CENTRAL BANK OF OMAN

FINANCIAL STABILITY REPORT Issue 5: 2017 CENTRAL BANK OF OMAN

FINANCIAL STABILITY REPORT Issue 5: 2017 © 2017 Central Bank of Oman. All rights reserved

Reproduction is permitted provided an acknowledgment of the source is made. Feedback on this Report may be given at [email protected]

Published by Financial Stability Department Central Bank of Oman P.O. Box 1161 Postal Code 112, Ruwi Sultanate of Oman

Head Office Tel : (+968) 24 777 777 Fax : (+968) 24 777 767

This publication can also be accessed through Internet at http://www.cbo.gov.om His Majesty Sultan Qaboos bin Said

FOREWORD It has been more than two years since the sharp fall in oil prices, however, uncertainty about the future path of the price of oil remains. Nonetheless, oil prices have been relatively stable since December 2016, which provided policymakers with a better understanding of the new economic reality. We observe signs of improved global economic outlook. Catching up with the U.S., the EU economy has shown marked improvement in 2016. The Asian economies, especially our main trading partners, China and India, are growing at a steady pace. Nonetheless, there are growing new risks. The U.S. withdrawal from the Paris Climate Accord might increase the supply of hydrocarbon and put a downward pressure on oil prices. The dynamics of Br exit are uncertain and could have a significant impact on financial stability in Europe and the rest of the world. China’s financial instability could be a function of its significant debt and growing housing market problems. The region is also entering a new phase of political instability, which could have a significant spillover into economic and financial instabilities. Being entrusted with the maintenance of financial stability of the Sultanate, the Central Bank of Oman remains watchful of these developments. Given global risks, on balance, we are optimistic about financial stability in the Sultanate. The economy faced clear challenges, including contractions in 2015 and 2016, but proved stable. International forecasts anticipate economic growth to resume next year. The government has been active in taking steps to consolidate its budget. Measured reforms, including the pace of economic diversification, have been taken and policies were put in place to increase revenues and reduce expenditures. The Central Bank of Oman continues to maintain a comfortable level of foreign reserves, which is sufficient to back-up the peg. During 2016, the Omani banking sector remained well capitalized and profitable with low infection ratio. Banks remained fairly liquid without any bout of serious stress. The credit growth remained healthy and the risks are well-contained. Our stress tests indicate low solvency and liquidity risks for the banking sector in the face of severe shocks. The cooperation among policy makers at the global level to coordinate financial sector regulations continued in 2016. The Central Bank of Oman ensured that its regulatory framework and supervisory policies are supportive of financial stability and economic growth. Our regulations also ensured that Oman complies with the international legislation and global best practices. During the year, a new Anti-Money Laundering Law was promulgated, Bank Resolution Framework was formulated, and policies to improve Financial Inclusion were introduced. Furthermore, guidelines on Sound Compensation Practices, Correspondent Banking Relationships, and adoption of IFRS 9 were issued. Oman is also on track in implementing Basel III capital and liquidity standards. Moreover, the Payment and Settlement Systems in Oman remained robust. Despite economic headwinds, we believe that the overall financial stability of the Sultanate remains intact.

Hamood Sangoor Al-Zadjali The Executive President

CONTENTS

Page No

Foreword

Financial Stability Assessment of Oman-An Overview I

Chapter I. Macro-Financial Outlook 01

Chapter II. Financial Institutions 33

Chapter III. Financial Sector Regulation And Infrastructure 59

Chapter IV. Stress Testing of the Banking Sector 72 List of Boxes

Page No. 1.1 Measuring Total Factor Productivity 12 1.2 Investment Demand in Oman 16 The Macro-Financial default-risk stress testing approach of the Central Bank of 1.3 20 Oman 1.4 Inflation in the Sultanate of Oman 26 1.5 The Government Debt 29 1.6 Estimating Import Demand Function for Oman 31 2.1 Banking Stability Index 35 2.2 Combating Non-Performing Loans 41 On Co-existence of Islamic and Conventional Banks: Do These Banks Differ in 2.3 54 Business Structure 3.1 Financial Technology 60 4.1 Shock Levels for Solvency Stress Tests 74 4.2 Interbank Contagion Effects 79 4.3 Macro Stress Test for Oman: Assumptio ns, Scenarios and Projections 80 4.4 Assuptions Underlying the Liquidity tress Testing 81

List of Figures

Page No 3.1 Process Flow for Bank Resolution in Oman 62

List of Graphs

Page No 1.1 Global Output 01 1.1.1 TFP Growth 1990-2015 14 1.1.2 Average TFP Growth 15 1.2 China and India real GDP Growth 02 1.2.1 Private Investment Function 19 1.3 Oman real GDP Growth Estimates 03 Page No 1.3.1 Actual and Forecast of the Default Rate 23 1.3.2 Out-of-Sample Projection, Oil Price Shock 24 1.3.3 Out-of-Sample Projection, Overnight Interest Rate Shocks 24 1.3.4 Out-of-Sample Projection, Combined Oil and Interest Rate Shocks 25 1.4 IMF Forecast Revision real GDP Growth Rate 03 1.4.1 The Phillips Curve 27 1.4.2 Calvo Price Equation 27 1.5 Total Investments as a Percent of Current GDP 04 1.5.1 Surplus and Debt Level 28 1.5.2 Debt-GDP and Growth Rate 30 1.6 Oman Nominal GDP Growth 04 1.6.1 Import Demand Function 32 1.7 Measures of the Output Gap 05 1.8 Oman Oil Prices 05 1.9 Brent Oil Prices 05 1.10 Foreign Reserves 06 1.11 GCC Real Exchange Rates 06 1.12 Global Inflation Rate 07 1.13 Oman’s Inflation Rate 07 1.14 Balance/Nominal GDP 08 1.15 External and Domestic Government Debt/GDP Ratio 08 1.16 Current Account percent of GDP 09 1.17 The Trade Account 09 1.18 Credit Growth 09 1.19 Narrow Money (M1) Growth 10 1.20 Broad Money (M2) Growth 10 1.21 M1 Growth 10 1.22 M2 Growth 11 1.23 VIX Index 11 1.24 MSM Performance 11 2.1 Assets / Structure of Financial Sector 34 2.1.1 Banking Stability Map 35 Page No 2.2 Growth in Banks Assets 34 2.2.1 Banking Stability Map 35 2.3 Uses of Funds 36 2.4 Flows in Asset Components 36 2.5 Flows in Asset Components 36 2.6 Private Credit Gap 37 2.7 Gross Loans 38 2.8 Risk Weighted Assets 38 2.9 Credit Growth 38 2.10 Foreign Currency Loans to Total Business Loans 39 2.11 Real Estate Financing & Exposure 39 2.12 Household Indebtedness to Income 39 2.13 Trends in Non-Performing Loans 40 2.14 Provisions Against NPLs 40 2.15 New NPLs and Recoveries 40 2.16 Restructured Loans 43 2.17 Special Mentioned to Gross Loan Ratio 43 2.18 Category-wise Breakup of NPLs 43 2.19 Policy and Overnight Interbank Rates 44 2.20 MSM Index and Returns 45 2.21 Stock Market Exposure of Banking Sector 45 2.22 Forex Exposure to Teir-1 Capital 46 2.23 Foreign Currency Assets & Liabilities 46 2.24 Cash Reserve Maintenance 46 2.25 Gap to Asset Ratio (in per cent) 47 2.26 Lending Ratio and Credit to Deposit Ratio 47 2.27 Sources of Funds 47 2.28 Customer Funding Gap 48 2.29 Breakup of Bank Deposits 48 2.30 Structure of Deposits 49 2.31 HHI of the Banking Sector 49 2.32 Banking Sector Concentration-by Total Assets 50 Page No 2.33 Concentration of Loans and NPLs 50 2.34 Credit Concentration 50 2.35 Solvency Profile of Banks 51 2.36 Frequency Distribution of CAR 51 2.37 Earnings Indicators 52 2.38 Composition of Non-Interest Expenses 52 2.39 Islamic Banking Indicators 53 2.40 Asset Structure of NBFIs 53 2.41 Mutual Funds 55 2.42 Assets Structure of FLCs 55 2.43 Trends in Non-Performing Loans 56 2.44 Funding Structure of FLCs 56 2.45 Earnings Indicators - FLCs 57 2.46 Insurance Penetration and Density 57 2.47 Gross Premiums and Retention Ratio 58 2.48 Net Claims and Loss Ratio 58 2.49 Money Exchange Companies 58 3.1 Tends in Value 66 3.2 Trends in Volume 66 3.3 Modes of payment: Tends in Value 67 3.4 Modes of payment: Tends in Volume 67 3.5 Daily Aggregate Closing Balances 68 3.6 Liquidity Concentration 68 3.7 Liquidity Concentration 68 3.8 Daily Payment Concentration 69 3.9 Shares in Payment System Activities 70 3.10 Cheque Clearing Duration 70 3.11 Reasons for unpaid cheques 71 4.1 Losses Resulted From the Differnet Risk Factors Under the Assumed Stress 72 Scenarios 4.2 CRAR of Local Banks After Shocks Under Balance Sheet Approach 72 4.3 CRAR of Foreign Banks After Shocks Under Balance Sheet Approach 73 Page No 4.4 Increase in The Current NPLs Before CRAR Drops Below CBO Requirement 73 For Local Banks 4.5 Increase in The Current NPLs Before CRAR Drops Below CBO Requirement 75 For Foreign Banks 4.6 Impact of 5 Largest Banks’ Borrowers Default on Their CRAR for Local Banks 75 4.7 Impact of 5 Largest Banks’ Borrowers Default on Their CRAR for Foreign Banks 75 4.8 CRAR of Local Banks After Shocks Under Moderate Macro Scenarios 77 4.9 CRAR For Local Banks After Shocks Under Severe Macro Scenarios 77 4.10 CRAR of Foreign Banks After Shocks Under Moderate Macro Scenarios 78 4.11 CRAR of Foreign Banks After Shocks Under Severe Macro Scenarios 78 4.12 Average Days of Survival Using Cash and Securities 78 4.13 CRAR of Foreign Banks After Shocks Under Moderate Macro Scenarios 78

List of Tables

Page No 1.1 World Trade 02 1.1.1 Dynamic-OLS Estimate of Aggregate Production Function 13 1.2 Demand Indicators 04 1.2.1 OLS Estimates of Oman’s Investment Demand equation, 2001 to 2015 17 1.3 Global Oil Supply/Demand 06 1.3.1 Out-of-Sample Projections of the Default Rate: Oil price shocks Scenarios 22 1.3.2 Out-of-Sample Projections of the Default Rate: Interest Rate Shock Scenarios 22 Out-of-Sample Projections of Default Rate: Combined Oil and Interest Rate 1.3.3 22 Shocks Scenarios 1.5.1 IMF Projections 28 1.5.2 Sustainability Gap Results 30 1.6.1 Import Demand Function 32 3.1 Capital as percent of Risk Weighted Assets 65 3.2 Shares in the Payment System 69 4.1 CRAR after Inter-Bank Contagion 76 4.2 Assumptions / Scenarios / Projections for Macro Stress Test for 2017 77 LIST OF ABBREVIATIONS

ACH Automated Clearing House ATM Automated Teller Machines BCBS Bank Credit and Statistical Bureau BIS Bank for International Settlement BoP Balance of Payments CBO Central Bank of Oman CBI Conventional Banking Institutions CCB Capital Conservation Buffer CES Constant Elasticity of Substitution CET1 Common Equity Tier 1 CPI Consumer Price Inflation CRAR Capital to Risk-weighted Assets Ratio CRWA Credit Risk Weighted Assets DR Disaster Recovery D-SIBs Domestic Systemically Important Banks DW Durbin Watson Test Value ECC Electronic Cheques Clearing EDA Emerging and Developing Asia EU European Union FDI Foreign Direct Investment FSB Financial Stability Board FY Financial Year GCC Gulf Cooperation Council GDP Gross Domestic Product G-SIB Global Systemically Important Banks G-SIFIs Global Systemically Important Financial Institutions HHI Herfindahl-Hirschman Index HP Hedrick Prescott HQLAs High Quality Liquid Assets IAS International Accounting Standards IBIs Islamic banking institutions IBP Initial Budgetary Position IEA International Energy Agency IFRS International Financial Reporting Standards IMF International Monetary Fund INSOL Insolvency & Bankruptcy Professionals LCR Liquidity Coverage Ratio LTC Long-Term Change in the Primary Balance M0 Reserve Money M1 Narrow Money M2 Broad Money MENA Middle East and North Africa MoF Ministry of Finance MRWA Market Risk Weighted Assets MSM Muscat Securities Market NBFI Non-Banking Financial Institution NCSI National Center for Statistics and Information NEER Nominal Effective Exchange Rate NOE Non-oil Expenditure NPL Non-Performing Loans NRI Node Risk Index NSFR Net Stable Funding Ratio OECD Organization for Economic Cooperation and Development OPC Oil Producing Countries PD Probability of default PSE Public Sector Enterprises RHS Right Hand Side RO Rial Omani ROA Return on Assets ROE Return on Equity RoW Rest of the World RRP Recovery and Resolution Plan RTGS Real Time Gross Settlement RWA Risk Weighted Assets S&P Standard & Poor’s SME Small and Medium Enterprise SVAR Structural Vector Auto-Regression TA Total Assets TFP Total Factor productivity TR Trade Repository U.K. United Kingdom UAE United Arab Emirates UIP Uncovered Interest Rate Parity US; USA United States of America USD United States Dollar WEO World Economic Outlook YoY Year on Year FINANCIAL STABILITY ASSESSMENT OF OMAN AN OVERVIEW

The Regulatory and Supervisory Regime in Oman is Rigorous. During the Year, the Regulations and Laws were Fine-tuned to Facilitate Economic Growth while Ensuring Financial Stability 1. During 2016, Central Bank of Oman made significant inroads in ensuring that it’s regulatory framework and supervisory policies cater to the changing operating conditions and needs of the economy while serving its stated objective of ensuring of financial stability to facilitate economic growth. Some regulations were adopted to ensure that Oman complies with the international legislation and global best practices while other regulation and policies were fine tuned to cater to the domestic needs. 2. During the year, a new Anti-Money Laundering Law was promulgated, Bank Resolution Framework was formulated, and policies to improve Financial Inclusion were introduced. Furthermore, guidelines on Sound Compensation Practices, Correspondent Banking Relationships, and adoption of IFRS 9 were issued. Oman is also on track with its implementation schedule of Basel III capital and liquidity standards. MACRO-FINANCIAL SCENARIO Slowdown in Economic Growth is Expected to Reverse during Next Year 3. Oman’s real GDP grew at 5.7 per cent in 2015. The IMF’s estimates for real GDP growth are 3.05 per cent in 2016 and 0.38 in 2017. The economy is expected to return to higher growth from 2018. IMF forecasts growth of 3.8 per cent in 2018, with an average growth of 2.4 per cent over the period 2018-2022. Performance of Non-oil Sector Reflects Diversification Efforts 4. Although the overall figures display slow economic performance, the performance of non- hydrocarbon GDP reflects the Sultanate’s diversification efforts while the robustness of Oman’s financial sector provides a cushion for the potentially negative effects on financial stability. Oil Prices Improved but Remain Uncertain. Government Expenditure Remained Heavily Dependent on Oil Revenues 5. OPEC and Non-OPEC oil producers agreed to reduce the supply of crude in an attempt to increase crude prices. The agreement pushed oil prices higher in late 2016. The upswing in crude prices was hampered by high crude inventory as well as quick increase of rig count in the United States. Oman’s oil price softened during the first quarter of 2017 to reach US $ 51.22 per barrel at the end of April 2017. The oil market is uncertain, however, Oman oil prices are anticipated to average between US $ 50 to US $ 55 per barrel in 2017 6. Government expenditure remained heavily dependent on oil prices. The 2017 budget is benchmarked on oil prices averaging US $ 45 per barrel. Thus, a timely fiscal consolidation would improve the current account and strengthen the stability of the currency and the financial system in the Sultanate.

Financial Stability Report - 2017 I Oman Maintained Adequate Level of External Reserves and the Peg of Omani Riyal to the US $ Remained Intact 7. The Rial’s peg to the US $ is fully intact. Total foreign reserves at the CBO increased substantially in 2016, which are adequate to maintain the peg. Global Inflationary Pressures are Picking up while Domestic Inflation Remained Low 8. World inflation averaged 2.8 per cent in 2016. It is projected to increase to 3.5 per cent in 2017 due to a number of factors including increase in aggregate demand and commodity prices. The general outlook for the upcoming years (2018 to 2020) remains stable, however, with an inflation rate of around 3.3 per cent. Inflation in advanced economies is expected to increase significantly in 2017; 2 per cent compared to 0.7 per cent in 2016. The MENA region’s inflation rate is expected to average at 8 per cent in 2017. 9. The CPI inflation rate in the Sultanate stood at 1.1 per cent in 2016. NCSI reported a YoY inflation rate of 2.8 per cent in March 2017. The IMF projects the Sultanate’s inflation to average 4.1 per cent during 2017 and stabilize around 3 per cent until 2020. Twin Deficit Continued, however, Consolidation Efforts are Underway 10. The fiscal deficit increased to RO 5.2 billion or 20.4 per cent of GDP in 2016. However, the estimates suggest that the fiscal deficit will decline in 2017 and 2018 based on expectations of fiscal consolidation and increasing revenues from taxes, removal of subsidies on fuel, and expected higher oil prices. 11. Low oil prices placed pressures on Oman’s current account balance. The current account deficit stood at about 15 per cent of nominal GDP in 2015 and 2016. It is expected to be 12 per cent in 2017 and 11 per cent in 2018. 12. The government debt reached US $ 19.8 billion by the end of 2016, which is 32.6 per cent of GDP and it is projected to increase in 2017. FINANCIAL INSTITUTIONS BANKS Banking Sector Remained Resilient amid Challenging Economic Conditions. Short-term Risks to Financial Stability further Subside as Commodity Prices Stabilised 13. The banking sector in Oman continued to remain resilient amid challenging economic conditions. Although the twin deficit continued to be there while the government is moving towards fiscal consolidation, the crude prices have risen from their lows of the last year. The new oil price range is now better understood, which has allowed better fiscal planning by the government. 14. Relatively improved crude oil prices, ongoing fiscal reforms, and satisfactory financial performance by the banking sector meant that the short-term risks to the financial stability further subside in 2016 which is evident from most of the banking stability indicators.

II Financial Stability Report - 2017 15. The banking stability index also show that on balance, the stability of the banking sector stayed intact as the sector remained well capitalized, profitable, and fairly liquid with low infection ratio during the year under review. Banks Continued to Expand, however, the Growth Rate Decelerated 16. Despite some slowdown in the economic activities, the banking sector continued to expand with strong credit offtake. Total Assets (net) of the banking sector exceeded RO 29 billion (Gross Assets RO 30.25 billion) at the end of 2016; thus, registering a growth of 6 per cent during the year. This growth is lower than previous years’ growth. However, deceleration in growth is not unexpected considering the challenging macroeconomic conditions faced by Oman and banks’ need to adjust to the new normal of lower oil prices and rising interest rates. 17. Notwithstanding these short-term adjustments, the banking sector in Oman is set for solid growth over the next several years on the back of economic diversification under ambitious Tanfeedh plans and a relatively low banking sector penetration. Private Sector Leverage Increases, however, the Credit Growth was not Considered Excessive 18. The ‘Private Credit to Non-Oil GDP’ ratio continued to rise during 2016. However, the existing level of corporate and household debt (in relation to the GDP) was far from excessive, therefore, the debt overhang remained highly unlikely and the increasing credit-to-GDP ratio indicates a positive development. 19. The Private Sector Credit to GDP Gap also increased during 2016. However, this does not signal build-up of system-wide risks as this increase in the Gap was driven largely by a sharp fall in nominal GDP (due to fall in oil prices) rather than excessive credit growth. Low NPL Ratios Suggest Well-contained Credit Risk 20. The banks have been able to grow their lending portfolio without much increase in NPLs, which augers well for the credit risk in the banking sector. The NPLs at the end of 2016 were 1.78 per cent (2015: 1.73 per cent) of the gross loans. The low NPL ratio suggest satisfactory asset quality and well contained credit risk. Moreover, the existing loan portfolio of banks is well covered against expected losses through adequate provisions with coverage ratio (provisions to NPLs) of 70 per cent (148 per cent including general provisions) which compares favorably with regional cohorts. Banking Sector Concentration Remained Moderately High – D-SIBs Framework and Bank Resolution Framework Help Deal with the Systemically Important Banks 21. The degree of concentration in the Omani banking sector, as measured by Herfindahl- Hirschman Index (HHI), reflects that concentration in the banking sector in Oman is moderately high but remains in line with the regional cohorts. In order to deal with the risks emanating from the presence of large institutions, the CBO had issued guidelines to identify, supervise, and regulate Domestic Systemically Important Banks. Moreover, as a part of the preparedness, Bank Resolution Framework is being finalized to amicably deal with systemically important banks.

