemic Feedbacks”, Working Paper, Bank of England. Mishkin, F. S., 2007, “Systemic Risk and the International Lender of Last Resort”, Working Paper, Board of Governors of the Federal Reserve, Speech delivered at the Tenth Annual International Banking Conference, Federal Reserve Bank of Chicago, September 28th. Organization for Economics Co-Operation and Development, 2008, “Handbook on Constructing Composite Indicators: Methodology and User Guide”, OECD and JRC European Comission. Rosengren, E.S., 2010, “Asset Bubble and Systemic Risk”, The Global Interdependence Center’s Conference on Financial Interdependence in the World’s Post-Crisis Capital Market, Philadelphia Wolken, Tony., 2013, “Measuring Systemic Risk: the role of Macro-prudential Indicators”, Bulletin Vol. 76 No. 4, Reserve Bank of New Zealand, December.

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211 Article 2 Financial Network Stability in Indonesia’s Banking System Article 2 Financial Network Stability in Indonesia’s Banking System

Article 2 Financial Network Stability in Indonesia’s Banking System Laura Grace Gabriella

Indonesia’s financial system has undergone significant differences, such as a complete network or incomplete transformation, accompanied by increased financial network, circular network, core-core network and core- system stability through greater bank capital resilience. periphery network (Allen & Gale, 2000; Lee, 2013; Georg, Nevertheless, interconnectedness in the financial system 2013). The existing research concluded that network has also increased, which could propagate shocks and structure differences have a disparate effect on shock trigger a banking crisis. This research investigates the propagation. For example, Allen and Gale (2000) stated changes that have occurred in Indonesia’s banking system that high levels of interconnectedness in a complete over two periods, namely 2008 and 2014, by testing network could reduce systemic risk, while vulnerabilities bank size and capital, bank concentration, as well as to the shocks would be high in an incomplete network, interconnectedness as the foundation to form a network assuming that borrowing from all banks is equal. Different structure. Thereafter, simulations are run on both structures also entail different policy recommendations. In networks to compare the speed and severity of a shock in general, a core-periphery network structure emphasises the network based on the degree of interconnectedness, the importance of diverse institutions at its core. For initial location of the shock and magnitude ofthe instance, Gai, et al. (2011) suggested that different polices shock. The results demonstrated that the financial are required when a central bank is at the centre of the network is robust yet fragile because despite increased network, otherwise known as a star network. Network network stability due to a solid capital base, greater structure differences also influence the implementation interconnectedness has accelerated shock propagation in of financial system stability supervision. In their research, the event of a crisis. Capponi and Chen (2015) found that supervision would be more effective in a core-periphery network rather JEL Classification: C63, C90, G28 than other network structures because the relevant Keywords: financial stability, financial network, systemic authority can focus on Domestic-Systemically Important risk Banks (D-SIB). Therefore, the authorities must consider the financial network structure underlying policymaking 1. Introduction decisions. This research aims to compare three The global financial crisis raised awareness in variables that influence Indonesia’s network structure: several countries of systemic risk. Furthermore, (i) bank size and capital; (ii) bank concentration; and (iii) interconnectedness between financial institutions is interconnectedness. The comparison will be used as a considered the main contributor to shock transmission reference when simulating shocks to observe differences that increases the probability of knock-on default. Various in terms of banking system resilience in Indonesia in 2008 conflicting opinions have been discussed concerning the and 2014 when confronting contagion shocks. influence of interconnectedness due to network structure

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Article Graph 2.1 Network Structure