Financial Stability Report - 2017 III Sectoral Credit Concentrations Exist. However, Stiffer Prudential Norms Counter-balance the Risks 22. Sectoral distribution of credit, particularly in the household loan segment, highlights credit risk concentration in banking sector. Banks also have substantial direct and indirect exposure to the real estate sector. At present, overall, household credit risk indicators remain at low levels and there are no signs of significant stress in the Omani real estate market. Moreover, the prudential regulations on lending are expected to keep the risks in these sectors at manageable levels. Banks Remained Fairly Liquid, without any Signs of Serious Strain – Liquidity Conditions that Eased after Regulatory Changes are Expected to Further Improve following External Debt Raised by the Government 23. Amid a growing loan portfolio, the banks on average, comfortably maintained the cash reserve requirements without significant signs of strains. The liquidity conditions in Oman tightened because of the budgetary needs of the government and decreased inflows due to depressed oil prices. However, accommodating regulatory changes and external funding kept sufficient liquidity in the domestic market.

Sizeable Public Sector Deposits Expose the Banks to the Concentration Risk. However, Banks Remained Resilient to Deposit Runoff 24. Banks operating in Oman have traditionally low reliance on wholesale markets. Government deposits, however, remained an important source of funding for the banks. The high level of public sector deposits combined with the reduced cash-flows of the government in the wake of dwindling oil revenues could pose a covert yet potent risk of significant withdrawal of deposits form the banking sector. However, the risk of withdrawal is not imminent as the government resorted to borrowing from international markets to finance its budget deficit. Moreover, the stress tests showed that the banks operating in Oman remained fairly resilient to the assumed deposit runoffs. Policy and Interbank Interest Rates Increased in Line with the US Monetary Policy. Rising Interest Rates might Put Pressure on the Borrowers as well as Banks’ Bottom Lines 25. Following the Federal Reserve’s lead, the policy rates and interbank rates in Oman have started to increase. The rising policy rates have also been partially passed through to the retail deposit and lending rates. The rising interest rates might put pressure on the bottom lines of the banks. However, the stress testing exercise shows that the interest rate risk in banks is within reasonable bounds if they face a 200 basis point adverse movement in interest rates. MSM Closes on a Positive Note – Banks Exercise Caution while Taking Market Exposures 26. The MSM 30 index gained 6.96 per cent during the year 2016 and closed the year as the second best performing stock market within the region. The relatively better performance of the stock market reflects higher oil prices, improved and optimistic sentiments of the market regarding economic conditions and a confidence in the government to induce a turnaround with measured consolidation and focused development and diversification plans. The uncertainty in the stock market underscores the significance of caution while taking stock market exposures; thus, banks continued with their strategy to keep equity exposures at low levels.

IV Financial Stability Report - 2017 Solvency Position Remains Robust and Banks Maintained Profitability despite Rising Funding Costs 27. The banks remained adequately capitalized as the benchmark Capital to Risk Weighted Assets Ratio of the banking sector increased to 16.8 per cent at the end of 2016 from 16.5 a year ago. At system level, even the Tier-1 capital was sufficient to meet the regulatory requirements. 28. Despite challenging macroeconomic conditions, stringent prudential norms for credit, rising funding costs, and declining Net Interest Margin (NIM), the banks maintained their profitability. The banks netted over RO 438 million in pre-tax profits (2015: RO 439 million). The profitability ratios, ROA and ROE, remained steady at 1.5 per cent and 10.5 per cent, respectively. The healthy bottom line of the banks not only reinforced their buffers but also enhanced their ability to support future growth. Islamic Banking Showed Strong Growth. The Sector as a Whole is Gaining Systemic Importance 29. Islamic banking in Oman has achieved remarkable growth since its inception about four years ago. At the end of December 2016, the Islamic banking assets formed 10.3 per cent of the total banking sector assets. With an annual growth of 37 per cent, total assets held by Islamic banks and the Islamic banking windows of conventional banks exceeded RO 3 billion, while the total assets of foreign banks stood RO 1.9 billion at the end of 2016. 30. Islamic banking institutions (IBIs) recorded remarkable improvement in profitability. The aggregate pre-tax profits of IBIs during 2016 increased to RO 13.6 million from RO 1.6 million in 2015. Due to fast paced growth, the Islamic banking sector as a whole is gaining systemic importance. NON-BANK FINANCIAL INSTITUTIONS (NBFIs) NBFIs Continue to Provide Vital Financial Services – FLCs and Insurance Dominate the Sector 31. NBFIs continued to play their important role in the financial sector by providing supplemental financial services like financing various niche markets, provision of insurance, asset management services, remittances, and currency exchange services. In terms of asset size, the Finance and Leasing Companies (FLCs) and Insurance companies remained the leading players in the NBFIs sector and accounted for over 51 per cent and 44 per cent of the total NBFIs assets, respectively. PAYMENT AND SETTLEMENT SYSTEMS Concentration Exists in the Payment and Settlement Systems, however, it Remained Robust without any Serious Disruption 32. The Payment and Settlement System continued to provide uninterrupted services without any serious operational issues. Aggregate volumes and values settled through the payment and settlement systems remained high with a significant gain in settlement volumes but a slight decrease in the settlement values. 33. The average daily payment concentration level in the system declined significantly during 2016. However, in terms of transactional concentration, about half of the turnover was handled by only three banks.

Financial Stability Report - 2017 V STRESS TESTING OF THE BANKING SECTOR Despite Challenging Macroeconomic Conditions, Banks Remained Resilient to Stressed Scenarios 34. Despite the prevailing macroeconomic challenges, the banks remained resilient to stressed scenarios at the aggregate level. Results of different solvency stress tests did not flag an increased vulnerability of solvency of the banks mainly due to their high capital adequacy ratio as well as their limited exposure to equity and forex. The robustness of the banking sector is also echoed in the macro-financial stress tests where banks on average remained solvent even in the severe scenario. Banks Remain in Comfortable Position when Faced with the Liquidity Shocks 35. When assessed with respect to the international benchmarks (of one business week or five days), all of the banks were found to be in a comfortable position to face the liquidity shocks under the assumed stress scenarios. At the end December 2016, the banking system as a whole would be able to sustain a liquidity shock for an average of 18 days with only cash and a total of 20 days with cash and securities.

VI Financial Stability Report - 2017 Chapter I Macro-Financial Outlook

The financial sector has been stable since the great fall of oil prices in 2014. The exchange rate peg is the nominal anchor of the economy and the main objective of monetary policy. It remained intact and supported by total foreign reserves at the CBO, which have increased substantially in 2016. However, the economy has contracted in nominal terms in 2016 and aggregate demand condition has been weak. Further, imbalances in the fiscal position, and the current account remained. The trade balance was positive, however. In addition, there is evidence that the interest rates, the inflation rate, and the real exchange rate have slightly risen. Ceteris-paribus, growth is expected to resume next year.

The Global Growth Picture & Major Trading Graph 1.1 Global Output Partners % Somewhat positive

World 1.1. The data show significant increase in 5 investments, manufacturing output and trade 4 Advanced in late 2016 despite the weaknesses in global 3 Economies economic performance in 2015 and early 2016. 2 Emerging/ The IMF suggests that the global economy Developing 1 Economies headed towards an upward cyclical recovery USA during the 2nd half of 2016 describing it as 0 Source: 2015 IMF 2016 2017 “gaining momentum” which is expected to Source: IMF continue in 2017. Although shrouded with uncertainty, commodity prices also picked up due to increased confidence. The agreement between OPEC and non-OPEC oil exporters seem to have reduced market supply and supported an uptick in oil prices. However, oil prices were capped by two forces: (1) increased production of U.S. shale oil, and (2) high inventories of crude oil due to cumulative levels of production by exporting countries. 1.2. Global output measured by real GDP growth was 3.1 per cent in 2016. Advanced economies’ output growth averaged 1.7 per cent while emerging markets averaged 4.1 per cent (Graph 1.1). The United States recorded a growth of 1.6 per cent in real GDP during 2016,

Financial Stability Report - 2017 1 Chapter I and is expected to increase to 2.3 per cent in 1.4. China and India are Oman’s largest 2017. The U.S. unemployment has reached 4.7 trading partners, which have significant effects per cent, which supported the Fed’s decision on the macro and financial stability through to raise interest rates twice within 6 months various channels such as trade, investments, reaching 1.0 per cent with further possible and remittances. The Chinese economy showed increases during 2017. Rising U.S. interest robust performance in 2016 with a real GDP rates poses a capital flight risk from emerging growth of 6.7 per cent albeit marginally lower market economies. than the 6.9 per cent in 2015. This small difference is unlikely to have an adverse effect on 1.3. The Euro zone’s growth remained the Omani economy in 2017. India’s economic constant at 1.7 per cent in 2016, which is an growth has declined in 2016 compared to the increase of 0.1 per cent from 2015’s growth previous year (7.9 per cent in 2015), but it is figure. expected to pick up significantly. India’s output growth is expected to reach to 7.2 per cent in Graph 1.2 2017. Graph 1.2 shows a summary of IMF’s China and India real GDP Growth published figures. % 1.5. Trade volumes decreased in 2016 in advanced economies, but increased significantly in emerging and developing economies. 10 Advanced markets’ imports and exports grew by 2.4 and 2.1 per cent respectively, compared 5 with growth of 4.4 per cent in imports and

0 3.7 per cent in exports in 2015. Emerging and 2015 2016 2017 developing markets’ imports grew by 1.9 up China India from -0.8 per cent in 2015, and exports grew Source: IMF by 2.5 per cent in 2016 compared to 1.4 per cent in the previous year (Table 1.1). Enhanced performance of global trade indicates increased income levels in both advanced and emerging/ developing economies, which strengthens global and regional financial stability.

Table 1.1 World Trade Volume (% Growth) 2015 2016 2017 2018 Imports Advanced Economies 4.4 2.4 4.0 4.0 Emerging and Developing Economies -0.8 1.9 4.5 4.3 Exports Advanced Economies 3.7 2.1 3.5 3.2 Emerging and Developing Economies 1.4 2.5 3.6 4.3 Source: IMF

2 Financial Stability Report - 2017 Macro-Financial Outlook

1.6. A few anticipated global shocks include: Oman’s Growth Picture First, the U.S. withdrawal from the Paris Climate Anticipated slowdown, but growth resumes next Accord will affect hydrocarbon production. year More supply of shale oil will reduce oil prices. Second, China is the second largest economy 1.7. Economic growth has a positive in the world and the persistent increase in its effect on financial stability. It invigorates private debt to GDP ratio and housing market the financial markets, reduces systemic risk, are causes of concern. Financial instability in and cushions adverse foreign shocks. Most China could affect the global financial markets important aspect of economic growth is adversely. Third, the dynamics of Brexit could Total Factor Productivity Growth (TFP). destabilize Europe’s financial markets. Box 1.1 includes our estimates of TFP for Oman and other GCC countries. TFP affects investments and the current account directly. Our estimate indicates that Oman’s TFP growth is positive. Graph 1.3 1.8. The latest published figures state that Oman real GDP Growth Estimates Oman’s real GDP growth was 5.7 per cent % in 2015 (Graph 1.3), The IMF and the World Bank estimates for real GDP growth in 2016 were 3.05 per cent and 2.2 per cent respectively (Graph 1.3). Official figures show that Non- Hydrocarbon real GDP grew by 3.2 per cent in 2015, but that is expected to decrease to 2 per cent in 2016 according to the World Bank report. Source: NCSI, IMF, World Bank 1.9. The IMF World Economic Outlook, which was released in April 2017, included revisions of Oman’s economic forecasts that were made in October 2016. Growth forecast of Graph 1.4 2017 was cut significantly from 2.6 percent to IMF Forecast Revision Real GDP Growth Rate about 0.38 percent. However, the forecasts are higher over the next five years. 1.10. It forecasts growth to be 3.8 percent

6 in 2018, then declines, but remains almost constant over the years 2019 to 2022, averaging 4 2.4 percent over the period 2018-2022 (Graph 2 1.4). 0 2017 2018 2019 2020 2021 1.11. Similarly, nominal GDP growth forecast is revised upward. The forecasts are based on the Oct-­‐16 Apr-­‐17 Source: IMF assumption that Brent oil prices will be around 55 USD / barrel on average over the period 2018 to 2022. The next five-year forecasts look positive although one should be mindful of the forecast uncertainty.

Financial Stability Report - 2017 3 Chapter I

Private investment is highly influenced by TFP, Graph 1.5 Total Investments as a Percent of Current GDP and completely crowded-out by government current expenditures. The data also show that foreign direct investments (FDI) has a positive effect on private investments. 1.13. Nominal GDP growth declined by 5.1 per cent in 2016 due to continued downward pressure from low oil prices during the year as displayed in Graph 1.6. Petroleum activities declined by 23.7 per cent compared to 2015, however, non-petroleum nominal GDP Source: IMF increased slightly during 2016 with a growth rate of 0.58 per cent albeit lower than 2015 Graph 1.6 growth of 2.7 per cent. Oman Nominal GDP Growth % 1.14. The performance of non-hydrocarbon GDP reflects the Sultanate’s diversification efforts which provides a cushion from the 10 potentially negative shocks. 0 -­‐10 2015 2016 1.15. Aggregate demand conditions were -­‐20 -­‐30 weak in 2016, as expected, and reflected -­‐40 in nominal GDP, however, private sector -­‐50 employment showed significant increase in Nom-­‐GDP Growth Oil GDP Growth Non-­‐Oil GDP Growth 2016 and Q1 2017. Table 1.2 reports some of Source: NCSI the aggregate demand indicators.1 Graph 1.7 plots the output gap measured as the deviations 1.12. Investment growth drives output of the real GDP from an HP filter’s trend. The growth. The latest IMF forecast revision (April cyclical fluctuations of the real price of oil are 2017) adjusted estimates of Oman’s investment/ also plotted for comparison. The output gap is GDP upwards by 1 per cent in 2017 and by 2.5 an indicator of the aggregate demand conditions per cent in 2018 averaging between 33 per cent which have been weak, and has been negative and 33.5 per cent investment expenditure/GDP (output is below potential trend) since 2015. for the next 5 years (Graph 1.5), which has a positive impact on financial stability. Box 1.2 estimates an investment function for Oman. 1 NCSI Statistical Bulletin Vol. 28, May 2017.

Table 1.2 Demand Indicators Jan/Apr 2017 Jan/Apr 2016 Change (%) No. of Issued Properties 83,307 87,489 -4.8 No. of Sales Contracts 21,675 26,883 -19.4 No. of New Vehicles Registered 24,515 32,816 -25.3 No. of Omani Employees in the Private Sector 236,645 210,074 12.6 No. of Expat Employees in the Private Sector 1,864,227 1,763,710 5.7 Source: NCSI

4 Financial Stability Report - 2017 Macro-Financial Outlook

Oil prices Improved but uncertain Graph 1.7 1.16. OPEC and Non-OPEC oil producers Measures of the Output Gap agreed to reduce the supply of crude in an attempt to increase prices, the agreement 0.4 increased oil prices in late 2016. 1.17. As shown in Graph 1.8, Oman’s oil -­‐0.1 futures monthly prices peaked at USD 55.9 per barrel in 2016 from a low of USD 40.44 per

-­‐0.6 Dec-­‐06 Oct-­‐07 Aug-­‐08 Jun-­‐09 Apr-­‐10 Feb-­‐11 Dec-­‐11 Oct-­‐12 Aug-­‐13 Jun-­‐14 Apr-­‐15 Feb-­‐16 Dec-­‐16 barrel. Benchmark Brent crude peaked at USD 58.7 per barrel in the end of 2016 from a low of Real Oil Price Output gap (HP Cilter) USD 43.46 per barrel (Graph 1.9). Source: Staff Calculations 1.18. The upswing in crude prices was hampered by continued reports of high crude inventory as well as quick increase of rig counts Graph 1.8 in the United States. Oman’s oil price softened during the first quarter of 2017 to reach USD Graph Oman Oil 1.8 Prices (USD pb) 51.22 per barrel as of the end of April. Oman Oil Prices (USD pb) 1.19. The oil market is highly uncertain, 69 and the OPEC’s April 2017 oil market report estimates 2017’s oil demand to increase by 1.27 59 million b/d averaging 96.32 million b/d, while 49 the International Energy Agency estimates demand to increase by 1.3 million b/d averaging 39 Jan-­‐15 Apr-­‐15 Jul-­‐15 Oct-­‐15 Jan-­‐16 Apr-­‐16 Jul-­‐16 Oct-­‐16 Jan-­‐17 96.7 million b/d (Table 1.3). Both estimates indicate a lower supply during 2017, which might Source: Bloomberg rebalance the glut in oil inventories. However, the report also indicates increased supply from Non-OPEC countries, mainly U.S. producers.2

Graph 1.9 1.20. Government expenditures are heavily Brent Oil Prices (USD pb) dependent on oil prices. The 2017 budget is

Graph 1.9 benchmarked on oil prices averaging USD 45 Brent Oil Prices (USD pb) per barrel. Thus, a timely fiscal consolidation 72 would improve the current account balance and strengthen the stability of the currency and the 62 financial system in the Sultanate. 52 1.21. Box 1.3 is a structural VAR model for Oman. We use the model to measure the effects 42 Jan-­‐15 May-­‐15 Sep-­‐15 Jan-­‐16 May-­‐16 Sep-­‐16 Jan-­‐17 of oil price shocks on the economy and on stress testing the aggregate default rate risk. Source: Bloomberg

2 OPEC Monthly Oil Market Report, April 2017 and the IEA Oil Market Report 2017

Financial Stability Report - 2017 5 Chapter I

Interest Rate and the Real Exchange Rates Graph 1.10 Foreign Reserves USD Million On the rise 1.22. The Rial’s peg to the USD remains intact. Total foreign reserves at the CBO have 22,000.00 increased substantially in 2016. 20,000.00 18,000.00 Graph 1.10 plots the foreign reserves held at 16,000.00 the CBO. The level of total reserves is adequate 14,000.00 to achieve the CBO’s objective of maintaining 12,000.00 the peg at its level. This level of reserves is 10,000.00 2016 2015 also adequate to maintain the usual import Source: CBO benchmark. Meeting these two objectives supports financial stability. 1.23. We plot the real depreciation rate for the 3 Graph 1.11 GCC countries in Graph 1.11. Real depreciation, Graph GCC Real 1.11 Exchange Depreciation Rate which measures th change in purchasing power of the currency, reduces import demand and GCC Real Exchange Rate consumption. furthermore, investors in Rial- 0.1 denominated assets demand more compensations 0.05 in terms of higher interest rates.

0 2000 2002 2004 2006 2008 2010 2012 2014 2016 -­‐0.05 3 RO’s Real Exchange Rate (RER) was calculated using (SP/P*) where (S) is the fixed exchange rate defined as the price of domestic currency in U.S. Dollar, and Bahrain Kuwait Oman Qatar KSA UAE (P) is the CPI and (P*) denotes U.S. CPI. Thus, the Source: Source: Staff Staff Calculations Calculation depreciation rate is the first-differenced of the log og the RER.

Table 1.3

Global Oil Supply/Demand (Million b/d)

IEA Figures 2016 2017

Avg. oil demand 96.6 97.9

Avg. oil Supply 96.98 96.71

OPEC Figures 2016 2017

Avg. oil demand 95.05 96.32

Avg. oil Supply N/a N/a

Source: IEA Oil Market Report, OPEC Monthly Oil Market Report April 2017

6 Financial Stability Report - 2017 Macro-Financial Outlook

1.25. In line with the global inflationary Graph 1.12 pressures, the CPI inflation rate in the Sultanate was 1.1 per cent in 2016. This is an increase Global In�lation Rate by 1 per cent over the inflation rate in 2015. NCSI reported a YoY inflation rate of 2.8 per 10 cent in March 2017.4 This was supported by a sharp increase in transportation price level of 5 10.8 per cent. The IMF projects the Sultanate’s 0 inflation to average 4.1 per cent during 2017 2016 2017 2018 2019 2020 and stabilize around 3 per cent until 2020. World The expected increase in the inflation rate is Advanced economies Source: IMF consistent with the removal of subsidies, higher expected interest rates, and the debt-financed budget deficit (Graph 1.13). These inflation rates are still in single digits and not expected to be destabilizing to the macro-economy or to Graph 1.13 create any financial instability.

Oman’s In�lation Rate 1.26. We model inflation in Box 1.4. We use two models. One is where inflation is a function 6 of expected inflation and the output gap (i.e., the deviation of real GDP from potential output). 4 The second model is where the inflation rate 2 is a function of expected inflation and the 0 real exchange rate depreciation rate (i.e., the 2015 2016 2017 percentage change of the real exchange rate).