2

1 2 1

1

3 4 2 3

3 4

Circular Network Core-core Network

Core-pheriphery Network

2. Theoretical Basis found that small banks in México have an extremely high 2.1 Network Topology interconnectedness rating. The influence of asset size In simple terms, a network is the graphical arrangement was also revealed by Glasserman and Young (2015), who of various nodes through edges. Each node has a value stated that shock contagion would be weaker if each node to indicate its magnitude, while the edges show the in the network had the same number of external assets. interaction between the nodes. In general, network In contrast, DasGupta and Kaligounder (2014) found that topology categorises the networks as complete or a homogenous network with high interconnectedness incomplete. In a complete network, each node is tends to be less stable, while high interconnectedness in a connected to every other node, while in an incomplete heterogeneous network leads to greater stability. network, at least one node is not connected to every other node. The second factor influencing the contagion process is timing. Financial institutions behave differently 2.2 Contagion in the Financial Network during stable and fragile times because timing creates There are several salient factors that influence the interconnectedness variations between financial contagion process in a financial network. The first institutions and increases susceptibility to shocks (Georg, is the heterogeneity of each respective bank’s size. 2013). During non-crisis periods, interconnectedness Heterogeneity occurs due to differences in terms of bank between banks increases liquidity allocation and risk assets, liabilities and capital. Nier, et al. (2007) suggested sharing. Interestingly, the research of Minoiu and that, in general, banks with a solid capital base are more Reyers (2013) showed that, globally, interconnectedness resilient to default contagion, while the magnitude of between banks typically increases prior to a banking crisis interbank liabilities tends to exacerbate knock-on default and then subsequently decreases. Similar characteristics risk despite adequate capital to withstand the exposures. were found by Gai and Kapadia (2010), namely that Several research papers applied asset size and leverage to financial systems are robust yet fragile, meaning that measure liquidity risk. Nevertheless, Martinez-Jaramillo under normal conditions, the system has low potential et al. (2014) confirmed that interconnectedness is not for contagion due to solid resilience but a shock could always linked to asset size. Their empirical research propagate with rapidity after a crisis event.

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The third factor is the size of the shock. Acemoglu, classified based on bank group, namely BUKU 1, BUKU 2, et al. (2015) discussed the different implications of BUKU 3 or BUKU 4 banks. interconnectedness based on the magnitude of the shock. After a small shock, interconnectedness would 3.2 Model Specification increase stability through the transmission of liquidity. 3.2.1 Basic Network Structure Notwithstanding, interconnectedness would also The balance sheet of the banking system was used as the increase shock transmission in the event of a large foundation of the network created. One set,represents shock. Therefore, there is a certain threshold where the interconnected banks in the network. The total interconnectedness could amplify or dampen shock assets of each respective bank (ai) consist of interbank transmission. Consequently, this research will modify placements (li) and external assets (ei). On the other several contagion shock scenarios based on the degree hand, total liabilities consist of interbank borrowing (bi), of interbank connectivity, initial location of the shock and term deposits (di) and equity (yi). Interbank placements magnitude of the shock. are represented by li, comprised of total loans from bank i to bank j. External assets are denoted by ei. Therefore, 2.3 Lack of Information when Determining Network total assets will be the total of all assets li + ei, with total

N Structure external assets of the banking system E= ∑ i ei . Total N Fundamentally, data to form a financial network is assets are represented by A= ∑ i ai . The percentage of E extremely specific to each individual bank and public external assets to total assets is expressed by β = so E A access to data is limited. Therefore, most literature that A = . Total interbank placements are denoted by β N assumes complete networks for analysis purposes despite L, where L= ∑i li. the reality of incomplete networks in the banking system. Another approach utilises an index to determine financial Article Table 2.1 Bank Balance Sheets under Symmetrical Conditions system stability or simplify the calculations of systemic risk with the Systemic Probability Index (SPI) to detect Asset Liabilities potential contagion (Halaj and Kok, 2013). To overcome External Assets, Equity (Net worth), this limitation, several studies applied simulations to ei γi analyse shock contagion. Deposits,

di 3. Data and Methodology Interbank Placement Interbank Borrowing 3.1 Data li = ∑ xij bi = ∑ xij Annual balance sheet data published by Bank Indonesia jϵN jϵN from 105 conventional banks in Indonesia in 2008 and Total Asset Total Liabilities 2014 was used in this research. The sample includes ai= li + ei γi+ di + bi state-owned banks, foreign exchange banks, non-foreign exchange banks, joint-venture banks and foreign banks. Source: Lee (2013) Rural banks and Islamic banks were omitted, however, to simplify the calculations. All the sample banks were

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Article Table 2.2. Result on t-test from 2008 and 2014 Changes in the value will denote increases/decreases in terms of interbank interaction. HHI for lending is t-test Bank Size and Capitalization calculated as follows: Bank Assets 4.0755*** l (0.0000) L L 2 i HHI (i) = ∑ j ϵ N (i) (wi j ) wi j = Bank Capital (Equity) 3.9587*** ∑ li (0.0001) Concentration HHI for borrowing is calculated as follows : HHI Assets -0.2424 (0.4045) HHI Interbank Placement -0.7814 b B B 2 i (0.7815) HHI (i) = ∑ j ϵ N (i) (wi j ) wi j = HHI Interbank Liabilities -0.9249 ∑ bi (0.8214) Interconnectedness Where w is the weighted value of interbank borrowing (li) Interbank Placement 2.6631*** (0.0048) and lending (Bi). Interbank Liabilities 4.7329*** (0.0000)

*** p < 0.00, ** p< 0.05, * p<0.1 • Interconnectedness Interconnectedness is analysed based on total 3.2.2 Network Structure Changes interbank placements on the liability side. Changes to In the first phase, this research analyses banking structure interconnectedness are also revealed by total aggregate changes in Indonesia, testing changes in bank capital and RTGS transactions for the period from 2005-2015. size, bank concentration and bank interconnectedness using the t-test to obtain the average values of the Therefore, at the end of the first phase, a comparison of variables over the two periods. banking system structures in Indonesia in 2008 and 2014 is complete. x + x T-test formula 1 2 t = 2 2 3.2.3 Network Structure Simulations S S 1 + 2 After obtaining the network structure in the first phase, N N 1 2 simulations are run to investigate network resilience to

• Bank Capital and Size shocks in both periods by controlling: Bank size is analysed based on the number of branches, • Initial shock location: large banks (cluster 1) and total assets and total credit of each respective bank, while small banks (cluster 2) bank capital is reflected by the Capital Adequacy Ratio • Shock magnitude: number of banks initially (CAR) along with changes in capital structure per BUKU affected by the shock bank group. The results of the simulations are subsequently used to

• Bank Concentration compare the severity of shocks by measuring the number Bank concentration is measured using the Herfindahl- of defaulting banks and then dividing by the total number Hirschman Index (HHI) in terms of lending and borrowing. of banks in the system. Then, the time required for the shock to stop propagating shall be used as a measure of network fragility.

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3.2.4 Modelling Financial Networks The matrix then uses a probability of 0.2 for a low degree The model assumes there are 100 banks in the network, of interconnectedness and 0.4 for a high degree of ranked by total assets. These banks are modelled as a interconnectedness. Furthermore, the random network network towards G = (N, L, X) with a finite set of nodes N = creates an adjacency matrix of 1 and 0. A value of 1 is given {1, 2,…, 100} and number of links L…, where the size of the to any bank that has a link to another bank and a value of link is based on interbank placements (li), which becomes 0 otherwise. The total value of interbank placements in (xij) in the matrix. Therefore, the following adjacency each year will be used as a proxy of bank capacity to lend matrix is obtained with dimensions of n x n: to another bank. That value is then divided the number of connections and the average allocated to each edge

0 x12 x1n with a value of 1. Therefore, a financial network for 2008,

known as {G08}, and a financial network for 2014, known X = x21 0 x2n

as {G14}, is formed.

x x 0 n1 n2 Thereafter, the shock’s location and magnitude is determined by the bank’s ID. The ID rating is based on total The matrix is non-symmetrical and has a diagonal value assets, with ID1 representing the bank with the largest of 0. Bilateral interbank transaction data is not publicly assets and ID100 the smallest assets. Consequently, available, therefore, the matrix is formed as a random banks with an ID from 1-20 are categorised as small network. banks (cluster 1) and banks with an ID from 21-100 are considered large banks (cluster 2). Simulations are then Network Characteristics and Attributes run of shocks in the network based on four different Two attributes are used for the network model: scenarios. The initial location of the shock will reflect shock magnitude, therefore, the four scenarios are as a. Erdös-Renyi Probability follows: All banks in the network are assumed to follow 1. One large bank (Node ID1) the Erdos-Renyi Probability (1960), where the 2. One small bank (Node ID30) independent edges are formed from the other 3. Two large banks (Node ID1 and ID 5) edges in the network structure. Banks are 4. Two small banks (Node ID30 and ID40) interconnected with one another as lenders and borrowers with a certain probability. The probability that a bank will transmit a shock to a b. Clustering neighbouring bank is stipulated as 0.5. The simulation The network consists of groups that distinguish continues to propagate the shock, stopping only when no large and small banks based on the BUKU more banks experience default in the system. Ultimately, classification of banks in Indonesia. Large BUKU the simulation shows the number of bank defaults and 3 and 4 banks are categorised as cluster 1, while the duration required for the propagation to cease. small BUKU 1 and 2 banks are grouped into cluster 2.