NCSI IMF The latter model fits Oman’s data rather well. Source: NCSI, IMF Government expenditures in Oman have significant effect on inflation, which supports the fiscal theory of the price level. Fiscal Balance and Debt Global and Domestic Inflation Timely consolidation would enhance the Picking up economy 1.24. World inflation averaged 2.8 per cent in 1.27. Government expenditure is a key driver 2016, and projected to increase to 3.5 per cent of the Omani economy. It consists of current in 2017 due to a number of factors including expenditures, which covers wages and salaries increase in aggregate demand and an increase in for the public sector of more than 180 thousand commodity prices since the 3rd quarter of 2016. employees, and capital investment expenditures. The general outlook for the upcoming years Under the current peg, government expenditures (2018 to 2020) remains stable, however, with affect the price level, the current account, and an inflation rate around 3.3 per cent. Inflation investments. Thus, it has a significant effect on in advanced economies is expected to increase financial stability. significantly in 2017; 2 per cent compared to 0.8 per cent in 2016. The MENA region’s inflation rate is expected to average at 8 per cent in 2017 (Graph 1.12). 4 NCSI Monthly Statistical Bulletin, April 2017

Financial Stability Report - 2017 7 Chapter I

1.28. The Sultanates fiscal deficit increased to RO 5300 million by end of 2016, which represents a 14.4 per cent increase from the end of 2015. Graph 1.14 shows that the 2015’s fiscal balance/ GDP was -17.2 percent, and reached -20.8 per cent in 2016. However, on a positive note, the IMF estimates suggest that the fiscal deficit will decline in 2017 and 2018 based on expectations of fiscal consolidation, increasing Graph 1.14 Fiscal Balance/Nominal GDP revenues from taxes, and expected higher oil % prices. The fund estimates fiscal balance/ GDP to be -9.8 per cent and -8.4 per cent in 2017 and 2018 respectively. 0.0 2015 2016 1.29. The government budget deficit is -­‐5.0 financed by debt, which is largely external. The -­‐10.0 debt reached USD 20.8 billion, which is 31.4 -­‐15.0 per cent of GDP by the end of 2016 and it is -­‐20.0 projected to increase in 2017 (Graph 1.15). As -­‐25.0 Source: CBO a rule of thumb, increasing external debt / GDP ratio over time is undesirable. The literature on external debt suggests that there is no concrete measure for assessing the worsening level of debt. In some cases Debt / GDP ratio is used Graph 1.15 and in others the Debt / Exports ratio. These ExternalGraph and 1.15 Domestic Government Debt/GDP Ratio External and Domes;c Government Debt/GDP Ra;o ratios could differ significantly. Box 1.5 is 31.4 % our attempts to evaluate Oman’s external debt 20 30 sustainability. We provide a number of measures 25 15 13.4 20 and arguments, which indicate that the current 12.8 10 15 debt level is still sustainable. 2.4 4.8 4.6 4.9 4.9 10 5 6.6 7.3 5 1.30. That being the case, the government has 2 1.9 1.7 1.5 2.2 2.4 0 1.2 1.6 0 taken some important policy decisions, which 2011 2012 2013 2014 2015 2016 might have a positive effects on the overall Ext. Dom. Debt/GDP Ra;o (RHS) macro-economy, and financial stability. There Source: MOF has been steps to increase revenues, which includes increase in corporate income tax rate and introduction of VAT. The government began reducing expenditures in 2015. It reduced expenditures by 6.5 per cent in 2016. In addition, there are measures underway to increase foreign investments in industrial projects and tourism.

8 Financial Stability Report - 2017 Macro-Financial Outlook

Current account The deficit will be declining 1.31. The current account balance is savings Graph 1.16 minus investments. Savings have fallen below Current Account Percent of GDP Graph 1.16 investment spending since mid-2014. The Current Account Percent of GDP % government has not yet consolidated its balance. 5 1.32. Low oil prices placed pressures on Oman’s 0 2014 2015 2016 2017-­‐IMF 2018-­‐IMF current account balance. The IMF estimates were -­‐5 used to evaluate current account/nominal GDP. -­‐10 Graph 1.16 shows that the current account stands -­‐15 at -18.6 per cent of nominal GDP in 2016, down -­‐20 from -15.7 per cent in 2015. It is expected to be -12 per cent in 2017 and -11 per cent in 2018.

Source: CBO, IMF The Trade Account Turning downward 1.33. Oman has a trade account surplus historically. Graph 1.17 plots the RO values of Graph 1.17 exports, imports, and the trade balance. Trade TheGraph Trade 1.17 Account (RO Million) Graph 1.17 exports are mainly petroleum products, imports, however, play an important role in the economy of The Trade Account (RO Million) The Trade Account (RO Million) the Sultanate because they include capital goods 20000 20000 used in the production of domestic non-oil output, 10000 and services. Defining trade balance excluding Re- 10000 Exports results in a negative trade balance in 2015 0 0 1975 1980 1985 1990 1995 2000 2005 2010 2015 1975 1980 1985 1990 1995 2000 2005 2010 2015 (RO -262 million) and 2016 (RO -610 million). -­‐10000 The negative trade account is consistant with the -­‐10000 Exports & Re-­‐exports Imports Exports & Re-­‐exports existing negative current account. Box 1.6 is a Trade Imports Balance micro-founded import demand function for Oman. Trade Balance (ex. Re-­‐exports) Source: CBO Trade Balance (ex. Re-­‐exports) We model imports demand as a function of real GDP and the real exchange rate. We estimate the long-run equilibrium and the deviations of current imports from that long-run equilibrium. Imports Graph 1.18 have just fallen below equilibrium because of the Credit Growth fall in GDP and the real depreciation of the Rial. % Money and Credit 25000 55 20000 45 Showing signs of relative decline 35 15000 25 1.34. Aggregate credit supply continues to 10000 15 grow throughout 2016 albeit at a much slower 5000 5 pace than previous years. Graph 1.18 shows 0 -­‐5 1981 1988 1995 2002 2009 2016 that credit flow grew by 10 per cent in 2016 compared to 12 per cent in 2015. Broad Money Total Credit Credit Growth (RHS) (M2) increased by only around 2 per cent in 2016 compared to 10 per cent in 2015 and 15.3 Source: CBO per cent in 2014, while Narrow Money (M1) decreased by 7.3 per cent in 2016 compared to growth of 11.7 per cent in 2015 and 20.4 per cent in 2014 as displayed in Graphs 1.19 and 1.20.

Financial Stability Report - 2017 9 Chapter I

1.35. The nominal exchange rate should be consistent with the value of narrow money in Oman relative to the United States. The recent Graph 1.19 real depreciation of the currency implies that the Narrow Money (M1) Growth quantity of M1 relative to M1 in the U.S. has been % increasing lately, along with decline in oil prices 6000 60 relative to global commodity prices. Graphs 1.21 5000 50 40 and 1.22 plot the ten-year average growth rates of 4000 30 3000 20 M1 and M2 for Oman and the U.S. The money 2000 10 0 supply in Oman grew much faster than in the U.S. 1000 -­‐10 0 -­‐20 over the periods. These figures reflect the increase 1981 1988 1995 2002 2009 2016 in relative demand for money associated with high Narrow Money (M1) in Millions of Rial Omani oil prices before the sudden fall in 2014. M1 Growth (RHS) International Financial Markets Source: CBO Cautious stability 1.36. According to the latest IMF reports, international financial markets are showing signals Graph 1.20 of increased investor confidence, prospects of fiscal Broad Money (M2) Growth stimulus, and deregulations in the United States, % which pushed the S&P 500 to a record high during 15000 50 2017. Financial volatility remained relatively 10000 30 low during 2016 and early 2017 supporting the observed increase in confidence; the VIX index 5000 10 measures implied market volatility (Graph 1.23). 0 -­‐10 1981 1988 1995 2002 2009 2016 However, the sharp increase in market confidence raises potential risks of overvaluation in equity Broad Money (M2) in Millions of Rial Omani M2 Growth (RHS) asset prices. The S&P price-to-earnings ratio is witnessing an upswing, which may cause Source: CBO increased volatility in case expected deregulations and fiscal stimulus do not materialize. 1.37. Increases in the Fed’s interest rate Graph 1.21 negatively affect bond prices. Developments M1 Growth in U.S. monetary policy will affect the Omani government’s bond market price as demand might increase with increased yields.

0.2 Muscat Securities Market 0.15 Improving trends 0.1 0.05 1.38. The Sultanate’s financial market (banking,

0 securities market, insurance etc.) is small and the 80-­‐89 90-­‐99 00-­‐09 10-­‐16 relationship between global markets performance

Oman USA and Muscat Securities Market (MSM) is fuzzy. Source: CBO and FRED However, decreased volatility and improved investors’ sentiments in international markets are welcome, and might have a positive effect on MSM’s performance during 2017.

10 Financial Stability Report - 2017 Macro-Financial Outlook

1.39. Muscat Securities Market’s Index Graph 1.22 M2 Growth increased by 6.96 per cent at end of 2016 compared to 2015. It scored 5782.71 points, but the trade volume and value declined sharply since 2014 - i.e., highly correlated with the sharp 0.2 drop in oil prices. Equity trade volume declined 0.15 by 20 per cent while the value declined by 31 per 0.1 cent as shown in Graph 1.24. High uncertainty 0.05 outweighed market confidence during the past 3 0 years. This market’s performance has not affected 80-­‐89 90-­‐99 00-­‐09 10-­‐16 financial stability in any significant way. Source: CBO and FRED Oman USA 1.40. MSM’s Q1 performance for 2017 showed an increase of equity trade value of 14 per cent compared to the same period in 2016 with a slight Graph 1.23 increase in number of trades by 1.95 per cent. VIX Index Graph 1.23 VIX Index 1.41. The economic contraction since 2015 has fed to lower stock prices. Rising interest rates (and 65 declining money growth) will keep a downward 45 pressure on asset prices including securities and 25 stock prices. The effect of anticipated inflation on 5 stock prices is negative for a variety of reasons, such as declining anticipated corporate profits Jan-­‐00 Jan-­‐01 Jan-­‐02 Jan-­‐03 Jan-­‐04 Jan-­‐05 Jan-­‐07 Jan-­‐08 Jan-­‐09 Jan-­‐10 Jan-­‐11 Jan-­‐12 Jan-­‐13 Jan-­‐14 Jan-­‐15 Jan-­‐17 Jan-­‐06 Jan-­‐16 and rising production costs. Uncertainty about the stock market will increase, but future demand Source: Bloomberg may also increase because of low stock prices.

Graph 1.24 MSM Performance

20000 40

30 15000 20

10000 10

0 5000 -­‐10

0 -­‐20 2012 2013 2014 2015 2016 Index Shares Trades Shares Trade Value Bond Trades Bond Trade Value Market Capitalization

Source: MSM, Annual Reports Index Change % (RHS) Foreign Participation % (RHS)

Financial Stability Report - 2017 11 Chapter I

Box 1.1 Measuring Total Factor Productivity

TFP is a measure of efficiency of the economy. It We estimate (1) in the following specification using measures the degree of efficiency or the intensity OLS:4 of factor inputs in the production of output, which ln(Y / L )   ln(K / L )  ln(L )  ln A (2) has implications for the economy and the financial t t t t t t

sector. The Conference Board is the global data Output,Yt is real GDP. Labor, Lt is working-age- source of total productivity growth (TFP), it population (15-64). We create a measure for the reports growth rates of TFP over the period 1990 stock of capital using the Perpetual Inventory method

to 2015 and shows that the GCC has negative Kt  (1 )K0  It . We assume that the depreciation average growth rates, except for Kuwait and rate is 5 percent annually since GCC stock of capital Qatar which are 0.4 and 1 percent respectively. is relatively new, and that the initial stock of capital

We show that the Conference Board measure of K0 is three times as large as real GDP in the initial 5 6 TFP does not account for hydrocarbon as a factor period. The level of TFP is At . input in production. Accounting for hydrocarbon changes the picture. Graph 1.1.1 shows high correlation between the Conference Board estimates of TFP growth for TFP is typically measured by the Solow Residuals. Oman, Kuwait and Saudi Arabia, and the United The Conference Board, however, computes TFP as a Arab Emirates and our estimates. Tornqvist Index, which is a chained weighted average of factors.1 Now we estimate the following over a longer span, 1980 to 2015:7 We show that the conference Board estimates for Y  A*K  L H  , (3) GCC are the same as the Solow Residuals of the two- t t t t t factor input (capital and labor) production function, Where is the flow of hydrocarbon in Oman.8 H t but most importantly, the estimates differ from TFP The flow is measured by the production of oil in of a three-factor input production function (capital, tons plus the production of gas in oil-equivalent tons labor, and hydrocarbon). as reported by BP statistics. We estimate (3) in the following specification Hydrocarbon is an established industry in the GCC with large foreign, modern, and efficient investments * 9 ln(Yt / Lt )   ln(Kt / Lt )   ln(H t / Lt )   ln(Lt )  ln At , (4) thus, it significantly contributes to technology and knowledge transfer which increases average The method of estimation is Dynamic-OLS. The economic efficiency.2

We estimate the following production function with 4 Ideally we would use Dynamic-OLS, which is more efficient es- two inputs for GCC:3 timator (Phillips and Loretan, 1991). It accounts for endogeneity and for serial correlation because it is equivalent to a system of   (1) equations. However, the sample used by the Conference Board Yt  At Kt Lt is small, 1990-2015, which is inappropriate for the Dynamic- OLS.

5 The additional regressor Lt measures the return-to-scale such that     1. Thus   0 implies a constant-return-to- scale; positive implies an increasing-return-to scale, and nega- tive implies a decreasing-return-to scale.

6 The population data are from the World Bank Development In- dicators. Investments and GDP in constant prices are from the 1 Ideally we would be interested in measuring TFP for the finan- IMF/WEO data. The sample is 1990 to 2015. cial sector, but we do not have the necessary data to doing so, hence this analysis is about aggregate TFP. 7 Except for Kuwait, where the sample is 1995-2015 because of missing data for the 1990s. Therefore, one must interpret the Ku- 2 Note that human capital, intangible capital, R&D and other vari- wait results with caution. ables could be also be important inputs in the production pro- cess, but we do not have data or proxies to use in the regression. 8 Solow and Wan (1976) and Stiglitz (1974) use flow measures of oil in the production function. 3 We excluded Bahrain because hydrocarbon is negligible. We also excluded Qatar because missing investment time series do not allow us to measure the stock of capital. 9       1measures the return-to-scale.

12 Financial Stability Report - 2017 Macro-Financial Outlook

general specification in log is:  The return-to-scale coefficient varies across p countries. Oman has a constant-return-to-scale , (5) (i.e., doubling inputs doubles output). Kuwait and yt  bxt  i xti  ( yt1  bxt1 ) i p the UAE have a decreasing-return-to-scale (i.e., doubling output requires more than doubling inputs). Where b is a coefficients-matrix andis the vector of Saudi Arabia has an increasing-return-to-scale (it the explanatory variables. TFP is − ˆ . yt bxt could double output with less than doubling inputs). Table 1.1.1 reports our estimates for Kuwait, Oman, Graph 1.1.2 shows the new estimates. On average, all Saudi Arabia and the UAE. Hydrocarbon is a very four GCC countries have higher TFP growth than the significant factor input in all countries. However, in Conference Board estimates and TFP obtained from the UAE hydrocarbon and the stock of capital are a two-factor input model. highly collinear (   0.91) and that explains why capital is insignificant.10

10 Saudi Arabia and the UAE have a significant constant terms, which is perhaps capturing the effect of an important missing variable.

Table 1.1.1

Dynamic-OLS Estimate of Aggregate Production Function

Dependent variable ln(Yt / Lt )

1980-2015

Oman Kuwait Saudi Arabia UAE

Constant - - -12.63 4.95 (0.000) (0.0341)

0.17 0.27 0.87 0.04 ln(K / L ) t t (0.0136) (0.0001) (0.000) (0.8626)

0.03 -0.17 1.13 -0.59 ln(L ) t (0.5838) (0.0491) (0.000) (0.0236)

0.97 0.59 0.87 0.45 ln(H / L ) t t (0.000) (0.0036) (0.000) (0.0629)

0.81 0.97 0.98 0.95 R 2

 0.04 0.01 0.10 0.06

Dynamic OLS has one lag and one lead. Covariance matrix is estimated using the Newey-West method except for the UAE, which is a re-scaled OLS estimate. P value are in parentheses. Kuwait has missing data in the 1990s so its sample is 1995-2015.

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Graph 1.1.1

TFP Growth 1990 -2015 Kuwait Oman 15 8

10 4 5

0 0

-5 -4 -10

-15 -8 90 92 94 96 98 00 02 04 06 08 10 12 14 90 92 94 96 98 00 02 04 06 08 10 12 14

Saudi Arabia UAE 15 10

10 5

5 0

0 -5

-5 -10

-10 -15 90 92 94 96 98 00 02 04 06 08 10 12 14 90 92 94 96 98 00 02 04 06 08 10 12 14

Conference Board OLS - Cobb-Dougals without Hydrocarbon

14 Financial Stability Report - 2017 Macro-Financial Outlook

Graph 1.1.2 Average TFP Growth

References

BP Statistics.

Conference Board Data.

IMF, World Economic Outlook, October 2016.

Phillips, C B and M. Loretan, (1991), Estimating Long-Run Economic Equilibria, Review of economic Studies V ol. 58, No. 3, 407-436.

Solow, R. and F. Y. Wan (1976). Extraction Costs in the Theory of Exhaustible Resources, The Bell Journal of Economics, Vol. 7, Issue 2, 359-370.

Stiglitz, J. (1974). Growth with Exhaustible Natural Resources: Efficient and Optimal Growth Paths, Review of Economic Studies, 123-137.

World Bank Development Indicators.

Financial Stability Report - 2017 15 Chapter I

Box 1.2 Investment Demand in Oman

We estimate private investment demand function for in Oman is higher than the global TFP growth (proxy Oman, and also shed light on the relationship between by the U.S.), investment growth increases. We used government expenditures and private investments. the derived TFP for Oman from Box 1.1; i.e., the Private investment spending might have a crucial residuals from a Cobb-Douglas production function effect on financial stability in Oman especially when with three factor inputs, capital, labor and the flow of the debt / GDP and uncertainty are rising. hydrocarbon. The U.S. TFP data are taken from the Conference Board. However, the model predicts that In the modern theory of investments (Glick, R. and   0 if global TFP shocks are more permanent than 2 K. Rogoff, 1995) the micro-founded optimization domestic shocks. We use the differentials between model results in investment growth as a function Oman and the U.S. to conserve on the number of of the lagged level of investment. In addition to degrees-of-freedom since our sample is relatively lagged investment level, investment demand is also short. a function of “country specific” TFP shocks, which reflect the efficiency of the production process in the Table 1.2.1 reports four regressions: the estimates of country, and “global” TFP shocks that reflect global equation (1). Then we test the effect of government technical progress. expenditures on private investments. The third set of results tests the effect of government investment We test this model for Oman. We also test the effect expenditures on private investments, and finally we of transitory governments spending shocks on private test the effect of foreign direct investments. investment, and the effect of government investment expenditures on private investments.

The regression equation is:

Oman USA lnIt  0  1It1  2 (lnTFPt  lnTFPt )  et , (1)

Where I t is private investment as a percent of current GDP, and the coefficient 1  0. In theory, 1   1 and 0    1.1 Eberly, J. et al. (2012) explain that the lag-level captures the effect of real interest rate on investment, i.e., negative. That is also true because investments are very persistent, the specification of the model naturally results in a negative coefficient.2 The coefficient   0 means that when TFP growth 2

1 The IMF – WEO data measure investment as a percent of GDP, expressed as a ratio of total investment in current local currency and GDP in current local currency. Investment or gross capital forma- tion is measured by the total value of the gross fixed capital for- mation and changes in inventories and acquisitions less disposals of valuables for a unit or sector. The data are available from 1980 onwards. Private investments is total investment minus government investment expenditures taken from NCSI (compiled by the COB). These data are short, from 2000 onwards.

2 In other words, investment is a unit root process.

16 Financial Stability Report - 2017 Macro-Financial Outlook 0.0025 0.0083 0.1308 0.0191 0.0713 0.0023 P value P -1.0 0.44 0.27 2.50 0.65 0.02 0.06 2.52 -0.92 Coefficient - 0.0017 0.0029 0.1067 0.0521 0.0016 P value P - -1.1 0.48 0.26 2.50 0.06 2.53 -0.92 0.64 denotes private investments. Coefficient p - - 0.0002 0.0098 0.0291 0.0001 P value P - - 0.47 0.26 2.60 0.06 2.30 -0.83 -1.08 est estimates. The superscript est estimates. Coefficient - - - 0.000 0.000 0.0827 P value P - - - 0.38 0.29 2.60 0.06 2.08 -0.76 Coefficient t ) Y / ) p I USA t ln( ∆ TFP ln ∆ − t t ) ) 1 t − ) t Oman Y G t ) / / Y / I Y / fdi TFP G G p I ln 2 ln( ln( ln( ∆ R DW ∆ ∆ ∆ ln( ( Table 1.2.1 Table Investment Demand equation, 2001 to 2015 OLS Estimates of Oman’s Variable Dependent Constant  The standard errors and the variance-covariance are consistent Newey-W

Financial Stability Report - 2017 17 Chapter I

The first set of estimates are consistent with the relative to government current expenditures grow by estimates reported in Glick and Rogoff (1995). The one percent, private investment increases by about coefficient - lagged investment level - is negative 2/3 of one percent. No change is found in the other 1 (i.e., 0    1) as predicted by the model and is coefficient estimates. statistically significant. The magnitudes are very sensible and within the magnitudes found in this Finally foreign direct investment has a significant literature. positive small effect on private investments growth in Oman.

The coefficient 2 - the effect of TFP – is positive as predicted by the model; i.e. as the Omani Graph 1.2.1 plots the actual and the fitted values economy becomes more efficient relative to the of the full model. The fit is very good given that U.S., investments demand increases. Since our TFP investment is typically very volatile and the equation measure accounts for hydrocarbon, most of the is estimated differences. The results should be efficiency is probably oil-related. interpreted with care because our sample is rather small, and that small sample problems may bias the In the second set of the results we test the effect of estimated standard errors. That said, the signs and transitory government expenditures shocks on private magnitudes are very consistent with the predictions investments. Permanent government spending shocks of the theory so they could be viewed as a reasonable are neutral, i.e., have no real effect (Barro, 1981). guide for policy. Increasing government investment However, measurement of the permanency of these and reducing government current expenditure growth shocks is difficult because one cannot successfully rates are good for private investments in Oman. disentangle many effects operating at the same time. We use the first differenced log of government expenditures. The coefficient is -1.08, which indicates a complete crowding-out effect. The coefficients do

not change from the first regression, but 1 is slightly larger. These results are reassuring and indicate the estimates are stable from a fiscal policy standpoint, it seems sensible to reduce government expenditures growth, especially as debt / GDP level rises to allow private investments to grow.

In the third set, we test the effect of an increase in government investment expenditures relative to total government expenditures. The denominator is mainly defence and security, and civil ministries current expenditures. The estimated coefficient is quite large, 0.64 and significant at the 10 percent level only. It means as government investment expenditures

18 Financial Stability Report - 2017 Macro-Financial Outlook

Graph 1.2.1

Private Investment Function

.8 Private Investment Function .6

.4

.2

.0

-.2

-.4

-.6

-.8 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15

Actual Predicted

References

Barro, Robert J. 1981, “Output Effects of Government Purchases,” Journal of Political Economy 89, 1086-1121.

Eber ly, J., S. Robelo, and N. Vincent, 2012, “What Explains the Lagged-Investment Effect?” Journal of Monetary Economics 59, 370-380.

Glick, R. and K. Rogoff. 1995, “Global versus Country-Specific Productivity Shocks and the Current Account,” Journal of Monetary Economics 35 (February), 159-92.

Financial Stability Report - 2017 19 Chapter I

Box 1.3 The Macro-Financial default-risk stress testing approach of the Central Bank of Oman

We provide an alternative methodology to stress The SVAR is given by the k -dimension SVAR is:1

testing. We show that an economic theory-based o  pt  structural, dynamic, stochastic model, which is   y estimated as an SVAR, is a sensible approach to  t    stress testing with multivariate shocks occurring it Y   n  (1) simultaneously. ct  yt   p  The financial sector in Oman (and the GCC in  t   df  general) is dominated by the banking sector. Net  t  o credit in Dec 2015 was RO 19.4 billion (50 billion The SVAR includes the price of oil pt (for robustness, USD) or 70 per cent of nominal GDP. Almost all of we tested the real and the nominal price of oil); GDP the credit is extended to SMEs and households. Thus, n yt ; nominal interest rate it ; the credit gap ct − yt private credit is a key component of the risk profile. n ; where ct is total credit and yt is nominal GDP; the price level p is the GDP deflator, and the default Typical testing method for the effect of adverse oil t rate df .2 We replaced the money supply with the price shocks involves estimating a single-equation t credit gap because liquidity is best represented by model such as those used by other central banks, e.g., credit intermediated by the financial system in a the Bundesbank and the central bank of the Czech fixed exchange rate system. Credit is 70 per cent of Republic. The equation was originally derived from GDP and relatively more important than money and a nonlinear one-factor credit risk model, e.g., Gordy more relevant to the credit default risk issue. We do (2003). The model boils down to a single equation of not report the estimated coefficients or the impulse the aggregate default rate as a function of a number response function to save space.3 of subjectively chosen macroeconomic variable, i.e., atheoretical. The observed residuals of the SVAR ( et ) have a covariance matrix∑(ee′) . The model is given by We treat this subjectivity by adopting a small open- Ae  Bu , where u is a matrix of unobserved shock, economy model, which consists of (1) an IS curve t t t which we want to identify. This matrix has an Identity (GDP is a function of the short term interest rate, covariance matrix (uu′) = I . There are different foreign GDP, and a measure of wealth or government ∑ methods to identify the shocks, but the orthogonality spending, which depends on the price of oil). This of the shocks implies the identifying restrictions IS curve is consistent with a micro-foundation on A and B are of the form A A′ = BB′ . And since optimization model (McCallum and Nelson, 2000). ∑ the matrices on both sides of the equality sign are (2) An LM curve (real money balances are a function symmetrical, we have k(k +1) / 2 restrictions on the 2 of the short term interest rate and GDP). (3) A price 2 k unknown elements in A and B . To identify A and equation (e.g., the Calvo price equation, which we B additional 2k 2 − (k +1) / 2 identifying restrictions are used in Box 1.3, and 1.4 an Uncovered Interest Parity needed. We estimate the SVAR for the period Sep (UIP) condition consistent with the exchange rate peg in Oman, i.e., the short term interest rate in Oman is equal to the federal fund rate. The four-equation 1 Using a number of residual-based tests, we could establish model could be solved for paths for output, price that these variables share at least one common trend, hence, level, money, and the interest rate. The exchange rate cointegrated. Therefore, estimating the model in the log-levels is fixed by the Central Bank of Oman. We estimate is valid for inference and the standard statistics are applicable. A VECM could be estimated in addition, but not necessary for the model using a structural Vector Auto-Regression the current objective. (SVAR). Thus the model is structural, dynamic, and stochastic, which satisfies most of the required criteria 2 Quarterly real GDP data are unavailable so we use nominal GDP instead. For robustness, we also measured the default for modeling macroeconomic variates. rate as a logistic transform ln(df /(1 df )) , which bounds the projections of the default rate between zero and one, and deals with nonlinearities. We found that the results remain unchanged.

3 Details are available upon request.

20 Financial Stability Report - 2017 Macro-Financial Outlook

1999 to Dec 2016 with four lags.4 The most critical assumption regarding the two shocks, oil price decline and the increase in the Stress Testing Scenarios interest rate is that the unanticipated movements in We focus on simulating the effect of an adverse oil the variables - forecast errors, are caused by structural price shock and an increase in short term interest shocks. And, these shocks are exogenous. It is highly rate on the default rate. The shock scenarios include unlikely than Oman can influence the price of oil. It a moderate and a severe (hypothetical) scenarios. is a price taker. Also, its short-term interest rate is The price of Brent crude dropped from 43.57 USD highly caused by the federal fund rate because of the in December 2015 to 33.7 USD in March 2016. This exchange rate peg. So we maintain the assumption is a significant drop of 22.6 percent. Our severe stress that these shocks are exogenous. test assumption is that the price of oil drops to 33.5, We estimate the SVAR for the period Sep 1999 to 33.1 and 33 USD in Jun 2016 to Dec 2016. In the Dec 2016. We produce a baseline out-of-sample moderate scenario, t, the price of oil drops to 35 USD unconditional dynamic forecast for the default rate a barrel and stays at that price for the whole year. The for 2017. Then we re-estimate the SVAR using moderate scenario for the interest rate is an increase the above shock scenarios over the same sample by 25 basis point three times a year, and the severe separately, and produce out-of-sample projections for scenario is an increase by 25 basis point four times the default rate in 2017. The tables below report the a year. out-of-sample baseline projections of the default rate, and the shocks.

4 Lag exclusion chi-squared tests and a number of Information Criteria Akaike, sequential LR test, and Final Prediction Error tests indicate that four lags are significant.

Financial Stability Report - 2017 21 Chapter I

Table 1.3.1

Out-of-Sample Projections of the Default Rate

Oil price shocks Scenarios (%)

Baseline Moderate Severe

Mar 2017 1.3163 0.8023 0.8044

Jun 2017 1.3208 1.0946 1.1094

Sep 2017 1.3253 1.4929 1.5436

Dec 2017 1.3298 2.0612 2. 1595

Table 1.3.2

Out-of-Sample Projections of the Default Rate

Interest Rate Shock Scenarios (%)

Baseline Moderate Severe

Mar 2017 1.3163 0.8458 0.8581

Jun 2017 1.3208 1.0143 1.039

Sep 2017 1.3253 1.3136 1.3505

Dec 2017 1.3298 1.7533 1.8109

Table 1.3.3

Out-of-Sample Projections of Default Rate

Combined Oil and Interest Rate Shocks Scenarios (%)

Baseline Moderate Severe

Mar 2017 1.3163 0.807 0.819

Jun 2017 1.3208 1.117 1.1531

Sep 2017 1.3253 1.544 1.6432

Dec 2017 1.3298 2.154 2. 3485

22 Financial Stability Report - 2017 Macro-Financial Outlook

Graph 1.3.1

Actual and Forcasts of the Default Rate

.06

.05

.04

.03

.02

.01

.00 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

Actual Basline Forecasts (4 lags) Baseline Forecast (8 lags)

Financial Stability Report - 2017 23 Chapter I

Graph 1.3.2

Out-of-Sample Projection Oil Price Shocks

Graph 1.3.3

Out-of-Sample Projection Overnight Interest Rate Shocks

24 Financial Stability Report - 2017 Macro-Financial Outlook

Graph 1.3.4

Out-of-Sample Projection Combined Oil and Interest Rate Shocks

References

Gordy, M., (2003), A Risk-Factor Model Foundation for Ratings-Based Bank Capital Rules, Journal of Financial Intermediation 12, 199-232.

McCallum, B. and E. Nelson, 2000, Monetary Policy for an Open Economy: An Alternative Framework with Optimizing Agents and Stick Prices, Oxford Review of Economic Policy, 16 (4), 74-91.

Financial Stability Report - 2017 25 Chapter I

Box 1.4 Inflation in the Sultanate of Oman

Inflation is destabilizing to the financial markets. We lagged inflation is estimated to be 0.64, but the output expect prices to increase in the future because of (1) the gap is statistically insignificant. Residuals are white permanent removal of price subsidy, (2) the increase noise and serially uncorrelated. This means that in fiscal spending (and the anticipated permanent expectations are adaptive and explain less than third increase in consumption tax, VAT) according to of the variations of inflation. the fiscal theory of the price level, (3) the increase in the interest rate, which is also partly attributed The second equation fits the data much better. The to rising debt, and finally because of anticipated estimate (OLS with consistent Newey-West standard errors) of   global inflation, especially the U.S. inflation, which is 0.33 and is unity, and both are propagates via import prices. For these reasons we statistically significant. Thus the data suggest that estimated two price models for Oman. most of the firms in Oman (two-third) adjust prices competitively. Adjusted R 2 is 0.84 and the residuals The first model is the Phillips curve: are serially uncorrelated.

p pt  Et pt   ( yt  yt )  vt , (1) We also run the same regression with the real government spending. The fiscal price theory of the where pt is the log of the CPI, yt is log real GDP, and price level predicts that an increase in government the superscript ( p ) denotes potential output. The spending increases inflation. The estimated p output gap yt − yt is measured by the deviations of coefficients  and  do not change. Quarterly p log real GDP from the HP-filter trend, yt , and E is government expenditures are very volatile and highly the expectations operator. inaccurate data. The real government expenditures data are available from 2002 Q1. We smooth the data The other price equation assumes that the domestic first then deflate the data by the CPI to measure the (non-traded) market is continuously clearing through real magnitude (2002 Q1 is base-year). The growth the relative price of foreign to domestic prices (the real rate of the real government spending has a coefficient exchange rate), and that some firmsy , follow a Calvo of 0.01 and significant at the 10 percent level (p value contract price setting, i.e., imperfectly competitive is 0.1922). Although these results are encouraging, whereby firms change prices with some probability, one should interpret with care because the data while the rest(1 ) set price competitively. quality is questionable. p  (1 )(p f  q ) [E p  (1)( p f  q )]   , (2) t t t t t t t t The Calvo price equation with adaptive expectations, f where pt is the log of the CPI, pt is the log of the U.S. foreign prices and the real exchange rate fit the

CPI, qt is the log of the real exchange rate defined Omani CPI inflation rate data better than the Phillips as the RO price of one U.S. dollar, E is expected curve. This seems plausible given that the exchange inflation measured by one period lagged inflation rate is fixed and foreign prices affect domestic price (this is because the data are short from Jun 2002 to level via imports prices, which is rather sizable in the Mar 2016. Usually 6-quarter moving average would Sultanate. Also, the measurement of the output gap in be a better proxy for expected inflation). a small sample is problematic.

The Phillips curve equation (estimated by OLS with Here are the actual, fitted data, and the residuals of consistent Newey-West standard errors) fits the data the two equations. with a low adjusted R 2 (0.28); the coefficient of the

26 Financial Stability Report - 2017 Macro-Financial Outlook

Graph 1.4.1

The Phillips curve .05

.04

.03

.02 .04 .01 .03 .00 .02 -.01 .01

.00

-.01

-.02 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16

Residual Actual Fitted

Graph 1.4.2

Calvo pr ice equation

.05 .04 .03 .02 .01 .00 .010 -.01 .005

.000

-.005

-.010

-.015 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16

Residual Actual Fitted

Financial Stability Report - 2017 27 Chapter I

Box 1.5 The Government Debt

The effect of debt on the economy is controversial and ambiguous. However, rising debt affects financial stability through the effects on the peg, interest rate, credit, and inflation among other variables. Our preliminary analysis suggests that the current and projected government external debt is, so far, sustainable.

The government borrowed approximately 7.6 billion RO by the end of 2016, most of the debt is external and more borrowing is anticipated. The IMF projected an increase in Oman’s debt over the next 5 years.

Table 1.5.1

IMF Projections in Billions of RO

2017 2018 2019 2020 2021 2022

Revenues 9.265 10.324 10.959 11.184 11.376 11.654

Expenditures 12.008 12.764 13.099 13.16 13.373 13.655

Gross Debt 10.556 11.987 13.365 14.692 15.877 17.165

Graph 1.5.1

28 Financial Stability Report - 2017 Macro-Financial Outlook

Is the debt sustainable? been shown that the interest rate is the difference between the nominal interest rate and the growth rate of nominal We use the data up to the end of 2016 and projections GDP. So,1 r  (1 i) /(1 g) , where i is the nominal made by the IMF in October 2016 to answer the question. interest rate and g is the rate of growth of nominal GDP. The answer is probably yes for a number of reasons. Oman borrowed money at different interest rates for First, The IMF draft Article IV staff report (2016) different maturities and these rates will change over time. includes a section on fiscal sustainability. It says that We will assume that the average interest rate on loans Oman has consolidated its fiscal position by reducing facing Oman (i ) is three percent (0.03).1We also assume government expenditures and raising the non-oil revenues that the interest rate on loans will be unchanged over the by a cumulative total of $8.3 billion in 2015 relative to projection period, and the growth rate of nominal GDP previous year. They run a fiscal saving baseline, which changes over the projection horizon. includes the following in 2015: cutting fuel subsidy (3 The European Commission (2006) provides two per cent of non-oil GDP), containing defence spending (3 alternative sustainability indices, which we will per cent of non-oil GDP), reduction in capital spending calculate for Oman. These indices are derivatives of the by civil ministries (2 per cent of non-oil GDP), and general budget constraint. The first index is called S2 higher fees (1 per cent of non-oil GDP). In 2016, there (European Commission, 2006). This index is made-up would be a fuel subsidy reform (4 per cent of non-oil of two conditions. The first condition is called the Initial GDP), more reduction in capital spending (3 per cent of Budgetary position (IBP). If the structural primary fiscal non-oil GDP), additional reduction in defence spending balance – GDP ratio remains unchanged in the future, (3 per cent of non-oil GDP), and containment of wages the intertemporal budget constraint implies that the level and benefits (1 per cent of non-oil GDP). Further, a 1 per of debt remains stable as share of GDP (it would change cent of non-oil GDP increase in corporate income tax in by the same amount of the difference between the 2017, and a 1 per cent VAT coming in 2018. interest rate and the growth rate of GDP. In other words, These measures are expected to close the primary fiscal the fiscal balance must change to compensate for the deficit by 2020 and put government debt on a declining change in the debt either by an increase in revenues or a path according to the IMF. The adjustment proposed reduction in expenditures, or both. The second term is a above will close the gap between the non-oil primary condition about future changes in the structural primary deficit and its long run desirable level by 2021. The IMF fiscal balance (LTC). This index is similar to the budget estimated the desirable level of non-oil primary deficit constraint in eq. (1), difficult to hold because it requires using a permanent income hypothesis model, and defined very long-term projections. as the one that achieves a constant per capita fiscal The second index, S1, has three terms. The general idea spending across generations. The reforms will leave of this index is to restrict the sustainability analysis to the a room for some capital spending, assuming that these limited number of forecast yearT instead of infinity as in capital expenditures will have a positive effect on growth. S2. Here the government is asked to choose a debt-GDP The reforms will support private sector access to credit by target D* and then find out how long it will take to reach limiting crowding out and reducing risk premia, which is T the target. The first term (IBP) is similar to that in S2. It growth enhancing. Caveats: (1) The IMF analysis is based ensures that the debt-GDP level remains at the starting on assumptions, and in particular the assumption about level at some point in point in time. The second term the future price of oil up to $ 60/-, which may or may not (DR) ensures that the debt-GDP level reaches the debt hold. (2) How likely would the government collect the per cent of GDP target in yearT . This term increases in assumed taxes on consumption and corporations? value if we assume a low target for the debt-GDP ratio or Second, the general sustainability condition (sustainability if we want to reach that target in a short period. The last gap) is the intertemporal government budget constraint, term (LTC) is about the future changes of the primary where the initial debt level plus the sum of the future fiscal balance. discounted present values of government expenditures We report our calculations in table (2). To account for must be covered by the sum of future discounted present uncertainty, we have three scenarios for each of the values of total revenues. sustainability indices, S1 and S2. We report a central ∞ FB D = t , (1) scenario with the interest rate as calculated earlier, t0 ∑ t−t + 0 t=1 (1 r) scenario 1 with a high interest rate (interest rate + where D is the debt – nominal GDP ratio in a base year t0 2 standard deviations), and scenario 2 with a lower (2015). The fiscal balance FBt is the difference between, interest rate (interest rate – 2 standard deviations). For the total revenues Rt to GDP ratio and the total government expenditures to GDP ratioGt , and rt is the interest rate. Since we measure the variables as ratios to GDP, it has 1 Some loan’s interest was slightly more than 3 per cent and other were at slightly more than 4 per cen.

Financial Stability Report - 2017 29 Chapter I

comparisons, and to make the interpretation clear, we also the current policies are sustainable. Obviously, a lower report examples of two of the European’s unsustainable interest rate makes the sustainability of the debt much and sustainable fiscal balance cases, e.g., Cyprus and more significant. These sustainability gaps are sensitive Sweden. These countries were chosen arbitrarily. to assumptions. For example, whether the target level of the debt-to-GDP is high or small or if the projection’s A positive value of the indicators means that the current horizon is long or not. policies are unsustainable. A negative value means that

Table 1.5.2 Sustainability Gap Results S1 S2 Total IBP DR LTC Total IBP LTC Scenario 1 -0.86 0.32 -1.19 0.019 0.44 0.32 0.12 Central -0.86 0.29 -1.097 0.019 0.39 0.29 0.10 Oman Scenario 2 -0.85 0.25 -1.12 0.019 0.34 0.25 0.08 Cyprus 4.00 -0.30 0.00 4.300 8.50 0.20 8.30 Sweden -2.7 -3.10 -1.00 1.500 -1.1 -3.1 2.00

IBP is the initial budgetary position. DR is the debt requirement in 2021. LTC is the long-run changes in the primary balance. The debt – GDP target in S1 is assumed to be 32 per cent in 2021 as forecast by the IMF. Calculations of the European countries were based on projection horizons to 2050.

S2 is highly likely to be biased in the case of Oman and its debt to exports ratio was 400 per cent.2 Oman’s because the projection horizon is too short. While current debt is about 60 per cent of total exports. the result of the more realistic S1 index indicates Fourth, the debt – GDP ratio is projected to increase that the current debt-financed fiscal position is between 2016 and 2021. It reaches 60 per cent in 2021. sustainable. However, since the debt is external, long Although this is not a good indicator, however, its growth run sustainability assessment should pay attention rate is falling over time. This falling growth rate of debt to the real depreciation rates (the change in the real – GDP ratio is a good indicator. The new IMF forecast exchange rate), imports and exports, and net foreign (April 2017) has not changed significantly. The growth investments. rate of the debt/GDP ratio is still falling with time. For further sensitivity analysis, we increased the initial debt level to 22 and 33 percent of GDP and in both cases, and the S1 total index value remained negative. The analysis should be updated by the end of the fiscal year and as debt changes, but in general a debt / GDP ratio much less than 100 percent is still sustainable for Oman.

Third, Oman’s total exports (oil, non-oil, and re- exports) were a little more than RO 13 billion in 2015. The sum of the discounted present values of the future projected debt in table (1) is RO 68b. Assuming that future total exports from 2016 to 2021 continue to be around RO 13b a year, the sum of the discounted present values is RO 76b. Thus, future debt is also References sustainable. A stronger sustainability or solvency European Commis sion, 2006, Long-Term criterion is that the debt to GDP ratio, or the debt to Sustainability of Public Finances in the European total exports ratio should not be allowed to increase Union, European Economy, No. 4. over time. It is unclear which debt indicator (ratio) is the appropriate yardstick. The choice of an indicator Roubini, N. 2001, Debt Sustainability: How to Assess is not straightforward and depends on the country’s Whether a Country is Insolvent, Stern School of economic structure. A country could be solvent using Business, NYU. one ratio and insolvent using the other. Argentina is a classic example of debt. Its debt to GDP was 50 per cent 2 Nouriel Roubini, 2001.