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4. Analysis 4.1 Banking System Changes The structure of the banking industry has also The results of the t-test showed that the structure of the changed in terms of the number of banks with a banking system in Indonesia underwent significant change core capital of more than Rp50 billion, which has from 2008 to 2014. In general, bank size and capital have gradually increased, while the number of banks with increased, with a stable degree of concentration, including a core capital of less than Rp1 trillion billion(?) has assets, interbank placements and interbank liabilities. declined. Such developments are congruent with BI Congruently, interconnectedness has also increased in policy to impose a minimum core capital threshold of line with growing interbank transactions. Rp80 billion in 2008. The threshold was subsequently increased to Rp100 billion in 2010. The banks with the a. Size largest capital base were also observed to maintain In general, total assets and total equity of the the largest assets, which are generally state-owned banking industry increased significantly from 2008 banks. Such conditions represent a strategic measure to 2014, indicating greater bank ability to resist for Bank Indonesia to enhance supervision of banks and absorb shocks. The banking industry accounts considered too big to fail. for around 80% of the financial sector, with 62.5% of total bank assets held by the 10 largest b. Concentration banks, which is indicative of a high degree of Statistically, no significant changes were observed in concentration. Such conditions were the result of terms of interbank concentration in Indonesia. The Bank Indonesia’s ‘Single Presence Policy’ released average value of assets and credit of the 10 largest in 2006, which prompted a proliferation of bank banks in Indonesia has remained at around 61% for mergers. The data shows that the number of the past decade. During the crisis in 2008, however, banks decreased after 2000 and then stabilised in bank concentration increased slightly to 62.22% and 2009, but the number of bank branches expanded then again to 66.24% in 2009 after Bank Indonesia significantly over that period. instituted its Single Presence Policy. The degree

Article Graph 2.2 Total Banks, Total Branches and Total Article Graph 2.3 Capital Adequacy Ratio (CAR) by Bank Banks by Core Capital in Indonesia from Group 2006-2012

CAR per BUKU (%) 20.000 150 37

32 15.000

100 27

10.000 22

50 17 5.000

12

0 7 2006 2007 2008 2009 2010 2011 2012 1 6 11 4 9 2 7 12 2 5 10 3 8 1 6 11 4 9 2 7 12 2 5 10 3 8 1 6 11 4

>Rp50 billion Total Branches Total Banks BUKU 1 BUKU 2 BUKU 3 BUKU 4

Sumber: Bank Indonesia

218 Article 2 Financial Network Stability in Indonesia’s Banking System

of bank concentration in Indonesia is acceptable, placements. Nonetheless, the data also shows that however, considering conditions in advanced several small banks have a high level of placements and countries, where, for example, the three largest loans as well. banks in the UK and US account for 75% and 40% respectively of total assets. The value of daily interbank transactions has also increased. The number of Real Time Gross Settlement c. Interconnectedness (RTGS) transactions has increased over time, from 2005- Interbank placements, as a proxy of bank 2015, despite decelerating in 2008. The data shows that interconnectedness, increased significantly over the the interbank offered rate increased during the global observation period, indicating greater interbank financial crisis. The interbank offered rate first increased on dependence as well as a more stable network. tenors of 12 months, followed by 6 months, 3 months and finally 1 week. Banks tried to safeguard liquidity through Article Table 2.3 Correlation of Bank Assets, Interbank Placements and Interbank Liabilities (2014) by borrowing from other banks at the longest duration tenors available. Furthermore, under stress conditions, Interbank Interbank Total Assets Placements Liabilities the banks became more segmented, favouring interbank Total Assets 1.0000 placements with similar banks. An example is the Interbank 0,9092 1.0000 Placements summary of Bank Mandiri loans. As the largest bank, with Interbank 0,7644 0,7844 1.0000 Liabilities total assets accounting for 15.2% of the banking industry, Bank Mandiri borrowed most loans from BUKU 4 and 3 Table 2.3 reveals that assets correlate very closely with banks. Consequently, it can be concluded that network placements on the interbank market but not with structure in Indonesia has become increasingly stable in interbank liabilities. Such conditions indicate that banks terms of bank size, capital and interconnectedness during with large assets tend to also maintain large interbank non-crisis periods.

Article Graph 2.4 RTGS Transactions (2005-2015) Article Graph Interbank Offered Rate (2008-2015)

20 14.000 2.000

12.000 15 1.500 10.000

8.000 10 8.000 6.000 5 4.000 500

2.000 0 1-Jan - 08 1-Jan - 10 1-Jan - 12 1-Jan - 14 0 0 Jan - 05 Jan - 07 Jan - 09 Jan - 11 Jan - 13 Jan - 15 Overnight (%) 1 Week (%) 6 Month (%) 1 Month (%) 3 Month (%) 12 Month (%) Nilai (Miliyar Rp) Volume (Satuan)

Sumber: Bank Indonesia Sumber: Bank Indonesia

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4.2 Simulasi Network Tipologi • The simulations produced consistent results over The formation of a financial network of banks in both observation periods using different initial Indonesia applied various assumptions explained in shock locations. If the shock originated from a the methodology. The resultant financial network is large bank, faster propagation was observed presented in Article Graph 2.6. Thereafter, financial but the duration was briefer. Nonetheless, network simulations were carried out. extremely high interconnectedness meant that the level of default was the same for both Article Graph 2.6 Financial Network of Banks in Indonesia (2008 and 2014) periods. • The simulations consistently showed that if Financial Network of Banks in Indonesia in 2008 more banks were affected by the shock at the onset, the shock would propagate throughout the system more quickly. Consequently, the magnitude of the shock significantly influenced shock transmission, leaving the system exposed and fragile if the degree of interconnectedness was high between the affected banks. • The simulations demonstrated that a shock would take longer to disperse in 2014 compared to 2008 but the severity was higher. Such developments indicate greater network Time = 1 interconnectedness under extreme conditions,

Financial Network of Banks in Indonesia in 2014 which created fragilities in the banking system and intensified the risks.

Therefore, the network in 2014 was said to be robust yet fragile, namely able to absorb the shocks under normal conditions but with increased severity under crisis conditions. The results are in line with the Financial System Stability Index (FSSI) released by Bank Indonesia, namely that financial stability was maintained despite the external pressures in 2008 due to a lack of interconnectedness between banks in Indonesia and foreign banks.

Time = 1 4.3 Policy Response The simulations revealed that the probability of default The simulations showed that a shock originating from a was higher in 2008 than in 2014, indicating greater large bank would be more severe and propagate more resilience over time. The rest of the simulation results are rapidly. Therefore, large banks are considered too big summarised as follows: to fail and require special supervision. In addition, the

220 Article 2 Financial Network Stability in Indonesia’s Banking System

central bank must also supervise banks that are too recommend further financial network analysis by Bank interconnected to fail because shock propagation relies Indonesia. Such research would directly recommend the on more connections. Consequently, Bank Indonesia still use of network analysis to observe bank behaviour and a needs to find an optimal financial network structure to multilayer network for future research. ensure more effective macroprudential policy. Although the central bank has already instituted various policies, such as capital requirements, liquidity requirements and bank restrictions, the network itself could be used to alleviate the effect of externalities through the provision of interbank liquidity.

5. Conclusion The research concluded that banking system stability in Indonesia increased from 2008 to 2014, evidenced by additional bank capital and a maintained degree of bank concentration, thus reinforcing bank resilience to shocks. Nevertheless, Bank Indonesia does need to anticipate greater segmentation during crisis periods and bank propensity to interact more with similar sized banks in terms of capital and assets.

Simulating various scenarios demonstrated that the network simulations were consistent with prevailing theory, namely that the initial location of the shock influences the transmission process. Shocks originating at large banks accelerate the propagation process compared to shocks at small banks. Furthermore, the simulations also showed that although the financial network was more stable in 2014, it remains robust yet fragile.

6. Limitations and Possible Contributions Network theory represents a new subject of economic analysis, which should be developed intensively. On the other hand, the main research limitation was the lack of complete network analysis due to confidential individual bank data. A more comprehensive data set would produce more realistic models and analysis of the financial network in Indonesia. Therefore, the authors strongly