30 Financial Stability Report - 2017 Macro-Financial Outlook

Box 1.6 Estimating Import Demand Function for Oman

We model import as a function of real GDP and the real GDP is deflated by the CPI (base=Mar 2001).2This Exchange rate. The stability of the real exchange rate estimator is most efficient. It assumes that the impinges on the stability of imports, which are inputs variables are integrated of order one, and cointegrated. in the domestic production of goods and services It is equivalent to a system of equation and accounts including oil and gas production. Thus, stability of for endogeneity and serial correlation. The general the currency in real terms has a significant effect on specification is: the stability of imports and potential output. Under p the current fixed exchange rate system, price stability yt     xt  i xti  ( yt1   xt1 ), (3) i p becomes paramount for imports and production of where y is log imports and x is a vector of the domestic output. explanatory variables. Thus, log imports is regressed We model the import demand function for Oman by on a constant term, log real GDP, and log real exchange assuming that imports are inputs of raw material and rate, plus their growth rates, one lag and one lead of 3 capital goods used in the domestic production of goods the growth rates, and an error correction term. The and services. In an optimizing models, the production variance-covariance matrix is consistent, estimated function is a Constant Elasticity of Substitution (CES), using the Newey-West method. where is the elasticity of substitution between labor Table 1.6.1 reports the estimated coefficients. All and imports m . l coefficients are significant. The estimated constant The CES is: elasticity of substitution, which the coefficient of  the real exchange rate is -1.7, which quite large and    , (1) implies that in the production function is about -1.5. yt    mt  (1 )lt   Thus, there is a large substitution between labor and m where t is log imports, yt is log real GDP. The imports in production and it depends on the real value   0 elasticity of substitution  1/(1 ) . As , it of the rial. A once percent real appreciation increases →1and the CES becomes a Cobb-Douglas. As    imports by 1.7 percent. The opposite is true. ,   0 and if   1,    or gets large. The cost-minimizing demand for imports is given by:1

mt  0 1 yt qt  t , (2) where qt is the log real exchange rate (i.e., the price of imports in terms of consumption goods). It is * measured by the deviations from PPP, qt = s − pt + pt

, where s is the fixed exchange rate, pt is the log of * Oman’s price level, and pt is the log of the U.S. price level. Prices adjust slowly (price stickiness), thus a real appreciation of the RO leads to more imports and more potential output.

We use Dynamic-OLS to estimate the import demand function from Mar 2001 to Dec 2016. Nominal 2 Data are from ERSD at the CBO, except for the U.S. CPI which is from Federal Reserve Bank of St Louis. The sample is restricted to 2001 because the CPI for Oman is only available from this date.

1 Bennett McCallum and Edward Nelson, 2000. 3 We restrict the lag and lead to one because the sample is small.

Financial Stability Report - 2017 31 Chapter I

Table 1.6.1 Import Demand Function

Dependent Variable: (mt) Method: Dynamic Least Squares Sample (adjusted): 2001Q3 2016Q3 Included observations: 61 after adjustments Fixed leads and lags specification (lead=1, lag=1) HAC standard errors & covariance (Bartlett kernel, Newey-West fixed bandwidth = 4.0000) Variable Coefficient Std. Error t-Statistic Prob.

yt 1.371888 0.090116 15.22355 0.0000

qt -1.699773 0.526530 -3.228254 0.0022 Constant 8.589908 0.666384 12.89032 0.0000 R-squared 0.971793 Mean dependent variable 20.04864 Adjusted R-squared 0.967454 S.D. dependent variable 0.588097 S.E. of regression 0.106096 Sum squared residuals 0.585329

ˆ Graph 1.6.1 plots the actual log import data and the long-run equilibriumaˆ + b xt using the estimated coefficients reported above. Imports are volatile. But volatility increased around the time of the global financial crisis in 2008. Import continued to be above the long-run equilibrium of the model since 2014. However, current import is slightly below long-run equilibrium.

Graph 1.6.1

21.2 Import Demand Function

20.8

20.4

20.0

19.6

19.2

18.8 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16

Log(imports) Long-Run Equilibrium

References

McCallum, B. and E. Nelson, 2000, Monetary Policy for an Open Economy: An Alternative Framework with Optimizing Agents and Stick Prices, Oxford Review of Economic Policy, 16 (4), 74-91.

32 Financial Stability Report - 2017 Chapter II FINANCIAL INSTITUTIONS

Amid prevailing macroeconomic conditions in Oman and abroad, the stability of the banking sector remained intact as the sector continued to be well capitalized, profitable, and fairly liquid with low infection ratio. Short-term risks to the banking sector further subsided as the crude oil price stabilized following an OPEC brokered deal to cut production and the liquidity conditions improved on back of successful issue of Eurobonds by the government and accomodating regulatory changes. The banks maintained high quality and adequate level of capital. The Gross and Net NPL ratios remained low and provisions are adequate, thus the credit risk remained well-contained. However, high concentration of loans to individuals and deposits from public sector may pose as a potential source of vulnerability. The interbank and retail interest rates started to rise in line with the CBO policy rates that may test the profitability and asset quality of the banking sector. Banks in Oman have low market risk and they take very limited foreign exchange and equity exposures. Stress testing results show that the banking sector is resilient to severe credit, market and liquidity shocks. The Banking sector dominates the financial landscape in Oman, however, NBFIs have scope to play a larger role in the financial sector. The prevalent imbalances in the global economy and uncertain geopolitical situation are of concern, however, we do not foresee any immediate threat to financial stability in Oman.

BANKING SECTOR IN OMAN 2.3. Despite some slowdown in the economic activities, the growth of the banking Short-term Risks to Financial Stability Further sector remained robust with strong credit Subside as Commodity Prices Stabalised offtake while infection ratio kept low. The credit 2.1. The banking sector in Oman continued portfolio of the banks remained healthy with to remain resilient amid challenging economic persistently low NPLs and adequate provisions. conditions. Although the twin deficit persisted The banks posted overall positive financial while the government is moving towards fiscal results. The solvency of the banks further consolidation, crude prices have risen from improved on back of steady earnings, right their lows of previous years and have shown shares and additional tier-1 capital injections by some stability around USD 50/ barrel since some banks. The additional capital has not only December 2016. The new oil price range is now helped banks meet the capital thresholds but better understood that has allowed better fiscal has also boosted the liquidity available to them. planning by the government. 2.4. The banking stability index and its sub- 2.2. Relatively improved crude oil prices, indices (Box 2.1) also show that on balance, the ongoing fiscal reforms, and satisfactory financial stability of the banking sector stayed intact as performance by the banking sector meant that the sector remained well capitalized, profitable, the short-term risks to the financial stability and fairly liquid with low infection ratio. Going further subside in 2016 which is evident from forward, the slower economic growth because of most of the banking stability indicators. lower hydrocarbon revenues and rising interest

Financial Stability Report - 2017 33 Chapter II rates may decelerate credit growth and put some Banks Continue to Enjoy Leading Position in pressure on asset quality and profitability of the the Financial Sector Landscape. However, the banking sector. Nevertheless, ambitious plans Growth of the Banking Sector Decelerated for economic diversification would present 2.6. The financial sector in Oman is new growth avenues to the banking sector in predominantly bank-centric. Banks not only form due course. The banks would need to reorient the largest segment of the financial sector both themselves to encash on these opportunities to in terms of size and accessibility, but also serve continue to play a pivotal role in the financial as the backbone of the payment and settlement sector of Oman. infrastructure. The total assets of the banking 2.5. The stress tests also confirm the strength sector form over 90 per cent of the total financial of the banking sector as the banks remain sector assets as of 31-Dec-2016. Within the banking sector, domestic banks account for over resilient to a battery of liquidity and solvency 90 per cent of the banking sector assets, while the stress scenarios. Even in a very severe scenario foreign banks remain marginal players in terms of whereby we increase the NPLs by over 5 times market share (Graph 2.1). of the existing NPLs, the banks on average remain solvent. More details on Stress Testing 2.7. Total Assets (net) of the banking sector of banks operating in Oman are covered in exceeded RO 29 billion (Gross Assets RO Chapter IV. 30.25 billion) at the end of 2016 thus registering a growth of 6 per cent during the year1 (Graph 2.2). This growth is lower than previous years’, however, deceleration in growth is not unexpected Graph 2.1 considering the challenging macroeconomic Assets / Structure of Financial Sector conditions faced by Oman and banks’ need to adjust to the new normals of lower oil prices and rising interest rates. Notwithstanding these short- RO Million term adjustments, the banking sector in Oman is set for solid growth over the next several years Domestic Banks, on the back of diversification of the economy Banks, 28,005 29,886 under ambitious Tanfeedh plans and a relatively Foreign Banks, low banking sector penetration. While the banks 1,881 keep the economy of Oman well-oiled, the size and scope of externalities of the banking sector Exchange Houses Finance & Leasing Insurance Banks Domestic Banks Foreign Banks warrant continued close monitoring of the sector. Lending Constitutes the Largest Component of Graph 2.2 the Banks’ Assets Growth in Banks’ Assets 2.8. With a share of about 74 per cent, lending forms the largest part of the banking sector assets. Investments form another 9 per cent of the total RO, million per cent 3,000 20 assets. Thus, the primary earning assets are about 82 2,500 15 per cent of the total asset base. Cash and balances 2,000 1,500 10 held with the Central Bank are over 9 per cent of total 1,000 assets suggesting adequate deployment of assets in 5 500 non-earning but highly liquid category (Graph 2.3). 0 0 Dec-­‐11 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15* Dec-­‐16 Growth in Assets Growth Rate (RHS) 1,* To calculate growth in 2016, the data for Dec-15 was recast to account for transfer of an external deposit from a commercial bank to CBO.

34 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

Box 2.1 Banking Stability Index

Methodology The first ranking observation (highest stability) thus receives a score of ‘0’, while the highest ranking To create composite Banking Stability Index, observation receives a score of ‘5’. The main we selected a battery of supporting indicators, advantage of means-of-order statistics is that, it is less transformed those indicators into indices and then sensitive to the distributional properties. Therefore, finally into a composite Banking Stability Index. normality assumption regarding the data series is not The indicators include Credit Growth, Private Credit required. Gap, and Private Credit/ Non-Oil GDP Ratio for ‘Credit Growth Index’; Gross NPL ratio, Net NPL Results Ratio and Coverage Ratio for ‘Asset Quality Index’; The banking stability map shows that on balance CRAR, Core Capital to Risk-Weighted Asset Ratio, the stability of the banking sector remained intact and Balance & Off-balance Sheet Items to Total despite prevailing macroeconomic conditions. Some Capital Ratio for ‘Solvency Index’; ROA and ROE indicators have slightly deteriorated, while others for ‘Profitability Index’; Prime Assets to Total Assets showed improvement during 2016. However, on and Loan to Customer Deposit Ratio for ‘Liquidity balance, the banking stability index was almost Index’; and Government Deposits to Total Deposits unchanged and the sector remained well capitalized, and Household debt to Total Credit for ‘Concentration profitable, and fairly liquid with low infection ratio. Index’. Finally, all these indices are combined into one composite Banking Stability Index using equal weights. The banking sector was able to register growth and Following Dijkman (2015), to transform the data maintain high asset quality. Nevertheless, the asset series into indices, we used ‘Means-of-Order quality indicators slightly deteriorated as the coverage Statistics’. In this technique, the data series with ratio declined from the earlier levels. ‘n’ observations are ranked from ‘1’ to ‘n’ in a way The Solvency index advanced on back of higher that higher rank corresponds to lower risk to the capital adequacy ratio that was boosted by retained financial stability. The rank of a specific observation earnings, right issues, and issuance of perpetual tier- determines the score that it receives, we calibrate the 1 eligible bonds. The banking sector maintained its scores from ‘0’ (lowest risk to stability) to ‘5’ (highest profitability and the earning indicators remained risk to stability). For a sample size ‘n’ an observation steady which helped maintain the profitability index. with rank ‘r’ gets a score of: Score=5× The Liquidity index deteriorated because of higher loans to customer deposits ratio. Nevertheless, on a positive note, liquid assets to total assets ratio Graph 2.1.1 improved during the year. While some risks are in Banking Stability Map transition, the liquidity and asset quality conditions need close monitoring because of the prevailing Banking macroeconomic conditions in Oman and abroad and Stability consolidation efforts by the government. Index 5 Reference: Concentr 4 Credit ation Growth 3 Index Index Dijkman, M., 2015, “Monitoring Financial Stability 2 in Developing and Emerging Economies”, Policy 1 Research Working Paper 7248, World Bank Group. 0 Asset Liquidity Quality Index Index

ProDitabili Solvency ty Index Index

The value of indices 31-­‐Dec-­‐15 range from ‘0’ (worst)31-­‐Dec-­‐16 to ‘5’ (best), conversely a movement away from center indicates imporvement in the index.

Financial Stability Report - 2017 35 Chapter II

2.9. Most of the increase in assets can be attributed to an increase in the lending which grew by about RO 2 billion or 10 per cent during Graph 2.3 2016. Claims on other banks also increased Uses of Funds marginally, while other components of the assets declined during the year (Graph 2.4). Despite the budget deficit and the need of the government to finance the deficit, there are no signs of crowding

30,000 RO, million out of the private sector credit as the government 25,000 used a judicious mix of funding from a variety 20,000 of sources including sizeable eurobond issues. 15,000 Resultantly, the increase in the lending was 10,000 5,000 propelled primarily by lending to the private 0 sector as domestic private and public sectors Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Credit Cash and balances respectively accounted for about 89 per cent and Investments Claims on Other Banks Other Assets 8 per cent of the growth in credit during 2016. The lending to SMEs substantially improved during the year with a healthy growth rate of over 50 per cent, albeit from a low base. Nevertheless, Graph 2.4 the scope of channeling credit to SMEs remains Flows in Asset Components (Year-on-Year in RO, million) there as despite a high growth rate, the total credit allocation to this segment was only about four per cent of the total lending portfolio of the 5,000 banking sector.

3,000 Rising Interest Rates and Prevailing Macroeconomic Conditions to Test the Banking 1,000 Sector Resilience

-­‐1,000 2.10. Until recently, the banks were operating Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 in the low interest rate environment. The low Cash and balances Claims on Other Banks Credit Investments interest rates usually create the conditions Other Assets for more risk taking by the banking sector. Therefore, a large and growing credit portfolio during prevailing macroeconomic conditions Graph 2.5 marked with rising interest rates, tax increases, Flows in Asset Components (Year-on-Year in RO, million) and spending cuts calls for the banks to remain vigilant regarding the credit, liquidity, and market risks although continued provision of credit by Graph 2.5 per cent 120 the banking sector bodes well for the economic growth2. 100 Segment wise Credit to Non-­‐oil GDP Ratio per cent 80 120 100 Private Sector Leverage Increases - However, 60 80 the Credit Growth doesn’t Reach the Excessive 40 60 Territory 20 40 20 0 0 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 2.11. The growth in private sector credit Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Household Household Business Business (private) (private) Other (private) Total Private Sector 2 Philippe Aghion & Steven Durlauf (ed.), 2005. “Handbook of Economic Growth”, Elsevier, edition 1, volume 1, number 1.

36 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS outpaced the growth in non-oil GDP during Credit Risk 2016. Resultantly, ‘Private Credit to Non-Oil Credit Growth Remained Strong. The Credit GDP’ ratio continued to rise while remaining in Risk Continues to Dominate the Risk Profile of sync with its own trend (Graph 2.5). Increase in the Banks. Slower Economic Growth and Rising credit can be used as a measure to stabilize the Interest Rates may Weaken Credit Quality short-term growth, nevertheless, higher levels of debt exacerbate the risks associated with 2.13. Amid rising interest rates and leveraging. In the case of Oman, the existing challenging macroeconomic conditions, the level of corporate and household debt (in relation credit off take in Oman remained strong. The to the GDP) is far from excessive, therefore, the lending portfolio of the banks registered a debt overhang remained highly unlikely and the growth rate of over 10 per cent during the year increasing credit-to-GDP ratio indicates a positive as the gross credit grew to RO 22.1 billion at the development. Moreover, besides household end of December 2016 (Graph 2.7). However, debt, the credit to the productive sectors of the there are some tendencies of slowdown of economy has also shown robust growth that credit growth as it remained subdued with only may help accelerate the non-oil GDP growth. 1.3 per cent increase during the last quarter of However, if such pace of expansion continues 2016. Private sector loans continued to form independent of the commensurate activities in a large part (about 90 per cent) of the lending real sector, vulnerabilities may arise. portfolio of the banking sector. 2.12. The Private Sector Credit to GDP Gap 2.14. Credit risk remained the most (Private Sector Credit to GDP Ratio minus Trend significant component of the risk profile of the of Private Sector Credit to GDP Ratio) continued banking sector as Credit Risk Weighted Assets to increase during 2016. However, this does (CRWA) continued to form over 90 percent of not signal build-up of system-wide risks as this the total risk weighted assets. The operational increase in Gap is driven largely by a sharp fall risk weighted assets have a share of about 7 in nominal GDP (due to fall in oil prices) rather per cent in the total risk weighted assets of the than excessive credit growth. This is affirmed banking sector, while market risk weighted from the Private Sector Credit to Non-oil GDP assets (MRWA) constitute about 2 per cent of gap, which increased at a much lower rate. the total risk weighted assets of the banking Therefore, any actions aimed at deleveraging or sector (Graph 2.8). The market risk remained decelerating the credit growth are not meaningful contained partly due to prudent limits imposed at this stage(Graph 2.6). by CBO on banks for taking market related risks. Although the market risk is overshadowed by the credit risk, the recent financial crisis had Graph 2.6 highlighted the importance of market risk as a Private Credit Gap lot of variation in the asset prices was related to the market risk factors3.Market risks are by 25 nature sensitive and quite volatile and hence 20 per cent their quantum should not be taken as the sole 15 reflection of their intensity. 10 5 0 Dec-­‐09 Dec-­‐11 Dec-­‐12 -­‐5 Dec-­‐05 Dec-­‐06 Dec-­‐07 Dec-­‐08 Dec-­‐10 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 3 Berg, T. (2010), “The term structure of risk premia: new evidence from the financial crisis”, European Centre Bank working paper series, No. 1165, Frankfurt. Private Credit-­‐to-­‐Non Oil GDP Gap Private Credit-­‐to-­‐GDP Gap

Financial Stability Report - 2017 37 Chapter II

Unsecured Lending Dominant with Lower Delinquency 2.15. Almost 82 per cent of the lending to Graph 2.7 corporates is without a collateral, whereas Gross Loans secured lending is only 18 per cent of the total lending portfolio of banks. Interestingly, 25,000 unsecured lending has a lower default rate as 20,000 RO, million compared to the secured lending. This indicates 15,000 that bank require collateral when ex-ante the 10,000 borrower is considered risky. Such borrowers 5,000 appear to have an ex-post higher probability of 0 default. Nevertheless, unsecured lending might Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 compromise the recovery (that is ‘higher loss Local Cy. Loans Foreign Cy. Loans Total Loans given default’), once a loan ceases to perform. Both the Domestic and Foreign Banks Contributed to the Credit Growth –Variable Rate Foreign Currency Loans may Intensify the Credit Risk Graph 2.8 Although They have Lower Historical Delinquency Risk Weighted Assets 2.16. The banking sector in Oman is dominated per cent by the domestic banks, while foreign banks account for only 6 per cent of the total banking 100 sector assets. Foreign banks are relatively a small 80 segment in Oman. Notwithstanding their size, 60 the foreign banks continued to maintain lending 40 growth4 at par with the local banks (Graph 2.9). 20

0 2.17. The share of foreign currency loans was Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 about 14 per cent of the lending portfolio as of 31- CRWA ORWA MRWA Dec- 2016. While foreign currency loans do not play an important role for the household credit, their share in business loans remained high at about 23 per cent (Graph 2.10). During the present Graph 2.9 rising interest rate environment, the foreign Growth in Credit currency denominated loans require intensified risk management as most of these loans are variable rate loans and thus may negatively affect the debt burden of the borrowers and pose a risk in 400 Index : Base 2007 350 the event of rise in interest rates or appreciation of 300 the foreign currency. On a positive note, foreign 250 200 currency loans have a lower incidence of default. 150 In terms of volume of loans, only 0.5 per cent of 100 50 foreign currency loans are delinquent as compared -­‐ to 5.9 per cent of RO denominated loans. 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Local Banks Foreign Banks

4 The kink in foreign banks’ lending growth is due to merger of OIB and HSBC, whereby the new entity was incorporated as a domestic bank.

38 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

Real Estate Exposures could be a Potential Source of Vulnerability. Higher Vacancy Rate may be a Potential Risk Graph 2.10 2.18. Banks in Oman have substantial direct and Foreign Currency Loans to Total Business Loans indirect exposure to the real estate sector. However, the real estate exposure of the banks in Oman is in line with their counterparts in other GCC countries

per cent both in terms of real estate credit to GDP and real 30 estate credit to total credit5. Direct exposures include 25 financing the residential or commercial real estate, 20 whereas indirect exposures include other financing 15 secured against real estate. The total real estate 10 exposure of the banking sector is about 33 per cent 5 of the total lending portfolio which is considered 0 large, therefore, a significant weakening in the real Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 estate market may expose the banking sector to considerable risks (Graph 2.11). Although, at present there are no significant signs of stress in the Omani real estate market, sizable exposures signify that Graph 2.11 a shift in investors’ sentiments, decline in rents or Real Estate Financing & Exposure higher vacancy rates for built-to-rent real estate may rapidly jeopardize the stability of the banking sector. High Household Indebtedness Remained High - 40 Stiffer Prudential Norms on Personal Loans would

30 Counter-balance the Risks

20 2.19. In Oman, lending to individuals surpasses all

10 other sectors. This kind of household indebtedness is characteristic of a resource dependent economy 0 Residential where hydrocarbon sector forms a large part of Dec-­‐15 Dec-­‐16 Other Real Estate Exposure Resedential the GDP and imported goods form a big share Commercial Financing to Developers of domestic consumption. However, lending to households is a sensitive territory as elevated level of household indebtedness may have implications for financial stability because of its potential to Graph 2.12 exacerbate the cyclical downturns. Therefore, Household Indebtedness to Income a close watch on this sector is warranted. Household Indebtedness in Oman is about 22 and 50 45 months of net salary for personal and housing 45 Housing loans respectively. This level of indebtedness 40 35 is considered high when compared to that in

30 OECD countries (Graph 2.12). At present, overall,

25 household credit risk indicators remain at low 20 Personal levels and household debt as a percentage of GDP 15 10 is low. Moreover, the prudential regulations on 5 lending to households are expected to keep the 0 risks in this sector at manageable levels.

AUT BEL CAN CZE DEU DNK ESP FIN FRA GRC IRL ITA JPN KOR NLD NOR OMN USA

Source: OECD Factbook 2016, and CBO Staff calculations 5 As of 31-Dec-2016, using either of the measures, Oman was third placed within the 6 Gulf Cooperation Countries.

Financial Stability Report - 2017 39 Chapter II

Low Levels of Gross and Net NPL Ratios Suggest Well-contained Credit Risk – Strained Operating Conditions Remain a Source of Vulnerability Graph 2.13 2.20. The banks have been able to grow their Trends in Non Performing Loans lending portfolio without much increase in NPLs, which augers well for the credit risk in the banking

RO Million RO Million per cent per cent sector. During 2016, the NPLs (net of reserve 350 350 RO Million per cent 3.0 3.0 350 3.0 interest) of the banking sector increased by RO 45 300 300 RO Million per cent 350 300 Kuwait 3.0 250 250 Kuwait 2.0 million, thereby the total stock of the NPLs rose to 250 300 Kuwait 2.0 200 200 2.0 200 250 Kuwait RO 392 million or 1.78 per cent (2015: 1.73 per 150 150 Qatar Qatar 2.0 150 200 Qatar 1.0 1.0 100 100 1.0 cent) of the gross loans. The net NPLs also increased 100 150 Qatar 50 50 100 50 1.0 by RO 30 million during the year, while the net 0 0 0.0 0.0 50 0 0.0 Dec-­‐12 Dec-­‐12 Dec-­‐13 Dec-­‐13 Dec-­‐14 Dec-­‐14 Dec-­‐15 Dec-­‐15 Dec-­‐16 Dec-­‐16 NPL ratio remained at 0.5 per cent (Graph 2.13). 0 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 0.0 *NPLs *NPLs Net Net NPLs NPLs Despite slight increase, the NPL ratios remained *NPLs Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Net NPLs Dec-­‐16 *NPLs to Loans(RHS) Net NPLs to Net Loans(RHS) *NPLs *NPLs to Loans(RHS) Net Net NPLs NPLs to Net Loans(RHS) in line with their past trend and close to that of *Net *Net of *NPLs reserve of to reserve interst Loans(RHS) interst Net NPLs to Net Loans(RHS) *Net of reserve interst *NPLs to Loans(RHS) Net NPLs to Net Loans(RHS) some other countries in the region. The low NPL *Net of reserve interst ratios suggest satisfactory asset quality and well contained credit risk. Moreover, the existing loan portfolio of banks is well covered against expected Graph 2.14 losses through adequate provisions with coverage Provisions against NPLs ratio (provisions to NPLs) of 70 per cent (148 per cent including general provisions) which compares favourably with regional cohorts (Graph 2.14). RO Million RO Million per cent per cent 350 350 3.0 3.0 300 RO. million Qatar per cent 80 300 300 2.21. As the fiscal surpluses of the past years Kuwait 250 250 250 Kuwait 2.0 60 2.0 have turned into deficits and economic growth has 200 200 200 150 150 Qatar Qatar decelerated, the favorable operating conditions that 150 40 1.0 100 100 1.0 helped business sector have shown some signs of 100 50 50 20 50 0 0 0.0 0.0 weakening. Nevertheless, the profitability of the 0 Dec-­‐12 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐15 Dec-­‐16 Dec-­‐16 0 listed companies improved during 2016. While at *NPLs Dec-­‐12 *NPLs Dec-­‐13 Dec-­‐14 Net Dec-­‐15 NPLs Net Dec-­‐16 NPLs Speci5ic Provisions Provisions to NPLs (RHS) present the businesses have posted overall positive *NPLs to *NPLs Loans(RHS) to Loans(RHS) Net NPLs Net to NPLs Net to Loans(RHS) Net Loans(RHS) *Net Source: of *Net reserve RespectiveNet of NPLs interst reserve Central to interst capital Banks’ (RHS) websites and CBO staff results and their indebtedness is far from excessive, calculations a hike in the interest rates and weaker demand may increase the vulnerabilities in the corporate sector. Going forward the tough operating environment including rising costs on account of reduction in Graph 2.15 subsidies, higher taxes and rising interest rates might New NPLs and Recoveries test the repayment capacity of some borrowers.

60 20 Recoveries and Low Accretion Kept the NPLs RO Million RO Million per cent per cent 350 350 3.0 3.0 Stock Low RO, Million per cent 300 300 15 40 Kuwait 250 250 Kuwait 2.0 10 2.0 2.22. During 2016, banks were able to recover 200 200 20 150 150 Qatar Qatar 2.8 per cent (or RO 9.7 million) against non- 5 1.0 100 100 1.0 performing loans. Moreover, banks managed to 0 50 50 0 0 0.0 recover an additional RO 75 million from other 0 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 0.0 Dec-­‐12 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐15 Dec-­‐16 Dec-­‐16 delinquent loans (special mention category). The *NPLs Cash Recovery *NPLs New NPLs Net Recovery NPLs Net / NPLs NPLs (RHS) cash recoveries have reduced during the past two *NPLs to *NPLs Loans(RHS) to Loans(RHS) Net NPLs Net to NPLs Net to Loans(RHS) Net Loans(RHS) *Net of *Net reserve of interst reserve interst years. However, as a welcome development the accretion to the NPLs has also considerably came down during 2015 and 2016 (Graph 2.15). A note on policy measures adopted elsewhere to combat the menace of NPLs is given in Box 2.2.

40 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

Box 2.2 Combating Non-Performing Loans

Omani banking sector has low incidence of Non- be done by accumulating capital buffers during good Performing Loans (NPLs). At present, the NPL ratio times and having dynamic provisioning to create of the banking sector is 1.78 per cent (Graph 2.2.1). reserves. During downturns, when there is a risk of Therefore, currently NPLs are not a cause of serious increase in NPLs and slowdown of credit growth, concern. However, during economic downturns these reserves and capital buffers can absorb the NPLs may rapidly increase. High level of NPLs are shocks. Presence of these buffers also enable central detrimental not only to the financial stability but banks to take counter-cyclical measures by releasing also to the economic growth because credit growth buffers during economic slowdown. slows down in a banking system that is plagued with high level of NPLs (IMF (2015)). Therefore, the Right Incentives for the Banks importance of having in place policies, procedures, Policies aimed at addressing the NPLs should involve and infrastructure to arrest rising NPLs or to deal strategies that (i) minimize the incentives to defer with NPLs if they eventually increase cannot be interest and repayment commitments, (ii) encourage overemphasized. early recognition of NPLs, provisions and write-offs, and (iii) promote more prudent valuation of collateral. Graph 2.2.1 Gross NPLs to Gross Loans Market for NPLs: Cleaning the banks’ balance sheets becomes imperative when NPLs reach a level where they negatively affect credit supply. One private sector solution for cleaning banks’ balance sheets while unlocking some liquidity is through a market for NPLs where banks may sell their toxic assets to a third party that is specialized in reviving sick businesses and / or collecting bad debts. Banks can sell their NPLs at lower discounts if an efficient market for NPLs exists. Other than information asymmetry, the factors that affect the efficiency or even presence of such a market include legal system for enforcement of creditors’ rights, cost of enforcement of contracts, and length of bankruptcy court proceedings.

Debt Resolution Measures:

Several debt resolution measures may help in combatting high level of NPLs. These measures include modernizing the bankruptcy frameworks, facilitating out-of-court foreclosures and Unlike Oman, some countries especially those in the restructuring, judicial capacity building, developing Euro area are battling the presence of persistently of a database of real estate collateral valuations, and high NPLs (Graph 2.2.1). This note takes a stock of capacity building for bankruptcy administrators and the measures that can be taken to address the menace judges. of high NPLs. Although the exact remedies may vary Adoption of Best Practices for Multi-creditor according to the particular circumstances faced by a Workout: country, important lessons can be learned from what worked or may work in other jurisdictions. International Association of Restructuring, Insolvency & Bankruptcy Professionals (INSOL) offers Increasing Banks’ Capacity to Deal with NPLs: guidelines for multi-creditor workouts. Adoption Central banks may take several measures to increase of the INSOL principles, which are considered the capacity of the banks to handle NPLs. This can as international best practices, may help revival

Financial Stability Report - 2017 41 Chapter II

of sick units through successful implementation References: of restructuring process. The principles advocate avoiding any knee-jerk reaction that may adversely Bridge, C., 2016, Analysis of International Out-Of- affect the borrower or interests of other creditors and Court Corporate Restructuring and Recommendations cooperation by all creditors in taking an informed for Implementation in Hungary, European Bank for decision and collective action to solve the financial Reconstruction and Development. difficulties of the borrower to recover their credit. Financial Stability Report, 2016, De Nederlandsche Bank. Increasing the capacity of the banks to absorb the International Monetary Fund (IMF), 2015, Policy Options shock of NPLs, right incentives for the banks to for Tackling Non-Performing Loans in the Euro Area, in address the NPLs, efficient resolution framework, Euro Area Policies —Selected Issues, IMF Country Report and adoption of international best practices are some No. 105/15 (Washington). of the measures that may address the problem of NPL Resolution Strategy, Official Gazette of Republic of compromised asset quality and allow banks to provide Serbia. fresh funds to the economy to facilitate growth. Zoller, C. B., 2017, Reducing the Burden of Non-Performing Loans with the Help of the Vienna Initiative, Laws in Transition Journal, European Bank for Reconstruction and Development.

42 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

Growing Volume of Special Mention Loans, however, Remained a Cause of Concern 2.23. The restructured loans in the banking Graph 2.16 Restructured Loans sector declined by RO 21 million during 2016 (Graph 2.16). However, the loans in the Special Mention category increased by 23 per RO, million per cent cent. During 2016, the special mention loans 400 1.5 increased by RO 240 million as compared to the 300 1.0 increase of RO 62 million during 2015 (Graph 200 2.17). The accumulative increase in special 0.5 100 mention loans over the past four years is close

0 0.0 to RO 800 million. Notwithstanding the current Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Non-­‐performing Restructured Loans low levels of NPLs and strong capital buffers Performing Restructured Loans Performing Rest. / Gross Loans (RHS) of the banks, the surge in special mention loans implies that asset quality indicators are at the risk of deterioration as adverse business conditions may push these fragile loans down Graph 2.17 to the NPL category. Therefore, due attention is Special Mention to Gross Loan Ratio warranted to arrest this trend and to check their slippage to NPLs. Although the stock of special mention loans is sizeable, their quantum (5.8 per cent of gross loans) is not large enough to RO, million per cent 1500 6 threaten the solvency or stability of the banking

1000 4 sector.

500 2 Bulk of the NPLs Continued to be in Loss category 0 0 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 2.24. About three-quarters of the NPLs of the Special Mentioned Loans SM Loans to Gross Loans (RHS) banking sector continued to be classified in the Loss category. During 2016, the NPLs in this category increased by RO 11 million (Graph 2.18). The continued rise in this category Graph 2.18 implies that banks need to shore up their efforts Category-wise Breakup of NPLs to take corrective actions aimed at reviving the NPLs and preventing their down-gradation following the initial classification of a loan to Dec-­‐16 the less severe categories of delinquency. With Dec-­‐15 the current low level of NPLs, this situation Dec-­‐14 does not look critical. However, in the event of Dec-­‐13 an economic downturn leading to possible hike

Dec-­‐12 in the level of NPLs, the task of taking prompt

0% 25% 50% 75% 100% corrective actions by the banks would appear Sub-­‐standard Doubtful Loss arduous. Given that bulk of these infected loans carry slim prospects of recovery, banks need to make concerted efforts for a turnaround in this trend.

Financial Stability Report - 2017 43 Chapter II

Market Risk Policy and Interbank Interest Rates Increased in Line with the US Monetary Policy. Rising Market Risk Continued to Remain Interest Rates might Put Pressure on the Overshadowed by the Credit Risk - Rising Borrowers as well as Banks’ Bottom Lines Interest Rates Entail New Risks 2.26. Following the Federal Reserve’s lead, 2.25. The recent financial crisis highlighted the policy rates and interbank rates in Oman the importance of market risk as a lot of variation have started to increase. During the fourth in the asset prices was related to the market risk quarter of 2016, the repo rates inched up to factors6. The continued uncertainty caused by 1.19 per cent. Due to the domestic liquidity concerns over the governments’ fiscal position, conditions and increase in the policy rates, the mounting public debt and economic growth overnight rates increased to 0.47 per cent at the prospects seem to have affected the market end of 2016 as compared to 0.19 per cent at the sentiments as well. However, the contribution end of 2015 (Graph 2.19). The rising policy of market risk remains trivial in the overall risk rates have also been passed through to the profile of banks when measured in terms of retail deposit and lending rates. The average current practices of calculating risk-weighted interest rates on private RO deposits increased assets7. Nevertheless, other than the stand alone to 1.16 per cent during Q4-2016 up from 0.64 considerations, the market and credit risks may per cent a year ago. Similarly, average lending interact to reinforce each other and may result rates on RO loans also increased to 5.08 per in substantial losses if not managed jointly8 cent during Q4-2016 as compared to 4.76 per (Graph 2.8). cent during Q4-2015. As Oman maintains a fixed exchange rate with the US$, any further increase in the interest rates by the Federal Graph 2.19 Reserve would push up the interest rates in Policy and Overnight Interbank Rates Oman. 2.27. The rising interest rates might put 7.0 6.0 pressure on the bottom lines of the banks. 5.0 However, the stress testing exercise shows 4.0 3.0 that the interest rate risk in banks is within 2.0 reasonable bounds if they face a 200 basis 1.0 point adverse movement in interest rates 0.0 (please refer to Chapter IV for more details on Dec-­‐06 Dec-­‐07 Dec-­‐08 Dec-­‐09 Dec-­‐10 Dec-­‐11 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Overnight Interest Rates Repo Rate stress testing of the banking sector). Effective Fed Fund Rate MSM Closes on a Positive Note – Banks Exercise Caution while Taking Market Exposures 6 Berg, T. (2010), “The term structure of risk premia: new 2.28. The MSM 30 index gained 6.96 per evidence from the financial crisis”, European Centre Bank working paper series, No. 1165, Frankfurt. cent during 2016 and closed the year as the 7 Throughout this section, risk weighted assets (RWA) second best performing stock market within are limited to RWA under Pillar-1 of Basel II capital the region (Graph 2.20). The relatively better accord, that is, interest rate risk in banking book is performance of the stock market reflects explicitly excluded from the analysis. recovery in oil prices, improved and optimistic 8 BCBS(2009), “ Findings on the interaction of market sentiments of the market regarding economic and credit risk”, BIS WP. 16.

44 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS conditions and confidence in the government Limited Exposure of Banks while Restricting to induce a turnaround with measured them from Benefiting from Stock Market Gains consolidation and focused development and may also have Insulated them from Adverse diversification plans. The proven ability of Effect During Downturns government to raise external funds at attractive 2.29. Banks continue with their strategy to terms further reassured the market besides hold small equity investment portfolios. The adding much needed liquidity to the market. banks’ investment in listed shares was RO 127 The continued uncertainty in the stock market million as of 31-Dec-2016 which is less than underscores the significance of caution while 0.5 per cent of their total risk weighted assets taking stock market exposures. or less than three per cent of their regulatory capital (Graph 2.21). Consequently, despite the better performance of the Index, banks did not gain much from it. On the brighter side, the calculated stock market exposure also ensured that the banks’ losses remain limited during Graph 2.20 downswings in the previous years. Banks MSM Index and Returns should, however, remain cautious about their indirect exposure to the stock market in the form of lending for the purchase of or against listed securities. Moreover, weak stock market performance is indicative of tougher operating conditions for the business which may also affect the quality of banks’ credit portfolio. Limited Exposure in Non-pegged Currencies Keeps the Foreign Exchange Risk under Control 2.30. Foreign exchange exposure of up to 40 per cent of Tier I capital is considered acceptable9. In comparison to that, the banks Graph 2.21 in Oman have been historically maintaining Stock Market Exposure of Banking Sector (RO Million) foreign exchange exposures of less than 25 per cent of their Tier-1 capital (Graph 2.22). Foreign exchange exposure of the banking sector decreased during 2016 with narrowing 30000 25000 of the gap between foreign currency assets 20000 and liabilities (Graph 2.23). The low and 15000 declining foreign exchange exposure reflects 10000 the continued faith of market participants in the 5000 currency peg. 0 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Listed Shares Total Capital RWA

9 CBO regulations also allow foreign exchange exposures of up to 40 per cent of Tier I capital.

Financial Stability Report - 2017 45 Chapter II

Liquidity Risk Banks Remained Fairly Liquid, without any Signs of Serious Strain – Liquidity Conditions Graph 2.22 that Eased after Regulatory Changes are Forex Exposure to Tier-1 Capital Expected to Further Improve Following per cent External Debt Raised by the Government 2.31. Amid a growing loan portfolio, the banks on average comfortably maintained the cash reserve requirements without any significant signs of strains. The excess cash reserves, over and above the required reserves, maintained by banks averaged about RO 500 million10 during All Currencies 2016 (Graph 2.24). The liquidity conditions in Oman tightened because of the budgetary needs of the government and decreased inflows due to depressed oil prices. However, the regulatory change to allow banks to use a portion of Graph 2.23 their investments in permissible government Foreign Currency Assets & Liabilities securities to satisfy cash reserve requirements and other sources of external funding kept 8,000 sufficient liquidity in the domestic market. 6,000 During 2016, Oman raised RO 2.5 billion 4,000 through a Eurobond issue. In 2017, Oman again 2,000 tapped the international markets through a multi- tranche $5 billion Eurobonds issue followed 0 Dec-12 Dec-13 Dec-14 Dec-15 Dec-16 by a $ 2 billion international Sukuk issue. All FCY Assets FCY Liabilities international bond issues of Oman witnessed strong investor interest that manifested in the form of heavy oversubscription. As a result, despite rating downgrade by one credit rating agency, Oman successfully raised the required

Graph 2.24 funds at competitive rates. The Eurobond issues Cash Reserve Maintenance made up for the lost inflows from oil revenues and subsided the liquidity concerns. 2.32. In anticipation of the future needs, banks

RO, million 2,000 across the GCC countries including some Omani banks have been tapping the overseas capital 1,500 markets. This combined with improvement 1,000 in oil prices and expected slowdown in credit 500 offtake will contribute to further ease up the 0 funding conditions in the market. Dec-­‐14 Jun-­‐15 Dec-­‐15 Jun-­‐16 Dec-­‐16 Excess Reserves Avg. Res. Req. Avg. Res. Maint.

10 It may be noted that these cash reserves are in addition to the banks’ investments in Government Development Bonds and Sukuks.