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Bibliography Acemoglu, D., Ozdalar, A. & Tahbaz-Salehi, A., 2015. Systemic Risk and Stability in Financial Network. American Economic Review, pp. 564-608. Allen, F. & Gale, D., 2000. Financial Contagion. Journal of Political Economy, pp. 1-33. Capponi, A. & Chen, P.-C., 2015. Systemic Risk Mitigation in Financial Networks. Journal of Economic Dyanmics & Control, pp. 152-166. DasGupta, B. & Kaligounder, L., 2014. On Global Stability of Financial Networks. Journal of Complex Networks, pp. 313-354. Gai, P., Haldane, A. & Kapadia, S., 2011. Complexity, Concentration, and Contagion. Journal of Monetary Economics, pp. 453-470. Gai, P. & Kapadia, S., 2010. Contagion in Financial Networks. Proceedings of The Royal Society A, pp. 2401- 2423. Georg, C.-P., 2013. The Effect of the Interbank Network Structure on Contagion and Common Shocks. Journal of Banking & Finance, pp. 2216-2228. Glasserman, P. & Young, H. P., 2015. How Likely is Contagion in Financial Networks?. Journal of Banking & Finance, pp. 383-399. Halaj, G. & Kok, C., 2013. Assessing Interbank Contagion using Simulated Networks. Computational Management Science, pp. 157-186. Haldane, A., 2009. Rethinking the Financial Network. Amsterdam: At the Financial Student Association. Kapadia, S., 2012. Financial Network and Contagion: Learning from Ecology and Epidemiology. Oxford: s.n. Lee, S. H., 2013. Systemic Liquidity Shortage and Interbank Network Structures. Journal of Financial Stability, pp. 1-12. Martinez-Jaramillo, S., Alexandrova-Kabadjova, B., Bravo-Benitez, B. & Solorzano-Margain, J. P., 2014. An Empirical Study of Mexican Banking System’s Network and Its Emplications for Systemic Risk. Journal of Economic Dynamics and Control, pp. 242-265. Minoiu, C. & Reyes, J., 2013. A Network Analysis of Global Banking: 1978-2010. Journal of Financial Stability, pp. 168-184. Nier, E., Yang, J., Yorulmazer, T. & Alentorn, A., 2007. Network Models and Financial Stability. Journal of Economic Dynamics & Control, pp. 2033-2060.

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Director Publisher : Erwin Rijanto Filianingsih Hendarta Yati Kurniati Dwityapoetra S. Besar Bank Indonesia Jl. MH Thamrin No.2, Jakarta Coordinator and Editor Indonesia Retno Ponco Windarti – Yanti Setiawan – Rozidyanti - Herriman Budi Subangun – Reska Prasetya – Minar Iwan Setiawan

The preparation of the Financial Stability Review is one of the avenues through Drafting Team which Bank Indoensia achieves its mission ”to safeguard the stability of the Indonesian Rupiah by M. Firdaus Muttaqin, Kurniawan Agung, Ita Rulina, Indra Gunawan, Arlyana Abubakar, Ndari Suryaningsih, Cicilia maintaining monetary and financial system stability for sustainable national economic development”. A. Harun, Khairani Syafitri, Risa Fadila, Lisa Rienellda, Bayu Adi Gunawan, Heny Sulistyaningsih, Hero Wonida, Sigit Setiawan, Ardhi Santoso H.M., Arifatul Khorida, Justina Adamanti, Maulana Harris Muhajir, Zulfia Fathma, FSR is published biannually with the objectives : Sagita Rachmanira, Afaf Munawwarah, Arisyi Fariza Raz, Anindhita Kemala D., Apsari Anindita N.P, Dhanita • To improve public insight in terms of understanding financial system stability Fauziah Ulfa, Rieska Indah Astuti, Teguh Arifyanto, Amalia Insan Kamil, Randy Cavendish, Harris Dwi Putra, • To evaluate protential risks to financial system stability Pita Pratita, Syachman Perdymer, Rio Khasananda, Illinia Ayudhia Riyadi, Widyastuti Noviandri, Rifki Ismail, • To analyze the developments of and issues within the financial system Yono Haryono, Diana Yumanita, Jhordy K. Nazar, Fadhil, Kartina Eka Darmawanti, Meliana Rizka, Fiona Rebecca • To offer policy recommendations to promote and maintain financial system stabilty Hutagaol, Agus Seno Aji, Rolan Erikson Samosir, Agustina Damayanti, Indra Gunawan Sutarto, Dahnila Dahlan, RR. Diva Amelia Putri, Irman Robinson, Wahyu Widianti, Inrayanto Ariandos, Fransiskus Xaverius Tyas Prasa

Information and Orders: OTHER DEPARTMENT CONTRIBUTION ON SELECTED ANALYSIS This edition is published in September 2016 and is based on data and information available as of June 2016, Economic and Monetary Policy Department unless stated otherwise. Financial System Surveillance Department SME Development Department The PDF format is downloaded from https://www.bi.go.id Statistics Department Source : Bank Indonesia, unless stated otherwise Payment System Policy and Oversight Department For inquiries, comment and feedback please contact : Payment System Management Department Financial Market Development Department Bank Indonesia Macroprudential Policy Department PRODUCTION AND DISSEMINATION TEAM Jl. MH Thamrin No.2, Jakarta, Indonesia Saprudin, Satrio Prasojo, Vergina Hapsari, I Made Yogi Email : [email protected] FINANCIAL STABILITY REVIEW No. 27, September 2016 FINANCIAL STABILITY REVIEW No. 27, September 2016

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