46 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

2.33. The stress test results also indicate a fair level of resilience of the Omani banking sector to varying degrees of liquidity shocks. Under Graph 2.25 stressed scenario, different banks can sustain the Gap to Asset Ratio (in per cent) outflows of deposits from 3 to 30 days11. Positive Gaps Bode Well for Liquidity - Repricing Risk Prevails Considering Rising Interest Rates 9m to 12m

6m to 9m 2.34. Tenor wise maturity gaps suggested some shifts due to the changing liquidity conditions 3m to 6m in the banking sector. The ‘Gap (Assets – 1m to 3m Liabilities) to Asset’ ratio for all tenors remained upto 1m positive during the year (Graph 2.25). This is a

-­‐5 0 5 10 15 20 positive development from short term liquidity Dec-­‐16 Dec-­‐15 management point of view. This trend may expose the banks to reinvestment risk and may affect their future earnings potential. However, given the current rising interest rate environment, Graph 2.26 reinvestment risk also remains largely muted. Lending Ratio and Credit to Deposit Ratio The Credit Growth Outpaced the Deposit Growth. However, Credit to Deposit Ratio Stayed Close to the Regional Cohort and its Past Trend, while the Lending Ratio Remained within Prescribed Limits 2.35. During 2016, the net lending increased by about 10 per cent, whereas the deposits grew by only 5 per cent. Consequently, the credit- Source: Respective Central Banks’ websites and CBO staff calculations to-deposit ratio increased to 108 per cent. The increase in credit-to-deposit ratio is suggestive of some tightening in the liquidity conditions that prompted the banks to tap international capital Graph 2.27 markets. The current credit to deposit ratio of the Sources of Funds banks is, however, close to their counterparts in other GCC countries (Graph 2.26). The current 30,000 level of credit-to-deposit ratio is not considered RO, million high as banks in Oman traditionally rely on 20,000 more stable sources of funding that is deposits

10,000 and capital, while wholesale funding remained limited at 7 per cent of total funding base (Graph 0 2.27). Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Deposits Due to other Banks Other Liabili>es Capital 2.36. It may be noted that the credit-to-deposit ratio ignores capital that is an important source

11 Details of shocks and their impact on banks’ liquidity may be seen in Chapter IV of this report.

Financial Stability Report - 2017 47 Chapter II of funding. The lending ratio (loans excluding 2.37. Higher oil prices since the OPEC deal Government soft loans to eligible deposits to cut production and lower expected credit plus capital) of the banking sector was about growth are further expected to stabilize the 79.5 per cent at the end of December 2016 funding conditions for the banking sector. which is lower than the ceiling of 87.5 per cent Although the Wholesale Funding is Small, the prescribed by CBO. This implies that banks Persistent Funding Gap Contributes to the still have a cushion to increase lending against Vulnerability their existing funding base. 2.38. Banks in Oman have traditionally low reliance on wholesale markets. Government deposits, however, remained an important source of funding for the banks. Due to continued reliance on public sector deposits and higher credit growth as compared to deposit growth, the customer funding gap - the gap between customer12 loans and deposits – Graph 2.28 increased to about RO 8.2 billion. Funding gap Customer Funding Gap as a percentage of loans comes out to be over 43 per cent. This high funding gap is suggestive of the banks’ vulnerability emanating from their

RO, million per cent lopsided funding structure (Graph 2.28). 10,000 100.00 8,000 80.00 Sizeable Public Sector Deposits Expose the Thousands Thousands 6,000 60.00 Banks to the Concentration Risk – However, 4,000 40.00 in Stress Testing Exercise, Banks Remained 2,000 20.00 Resilient to Deposit Runoff 0 -­‐ Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Funding Gap Lending Ratio(RHS) 2.39. The deposit structure of the banking Gap to Customer Loans(RHS) sector in Oman follows a peculiar pattern, with Government and Public Sector Enterprises (PSEs) contributing jointly about one-third share in the total deposits (Graph 2.29). The Graph 2.29 high level of public sector deposits combined Breakup of Bank Deposits with the reduced cashflows of the government in the wake of dwindling oil revenues could pose a covert yet potent risk of significant RO, million 21,000 1.4 1.2 withdrawal of deposits form the banking sector. 1.5 1.9 However, the risk of withdrawal is not imminent 14,000 65.1 64.9 as the government resorted to borrowing from 63.2 64.7 international markets to finance its budget 7,000 4.9 6.0 5.1 5.8 deficit. Although, on average the liquid assets 28.9 28.7 27.7 29.0 0 (excluding interbank assets) of banking sector Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 almost cover the deposits made by Government Govt. PSE Pvt. Non Res. Liq. Assets and PSEs, certain individual banks exhibit

12 Excluding Government, Public Sector Enterprises and Financial Institutions.

48 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS varying degree of resilience to the deposit Competition, Concentration and Intercon- withdrawal by the government, implying that nectedness such a withdrawal could put the banking sector Banking Sector Concentration Remained under liquidity stress. It may be noted that Moderately High – D-SIBs Framework and about one-third of the banking sector deposits Bank Resolution Framework Help Deal with are Demand Deposits which are theoretically the Systemically Important Banks more susceptible to withdrawal during stressed times (Graph 2.30). 2.41. The degree of concentration in the Omani banking sector, as measured by 2.40. The latest stress tests showed that Herfindahl-Hirschman Index (HHI), reflects the banks operating in Oman remained fairly that concentration in banking sector in Oman resilient to the assumed deposit runoffs. is moderately high13,14, but in line with the peer group of GCC countries. The concentration is, however, much higher than that in advanced economies, for example in the European Union Graph 2.30 (Graph 2.31). Structure of Deposits 2.42. When the concentration is measured as share of assets of the top few largest banks in the 10,000 total banking sector assets, a similar pattern is 8,000 revealed. The top five (three) banks account for 6,000 about 78 per cent (61 per cent) of total banking 4,000 sector assets (Graph 2.32). Due to the relatively 2,000 smaller market size, higher concentration 0 Demand Saving Time Others levels in banking sector is not surprising. In Private Govt. & PSE NBFIs Others Oman the concentration is in sounder and stronger institutions, however, concentration has its demerits as it is counterproductive for efficiency and innovation, and increases the systemic risk from the failure of a big institution.

Graph 2.31 In order to deal with the risks emanating from HHI of the Banking Sector the presence of large institutions, the CBO had issued guidelines to identify, supervise and regulate Domestic Systemically Important

0.220 Banks. Moreover, as a part of the preparedness

0.200 to amicably resolve the systemically important

0.180 banks, CBO has drafted a Resolution Framework

0.160 that is in the advanced stages of finalization.

0.140

0.120

0.100 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 13 As HHI is computed as sum of squared market shares of all banks, we use total assets of banks to calculate HHI. US Department of Justice and Federal Trade Commission classify HHI values between 0.15 and 0.25 as moderately concentrated markets. 14 Slight decrease in HHI is partly on account of transfer of an external deposit from a commercial bank to CBO.

Financial Stability Report - 2017 49 Chapter II

Sectoral Credit Concentrations Require Heightened Supervision and Prudent Monitoring of Key Portfolios –Default by Top Graph 2.32 Five Borrowers may Wipe out Half of Banking Banking Sector Concenteration - by Total Assets Sectors’ Capital 2.43. Sectoral distribution of credit, particularly in the personal loan segment, highlights credit risk concentration in banking sector. Such concentrations may lead to risks that are systemic in nature (Graph 2.33). Given the structure of the Omani economy, this type of credit concentration is unavoidable. However, the high quantum of the banks’ exposure to the household segment, having potential of volatile performance, could be a source of concern as it might spell a situation of debt overhang15. Presently, however, this segment has been Graph 2.33 performing well with slightly lower than Concentration of loans and NPLs(share in percent) average NPL ratio. 2.44. The construction and manufacturing sectors have proportionally very high incidence of NPLs thus posing as a source of vulnerability for the banking sector. The construction sector is cyclical in nature. Although the government has earmarked sizeable budget for development projects, it is likely that non-critical projects may be shelved in favour of projects aimed at diversification, which may put strain on the construction sector. Considering that the construction sector is the second largest user of the bank credit, extra caution is warranted from Graph 2.34 the banks while taking exposure to this large Credit Concentration but volatile sector. 2.45. The lending to the top five borrowing groups constitutes about 10 per cent of the per cent 12 lending portfolio of the banking sector. This 10 implies that a default by these five borrowers 8 6 (from over 300,000 borrowers) may erode 4 about one-half of the capital of the banking 2 sector (Graph 2.34). 0 Group-­‐1 Group-­‐2 Group-­‐3 Group-­‐4 Group-­‐5 Top 5 Total Dec-­‐15 Dec-­‐16 15 To avoid debt-overhang like situations, CBO has set prudent limits on consumer financing linking the aggregate loan limits to the repayment capacity (income) of borrowers.

50 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

Solvency and Profitability 2.47. The regulatory capital of the banks increased by about RO 300 million or 7 per Solvency Position Remains Robust with Low cent during 2016. The capital strengthened Leverage and High Quality Tier-1 Capital because of satisfactory earnings, right issues, 2.46. The banks remained adequately and issuance of perpetual tier 1 capital bonds. capitalized with the benchmark Capital to The leverage ratio (Capital to On and Off- Risk Weighted Assets Ratio (CRAR) of the balance sheet exposure) of the banking sector banking sector increasing to 16.8 per cent remained over 9 per cent as against the Basel at the end of 2016 from 16.5 a year ago. The Committee’s requirement of minimum three per CRAR thus exceeds both the Basel norms and cent depicting satisfactory solvency position of CBO requirements of 12.625 per cent of risk banks. weighted assets. At system level, even the Tier- 2.48. All banks operating in Oman were able 1 capital was sufficient to meet the regulatory to meet the CBO requirements of 12.625 per requirements (Graph 2.35). Importantly, banks cent of CRAR. Moreover, 14 banks had CRAR in Oman possess high quality of Tier-1 capital of 14 per cent or over (Graph 2.36). comprising almost entirely of Common Equity Tier -1 capital. 2.49. Capital adequacy ratios do not fully account for low level of diversification of credit portfolios, high degree of interest rate risk in the banking books and imbalances in the real Graph 2.35 sector (for example, formation of asset price bubbles) that may adversely affect the credit

Solvency Pro�ile of Banks portfolio of the banks. Thus, these ratios may overestimate the resilience of the banking Capital, RO million per cent 5,000 19 sector. To partially offset the drawbacks of 17 4,000 the capital ratios, we supplement our analysis 15 3,000 13 with stress testing exercise. The stress testing 2,000 11 exercise shows that the banking system stands 9 1,000 7 quite solvent with adequate level of capital 0 5 and thus remains resilient to various stressed Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 scenarios. Even when severe credit and market Core Capital Tier-­‐II Capital CRAR(RHS) shocks are applied, the banks remain solvent with a comfortable level of system-wide CRAR of higher than the regulatory requirements.

Graph 2.36 Banks Maintained Profitability Despite Rising Frequency Distribution of CAR Funding Costs and Declining NIM 2.50. Strong profitability can reinforce banks’ buffers over time and enhance their 10 ability to support growth. Despite challenging 8 macroeconomic conditions, stringent prudential 6 norms for credit, rising funding costs, and 4 declining Net Interest Margin (NIM), the banks 2 maintained their profitability. The increase 0 in earning assets and thus higher interest and [0,12] [12,14] [14-­‐16] [16-­‐18] [18,20] [>20] Dec-­‐15 Dec-­‐16 investment income offset the higher funding and

Financial Stability Report - 2017 51 Chapter II provisioning costs. Resultantly, during 2016, 2.51. Interest income remained dominant the banks netted over RO 438 million in pre-tax (79 per cent) in the total revenues of the banks, profits (2015: RO 439 million). The profitability whereas non-interest sources contributed only 21 ratios, ROA and ROE, remained steady at 1.5 per cent to the revenues of the banks. Moreover, per cent and 10.5 per cent, respectively despite within the interest income, interest earned on a marginal decrease in NIM from 2.83 per cent loans formed the lion’s share with about 90 per during 2015 to 2.76 per cent in 2016 (Graph cent contribution. This skewed position reflects banks’ inability to diversify sources of income and 2.37)16. calls for concerted efforts by the banks to try to diversify the sources of income within the present bounds, limits, and prudential norms. 2.52. Major portion of banks’ non-interest expenses stem from staff and administration costs Graph 2.37 with a share of 57 per cent in the total non-interest Earnings Indicators (per cent) expenses. This suggests that there is a scope of improving operational efficiency by arresting the staff and administrative costs (Graph 2.38).

ROE 15.00 ROA 5.0 NIM Islamic Banking 12.00 4.0 Islamic Banking Showed Strong Growth 9.00 3.0 Tendencies with Total Assets Surpassing Foreign 6.00 2.0 Banks Assets 3.00 1.0 -­‐ 0.0 2.53. Islamic banking in Oman has achieved Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 remarkable growth since its inception about four ROE ROA (RHS) NIM (RHS) years ago. At the end of December 2016, the Islamic banking assets formed 10.3 per cent of the total banking sector assets. With an annual growth of 37 per cent, total assets held by Islamic banks Graph 2.38 and the Islamic banking windows of conventional Composition of Non-Interest Expenses banks at the end of December 2016 exceeded RO 3 billion, while the total assets of foreign banks were RO 1.9 billion at the end of December 2016. RO Million With 11 per cent share in total financing/ credit 600 500 of the banking sector, the financing by Islamic 400 banking institutions was RO 2.4 billion, while 300 their deposits were RO 2.2 billion as of 31st 200 December 2016 (Graph 2.39). 100 0 2.54. Share of Islamic banks in the total Islamic Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 banking assets increased slightly during 2016. Provisions Staff & Admin. Other With a share of 70 per cent (2015: 72 per cent) in total Islamic banking assets, Islamic windows of conventional banks continued to dominate the Islamic banking sector. The initial teething phase of the full-fledged Islamic banks appears to have passed and they are expected to play a bigger role in the sector in future. The higher growth of 16 Throughout this section, profitability ratios are IBIs raises questions about the business structure calculated using pretax figures and include Islamic banking data. of the Islamic banks and how does it is different

52 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS from that of conventional banks. An empirical NON-BANKING FINANCIAL assessment of this issue may be seen in Box 2.3. INSTITUTIONS 2.55. Islamic banking institutions (IBIs) NBFIs Continue to Provide Vital Financial recorded remarkable improvement in profitability. Services – FLCs and Insurance Dominate the The aggregate pre-tax profits of IBIs during 2016 Sector increased to RO 13.6 million from RO 1.6 million in 2015. Five out of six Islamic banking windows 2.57. Non-Bank Financial Institutions posted pre-tax profits during 2016, while all (NBFIs) play an important role in the financial windows were profitable during the last quarter of sector by providing supplemental financial 2016. One of the two full-fledged Islamic banks services like financing various niche markets, turned profitable during 2016, while the other provision of insurance, asset management managed to further cut its losses. services, remittances, and currency exchange 2.56. The sector is expected to improve its services. A feature that distinguishes NBFIs bottom-line while continuing to gain market share. from banks / depository institutions is that Due to fast paced growth, the Islamic banking the former do not accept (retail) deposits sector as a whole is gaining systemic importance, while they mobilize contractual savings and however, it still does not pose a systemic risk at provide financing. Presence of NBFIs may help the moment. improve the efficiency and reach of the financial sector as they complement and compete with commercial banks17. Deep and broad financial Graph 2.39 markets made available with the presence of Islamic Banking Indiators NBFIs along with commercial banks offer synergies that foster economic growth18. 2.58. In terms of asset size, the Finance & Leasing Companies (FLCs) and Insurance companies remained the leading players in the NBFIs sector accounting for over 51 per cent and 44 per cent of the total NBFIs assets, respectively. 2.59. The FLCs recorded a growth of 4.8 per cent in total assets during 2016 as compared to 12.8 per cent during 2015. This sharp decline in the growth rate is consistent with the slower economic growth rate (Graph 2.40). Graph 2.40 Assets Structure of NBFIs

RO Million 2,500 17 Vittas, Dimitri, 1999, “The Role of Non-Bank 2,000 Financial Intermediaries (with Particular Reference 1,500 to Egypt)”, Policy Research Working Papers, The 1,000 World Bank.

500 18 Gabriela Anghelache & Alexandru Manole & Ana Carp & Cristina Sacala, 2016. “Tendencies in the 0 2012 2013 2014 2015 2016 evolution of the private pensions system in Romania”, Exchange Houses Finance & Leasing Insurance Romanian Statistical Review, vol. 64(11), pages 101- 111.

Financial Stability Report - 2017 53 Chapter II

Box 2.3 On Co-existence of Islamic and Conventional Banks: Do These Banks Differ in Business Structure1 Islamic and conventional banking institutions co-exist in and co-exist in a competitive atmosphere. Since the many countries. The higher growth of Islamic banking regulatory framework of the country has the provisions institutions (IBIs) raises questions about the business for conventional banks to open stand-alone Islamic structure of the Islamic banks and how does it differ branches, several conventional banks have availed this from that of conventional banks. 1 opportunity and started Islamic banking operations.

Islamic banking and finance mainly emerged because By employing bank-time fixed effects on a dataset from Islamic jurisprudence (shariah) does not allow the 2002:Q2 to 2016:Q1, they decipher how Islamic and transactions that involve usury or interest. Moreover, conventional operations within the same bank differ in gambling, discounted sale of debt, and excessive terms of their business structure and efficiency. After uncertainty in contracts are prohibited in Islam. Shariah controlling for an array of bank level characteristics, their also forbids investments in certain industries which are findings suggest that there is a significant difference in illegal based on its social values. business orientation of Islamic and conventional banking institutions, as measured by non-deposit funding to There has been a considerable debate that the practice of total funding, and gross loans to total assets ratios. The Islamic banks is different from what is proposed in theory. results demonstrate that IBIs rely less on non-deposit Accordingly, some studies argue that Islamic banks funding which implies that they are more engaged in are operating just like conventional banks (El Gamal core banking business. However, their asset portfolio (2006); Zaman (2002)). Others support this argument by reveals that they have lower loans to total asset ratio than showing that non-participatory debt-based modes used that of Conventional Banking Institutions (CBIs). This by Islamic banks are much higher than equity-based outcome indicates that IBIs are less involved in financial modes of financing that are encouraged in Islamic finance intermediation than their conventional counterparts. On theory. They conclude that practice of Islamic banking the other hand, IBIs are less efficient than CBIs. However, is indistinguishable from conventional banking (Khan with increase in their size, the differences between IBIs (2010); Chong and Liu (2009)). That is, Islamic banks use and CBIs in terms of cost efficiency and business structure asset-backed debt instruments such as murabahah (sale decline. They also show that, as IBIs become larger, their of merchandise on credit) and ijarah (operational lease) cost efficiency level also improves and the difference instead of joint venture financing modes as musharakah between IBIs and CBIs fades away. Moreover, with and mudarabah. These studies conclude that Islamic higher cost indicators, Islamic windows both small and banking is different from conventional banking in its form large of mixed banks are less efficient than conventional but not in substance. On the other hand, some scholars banking branches. They conclude that there are inherent advocate that it is inevitable to use debt financing (backed differences in the business orientation of IBIs and CBIs. by real assets) in transitional phase of IBIs to avoid moral hazard problem that exists in equity financing (Ahmad References: (1993); Yousef (2004)). Ahmad, Ausaf, 1993, Contemporary practices of Islamic Zaheer and Farooq (2017) test if the business structure financing techniques, Islamic Economic Studies 1, 15-52. of IBIs is different from conventional banking using Chong, Beng Soon, and Ming-Hua Liu, 2009, Islamic income, funding, and financing structure of Islamic banking: Interest-free or interest-based? Pacific-Basin and conventional banking. Using banking sector data Finance Journal. of Pakistan, they investigate how Islamic banking in practice is different from conventional banking in El-Gamal , Mahmoud A., 2006. Islamic finance: Law, terms of business structure and related cost efficiencies. economics and practice (Cambridge University Press, Pakistan is among those countries that has been hosting New York). both conventional and Islamic banks for more than a Khan, Feisal, 2010, How `Islamic’ is Islamic Banking?, decade. Currently, both systems are well developed Journal of Economic Behavior & Organization 76, 805- 820.

1 This section is based on, Zaheer, Sajjad and Farooq, Yousef, Tarik M., 2004, The murabaha syndrome in Moazzam, 2017, On the Co-existence of Conventional and Islamic Islamic finance: Laws, institutions and politics, in Clement Banks: Do These Banks Differ in Business Structure. In H. Kabir M. Henry, and Rodney Wilson, eds.: The politics of (Ed.), Handbook of empirical research in Islam and economic life ( assessment and treatment (pp. 355-374). USA: Edward Elgar. islamic finance (Edinburgh University Press, Edinburgh).

54 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

2.60. With the addition of two more mutual Finance and Leasing Companies funds during the year, 23 mutual funds were Lending Remains the Leading Segment of the operational in Oman at the end of 2016. Of Asset Portfolio of the FLCs. However, Credit these funds, 18 were open- ended with a Net Growth Slowed Down during the Year Asset Value of RO 236 million, while the other 5 were closed-ended funds with Net Asset 2.61. The gross financing portfolio of FLCs Value of over RO 162 million as of end of registered a growth rate of 3.8 per cent (2015: 11 December 2016 (Graph 2.41). The asset base per cent) during 2016. The net credit portfolio of the mutual funds suggest that the overall thus grew to RO 1,028 million at the end of 2016. mutual funds market is small. However, the The lending growth of the FLCs declined with the growth in the number of funds is valuable as decline in the growth rate of economic activities. it provides additional options of diversified and FLCs do not accept checking or demand deposits, professionally managed investment avenues for therefore, they do not need to carry large cash small investors. balances or liquid assets. Consequently, they can employ a larger proportion of their assets in financing or other earning assets. Financing, therefore, continued to have a dominant share in the Graph 2.41 assets of FLCs. At the end of December 2016, the Mutual Funds net financing constituted about 95 per cent of total assets of FLCs suggesting efficient deployment 250 20 of assets. Currently, with a share of 65 per cent, 200 RO Million 15 financing to businesses declined from the previous 150 year’s when it was 68 per cent of the total financing 10 100 provided by FLCs. Financing to households was 50 5 about 35 per cent (2015: 32 per cent) of the total credit extended by FLCs (Graph 2.42). 0 0 Closed Ended Open Ended Value Number (RHS) 2.62. FLCs usually provide asset based financing, which is also the forte of Islamic banking institutions (IBIs). With the growth of Islamic banking, FLCs are facing stronger competition from the banking sector. Considering Graph 2.42 that IBIs and FLCs are vying for similar financing Assets Structure of FLCs classes, some consolidation among these financiers may provide value to the shareholders. 100 RO Million per cent 1,200 80 NPLs Increased Amid Slower Credit Growth 1,000 60 – Vulnerable Borrowers Call for Heightened 800 40 Monitoring 600 20 400 2.63. The NPLs of FLCs increased by RO 0 200 9.7 million during 2016. The growth of NPLs 0 outpaced the credit growth, as a result, the NPL Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Personal Loans Business Loans ratio increased to 5 per cent at the end of 2016 Adv. / Total Assets (RHS) from 4.3 per cent at the end of the previous year. Likewise, the net NPL ratio (without accounting for general provisions) increased to 2.9 per at the end of 2016 cent from 2.15 per cent in 2015

Financial Stability Report - 2017 55 Chapter II

(Graph 2.43). The NPL ratio of FLCs remained 2.65. The FLCs continued to count primarily much higher than that of the banking sector. on bank borrowing and capital to fund their Moreover, the business customers of FLCs are operations. At the end of December 2016, mainly from SME sector that are more vulnerable bank borrowing constituted 63.4 per cent to economic downturns. FLCs should, therefore, (2015: 61.7 per cent) of the balance sheet of gear up their credit analysis, monitoring, and FLCs. However, there is a marked change in risk management practices to keep the credit risk the composition of the bank borrowing. At within manageable limits. the end of 2016, the long-term bank funding Decrease in Long Term Bank Funding and More declined to 23 per cent (2015: 47 per cent) Short Term Funding in Rising Interest Rate of total bank funding, while the share of Environment are Unfavourable Cues – Higher short term bank borrowing increased to 77 Funding Costs and Declining Financing Rates per cent as compared to 53 per cent in 2015 may Weigh on Profitability (Graph 2.44). Heavy reliance on short term 2.64. Lately, CBO allowed FLCs to raise six- bank borrowing continued to expose FLCs month term deposits from corporates, this was to the cost and availability of bank funding. expected to help them diversify their sources Moreover, becaus of the interconnectedness of funding. However, FLCs could not mobilize with banks, shocks from banks may be quickly much deposit from this source. transmitted to FLCs.

2.66. The earnings of FLCs marginally Graph 2.43 declined during 2016. FLCs posted pre-tax Trends in Non Performing Loans profit of RO 35.3 million during 2016 as compared to 36.4 million during the previous year. Similarly, the profitability indicators, RO Million per cent 70 8 ROA and ROE, also slightly declined but 60 50 6 remained healthy at 3.3 per cent(2015: 3.7 40 per cent) and 13.6 per cent (2015: 14.6 per 30 4 19 20 cent), respectively (Graph 2.45) . The decline 10 2 in earnings was primarily on account of the 0 -­‐10 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 0 higher cost of borrowing from the banks. Gross NPLs NPLs to Loans(RHS) Net NPLs to Net Loans(RHS) Moreover, declining yield on financing due to heightened competition also contributed to decrease in profitability. Due to pressure Graph 2.44 on lending rates because of increasing Funding Structure of FLCs competition from IBIs, higher funding costs because of the increase in policy rates, and RO, Million 1,500 potential increase in provisions, the FLCs may find it increasingly challenging to maintain 1,000 the level of profitability unless they make concerted changes in their business model. 500

0 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 Capital and Reserves Bank Borrowing(Long-­‐term) Bank Borrowing(Short-­‐term) Deposits 19 In this section profitability ratios are calculated using Other liabilities pretax figures.

56 Financial Stability Report - 2017 FINANCIAL INSTITUTIONS

Insurance Sector 2.68. From the traditional metrics, Oman appears to be relatively under-insured. Therefore, Slower Economic Growth May Weigh on the it continues to offer ample growth opportunities Growth of the Sector – Significant Upside to insurers. Remains to be Tapped 2.69. The indicators used to measure the 2.67. The insurance sector in Oman, development of insurance sector indicate that there comprising 22 insurance companies, grew is significant space for growth of the insurance steadily over the past few years on back sector in Oman. The Insurance Penetration, of the growing economy and increasing defined as the ratio of insurance premiums to population. However, during the recent phase GDP, was about 1.8 per cent which is comparable of consolidation and declining economic to that of GCC countries but remains much activity, the growth rate of the insurance sector lower than the global average of 6.5 per cent. remained low. The muted economic growth, Likewise, Insurance Density, which is per head smaller addition to the stock of vehicles, and insurance premium, is about RO 99 (2015: RO shelving of some non-essential projects may 107) per person as compared to the GCC average weigh on the growth of the sector. of RO 141 and global average of RO 252 per head (Graph 2.46). Both of these indicators are suggestive of the potential available to cater to Graph 2.45 the underserved and unserved market segments. Earnings Indicators - FLCs The upside potential along with commencement of operations by two Shariah compliant takaful companies suggest that despite some slowdown in per cent 40 RO, million 15 economic activity, the long term growth prospects for the insurance sector remain optimistic as the 30 10 growth may pick up with an increase in product 20 awareness. 5 10 Motor Insurance Leads the Premium Collection; 0 0 Dec-­‐12 Dec-­‐13 Dec-­‐14 Dec-­‐15 Dec-­‐16 High Retention and Loss Ratios Calls for Stringent Pro0it Before Tax ROA (RHS) Risk Management – Group Life Insurance also ROE (RHS) Lending Rate (RHS) Needs Attention 2.70. The premium collected by insurance companies registered an increase of about two per Graph 2.46 cent (2015: 11 per cent) during 2016. The gross Insurance Penetration and Density premiums reached RO 455 million from RO 442 million in 2015. The general (non-life) insurance 7.0 sector continued to be the dominant segment in per cent RO 300 6.0 250 the insurance business with a share of about 85 5.0 200 4.0 per cent in gross premiums. Within this segment, 150 3.0 the motor insurance leads the premium collection 100 2.0 with a share of about 35 per cent (Graph 2.47). 1.0 50 -­‐ 0 Insurance Penetration Insurance Density 2.71. On average, the insurers retained about 57 Source: CBOOman Staff (2016) Calculations, GCC NCSI, (2014) CMA, Alpen CapitalWorld GCC (2015) per cent of the risk, while transferred the rest to InsuranceSource: Industry CBO Staff Calculations, NCSI, CMA, Alpen Capital GCC Insurance Industry the re-insurers. However, for motor insurance, the insurance companies retained about 83 per cent of premiums (and proportionally higher risks).

Financial Stability Report - 2017 57 Chapter II

2.72. The net claims paid against motor insurance constituted about 56 per cent of the claims paid by the insurance companies. Higher Graph 2.47 claims along with higher retention ratio implied Gross Premiums and Retention Ratio that the net loss ratio (net claims / net premiums) for motor insurance also remained high at 77 per RO, Million per cent cent. That is, 77 per cent of the premiums earned 400 100 by underwriting the motor risks were paid back in 80 300 the form of claims. High retention ratio coupled 60 200 with high loss ratio for the motor insurance calls 40 for stringent risk management regimes to guard 100 20 against large losses. The loss ratio for group life was 0 0 the highest at 96 per cent (Graph 2.48). However, Total Others Marine Motors Medical liability Property group life as the group life forms a smaller segment of the engineering Life indvidual insurance companies, the net claims paid against SourceGross : CMA Premiums , CBO Staff Net Calculations Premiums Retention Ratio (RHS) group life were only about 6 per cent of the claims paid by the insurance companies during 2016. Money Exchange Companies Graph 2.48 Growth Tendencies Continue – Substantial Net Claims and Loss Ratio Operational and Reputational Risk Exists, while 200 RO, Million per cent 100% Systemic Risk is Limited 200 RO, Million per cent 100% 80% 150 80% 150 2.73. Money exchange companies are primarily 60% 100 60% engaged in the business of remittances and 100 40% 40% currency exchange. The flexible working hours 50 50 20% 20% and efficient operations of these companies ensure 0 0% the documentation of remittances and discourage 0 0% Total Others Marine Motors Medical liability Total informal channels of money transfer especially Property Others Marine Motors Medical group life liability Property group engineering life Life indvidual engineering for small ticket remittances. Life indvidual

Source : CMA Net , CBO Staff Claims Calculations Paid Loss Ratio 2.74. The growth rate of value and volume of Net Claims Paid Loss Ratio remittance tapered during 2016 as these grew by one per cent and 0.6 per cent, respectively. Nevertheless, the volume of transactions handled Graph 2.49 (13.24 million) remained substantial giving rise Money Exchange Companies to high operational risks. Unlike the remittance business, the currency exchange recorded a large growth (57 per cent) during 2016. The total value 5,000 RO, million million 15 of foreign currency exchanged by these companies 4,000 grew to RO 3.2 billion during 2016 as compared 10 3,000 to RO 2 billion during 2015.

2,000 5 2.75. Due to large and increasing volume of 1,000 operations and extensive customer interactions, 0 0 operational risk is particularly important for 2012 2013 2014 2015 2016 these establishments that may eventually lead to Cy. Notes Exchanged Remittances Value Remittances Volume (RHS) reputational and legal risks. However, the size of individual companies and nature of their business means that they do not pose systemic risk to the financial system.

58 Financial Stability Report - 2017 Chapter III Financial Sector Regulation and Infrastructure

The cooperation at the global stage to coordinate financial sector regulations continued. In 2016, Central Bank of Oman made significant inroads in ensuring that its regulatory framework and supervisory policies cater to the changing operating conditions and needs of the economy while serving its stated objective of ensuring of financial stability to facilitate economic growth. Some regulations were adopted to ensure that Oman complies with the international legislation and global best practices while other regulations and policies were fine-tuned to cater to the domestic needs. During the year, a new Anti-Money Laundering Law was promulgated, Bank Resolution Framework was formulated, policies to improve Financial Inclusion were introduced, and guidelines on Sound Compensation Practices, Correspondent Banking Relationships, and adoption of IFRS 9 were issued. Oman is on track with its implementation schedule of Basel III capital and liquidity standards. Moreover, the Payment and Settlement Systems in Oman remained robust while the settlement values slightly declined during 2016.

REGULATORY DEVELOPMENTS IN OMAN concerted efforts to ensure implementation of its policies in letter and spirit. Some of the key 3.1. The global post-crisis focus on developments in financial regulations in Oman harmonization and increased coordination are enumerated below. of financial regulations continued. In this backdrop, the Central Bank of Oman (CBO) a) New Anti-Money Laundering Law and carried on with its endeavors to step up its Establishment of a National Center for regulatory and supervisory policies to keep Financial Information those aligned with the international best 3.2. In Oman, a Law of Money Laundering practices while at the same time fine-tuning the was promulgated in 2002 that was followed policies and regulations to cater to the domestic by Executive Regulation of the Law of Money needs. The central theme of the CBO policies Laundering in 2004. An upgraded Law of has been to ensure that instead of focusing Anti-Money Laundering and Combating the entirely on short term, non-sustainable, risk Financing of Terrorism (AML/CFT) law prone gains, the banks develop sustainable was made public in 2010 and pursuant to the business models and align themselves to cater provision of the Law a Financial Investigation to the diverse needs of the real sector while Unit was established under the aegis of Royal remaining less crisis-prone and more stable. Oman Police. To strengthen the legislation on Other than devising policies and regulations AML/CFT, a new Law on “Combating Money aimed at bolstering financial stability, CBO Laundering and Terrorism Financing” was keeps a tab on innovations affecting the financial issued in 2016 through a Royal Decree. sector. An overview of Financial Technology or FinTech is given in Box 3.1. CBO also made

Financial Stability Report - 2017 59 Chapter III

Box 3.1 Financial Technology

Financial technology, also known as FinTech, is and payment verticals taking the lion’s share2. While an industry composed of companies that use new it all stemmed out of Silicon Valley and still dominate technology and innovation with available resources the world innovation index, London has taken in order to compete in the marketplace of traditional over the overall global ranking first place as world financial institutions and intermediaries in the best Fintech hub followed by Singapore as per the delivery of financial services1. FinTech startups aim at latest report of the Global Fintech Hub Report. The providing easier, accessible, and affordable financial rankings evaluated FinTech hubs across six indices: services to their target customers. They span over six Regulation, Access to Expertise, Foreign Startup, vertical business lines namely: Insurance, Payments, Proximity to Consumers, Innovation Culture, and Deposit and Lending, Capital Raising, Investment Government Support. Management, and Market Provisioning. Some of the benefits of Fintech include social impact The FinTech gained traction out of the Silicon Valley such as financial inclusion, improved efficiency, and after the 2008 financial crisis. Fintech startups reduction of systemic risks by increasing diversity nowadays compete with the incumbent financial of customers within the financial system through its institutions either to tap into the unserved segment offering of more accessible, affordable, and efficient of the customer base (especially millenniums born financial services and products. On the flipside, in late 80s and early 90s) or unhappy customers of FinTech also introduce many new risks to the existing existing financial institutions. According to Citi & banking & financial sector. For instance, there is risk CB insights May 2016 report, FinTech investments of increased harm to investors and consumers through have increased by 10 folds in the past five years to fraud, increased risk of data misuse, risks beyond the touch $19 billion in 2015. In first quarter of 2016, control of regulatory framework in addition to macro- Fintech investments reached $5.7 billion with lending prudential risk like unattended concentration risks.

1 Infinite Financial Intermediation, 50 Wake Forest Law Review 2 The Pulse of Fintech, Q1 2016, Global Analysis of Fintech 643 (2015). Venture Funding, May 25th, 2016.

60 Financial Stability Report - 2017 Financial Sector Regulation and Infrastructure

3.3. The new Law is wider in its scope and 3.7. Based on the systemic scores, Bank application and introduces operational and Muscat was designated as D-SIB in Oman. As supervisory architecture for the enforcement the D-SIB, the bank is subjected to an enhanced of the Law. The Law envisages establishment regulatory and supervisory framework. The of The National Committee for Combatting additional requirements for the D-SIB include Money Laundering and Terrorism Financing. one per cent systemic capital surcharge, an The Committee is mandated to establish, upgraded stress testing suite including macro develop, and follow up on the implementation stress tests, biannual meetings with the D-SIBs of a national strategy for prohibiting and Committee of CBO to discuss issues of systemic combating crimes of money laundering and relevance, improved risk appetite framework, terrorism financing in coordination with the and a board approved Recovery & Resolution Plan (RRP). competent regulatory authorities. 3.8. Bank Muscat submitted its RRP in 3.4. The Law also mandates setting up a December 2015 that includes a self-propelled National Centre for Financial Information as a recovery in extreme cases and identifies RRP legal person with administrative and financial related roles & responsibilities. The RRP of the powers. The Centre shall have the mandate of Bank spells out its operations, core & critical receiving, analyzing, and requesting reports functions, the inherent risks, recovery triggers, and information suspected of being related mitigating measures, and recovery options to or linked to money laundering or terrorism re-establish the Bank’s health. financing activities. It shall also receive other information related to cash transactions, wire 3.9. CBO is in the process of finalizing transfers, cross-border declarations, and other the Bank Resolution Framework for Oman. reports set by the supervisory authority. The objective of the Resolution framework is to save financial institutions, but if that is not 3.5. The new AML/CFT law is expected to possible then it allows CBO to resolve them in further strengthen the AML/CFT standards and an orderly manner, with the least disruption, and oversight in Oman. without burden on national exchequer while maintaining continuity of their vital economic b) Bank Resolution Framework in Oman functions and preserving financial stability. 3.6. CBO issued its framework to identify 3.10. The corpse of the Resolution framework and deal with Domestic Systemically is derived from FSB’s Key Attributes of Important Banks (D-SIBs) in January 2015. Effective Resolution Regime. It covers legal and The identification strategy for D-SIBs is based institutional elements of the bank resolution as on the principles and criteria suggested by also firm-specific resolution plans for D-SIBs/ BCBS while modifying the indicators suitable other financial institutions. These elements for Oman. To calculate systemic score, banks cover (i) the governance structure that involves are assessed across five dimensions: size, the highest authority in CBO; (ii) Internal interconnectedness, substitutability, complexity procedures that seek to elaborate the role and (including cross-jurisdictional activity), and responsibilities of all stakeholders including the domestic sentiment using various indicators. departments within CBO that need to work to All dimensions have equal weightage. Total a pre-determined action plan so that there is a score – the ‘systemic score’ – signifying the seamless process to take an important decision systemic importance of each bank is thus like bank resolution and execute the same with obtained. precision and prudence; (iii) A clear-cut process

Financial Stability Report - 2017 61 Chapter III

flow based on the triggers and events that might venues to boost financial stability through a unfold (a schema of the process flow is given wider and more diversified user base and a in Figure 3.1); (iv) Resolution powers that deeper financial system. During 2016, CBO allow scope for action to CBO commensurate took a series of steps to increase financial to its responsibility; (v) Resolution triggers that inclusion in Oman. Banks were advised to guide initiation of resolution plan; (vi) Funding take necessary steps to facilitate provision options that may be quickly used in case of of banking services to disabled persons. need; (vi) A resolution toolkit that documents Similarly, the banks were urged to open outlets and assesses various resolution options; (vii) and offer their services in under-banked, far Provisions for resolvability assessment; and flung interior and border regions with a view (viii) Bank-specific resolution plans. to support economic activities in such regions. 3.11. Once operationalized, the Bank To create proper incentives, CBO linked Resolution Framework would form an integral the approval of new banking outlets in other part of the crisis management framework and locations with the provision of services in would boost the capacity of CBO to handle under-banked areas. Moreover, CBO adopted bank resolutions. the criteria set by Public Authority for Small and Medium Enterprises Development to C) Financial Inclusion define SMEs and besides banks, urged finance 3.12. It is argued that financial inclusion & leasing companies to take cognizance of the not only aids inclusive growth but also offers needs of the SME sector.

Figure 3.1

Process Flow for Bank Resolution in Oman

Capital Conservation RECOVERY PRE-RESOLUTION RESOLUTION Buffers (CCB) TRIGGER TRIGGER TRIGGER BREACH

Is Bank NO Viable?

YES NORMAL PREPARATION TEMPORARY CCB RULES SUPERVISORY RECOVERY FOR STABILIZATION RESOLUTION GOVERNMENT KICK-IN REGIME RESOLUTION CONTROL / EXIT YES

Is Bank NO YES Viable? NO Conservation Actions NO Successful? Private Sector Resolution Resolution Recovery NO Successful? YES Successful? Feasible / Needed? YES YES NO

PROCEDURES AT A GLANCE

NORMAL REGIME CCB Rules RECOVERY RESOLUTION STABILIZATION RESOLUTION TEMPORARY - Apprise higher - All of “Resolution GOVERNMENT CONTROL - On-site Examination. Follow the approved PREPARATION management of the - Freeze all transactions in Preparation” plus, / EXIT Capital Conservation - Apprise higher breach of recovery the bank with immediate - Determine the resolution - All “Resolution - Off-site Surveillance. Buffers Framework: management. threshold. effect. strategy and exercise least Preparation”, necessary - Seek for “stressed time” - Reducing dividend - Evaluate the adequacy - Announce Closure of costly option. “Resolution” steps plus, - Stress Testing. information. payments. and feasibility of recovery bank for 48 hours. - Legal consultation - Seek Approval of BoG of - Prompt for special actions. - Call detailed information - Act as or Appoint CBO and BDIS. - Monitoring of Capital - Share buybacks. examination. - Monitor recovery of insured/un-insured receiver. - Coordinate with MoF for Conservation Buffers, - Enlist outside consultants -Staff bonus cuts. actions and progress deposits. - Meeting with BoD necessary approvals. Recovery, and Resolution to assess losses / value. made by the Bank. - Re-open with full access - Approval of BoD for due - Determine an exit Thresholds. - Explore feasible -Plan to raise new capital - Evaluate the success of to insured deposits / part diligence by interested strategy and seek resolution options. the recovery actions, and access rest to rest of theof the parties. approval for Time frame. - Set-up data / legal determine future course deposits. - Marketing plan/ - Follow “Resolution” documents dossier. of action. authorization. steps.

62 Financial Stability Report - 2017 Financial Sector Regulation and Infrastructure d) Sound Compensation Practices: of such important business in big scale could potentially carry serious and unintended 3.13. Compensation practices in financial consequences in the affected countries leading institutions that rewarded short-term risk to financial stability issues and also economic taking at the cost of long-term profitability growth. Because of the importance of continuity were a contributing factor to the global of correspondent banking relationships, CBO financial crisis. In response to that and has advised banks to ensure that they have to align compensation with prudent risk- robust policies and practices that enable taking, the Financial Stability Board issued them to continue to remain attractive for the principles and implementation standards for correspondent banking relationship. Banks Sound Compensation Practices. To comply were also advised to refer to the Anti-Money with the international best practices, in April Laundering Principles for Correspondent 2015, CBO advised banks to implement Banking issued by the Wolfsberg Group to sound compensation principles and standards guide their policies and practices. covering all material risk takers including performance-related recipients. The banks can f) Adoption of IFRS 9 themselves design appropriate compensation 3.15. IFRS 9 is an International Financial schemes, however, a minimum of 45% of Reporting Standard (IFRS) that was issued variable component is required to be deferred by the International Accounting Standards and paid annually (equally) over the three years Board in 2014. Once it becomes effective subsequent to the appraisal year. In February in 2018, it will replace IAS 39. It deals with 2016, CBO allowed some flexibility to the the accounting for financial instruments and banks by allowing them to exempt annual includes (i) a logical model for classification variable component of less than RO 35,000 & measurement of financial instruments, (ii) a from deferment regardless of the position of forward-looking ‘expected loss’ impairment of the recipients of such compensation. financial assets, and (iii) a reformed approach e) De-Risking and Correspondent Banking to hedge accounting.

3.14. Many new regulations and regulatory 3.16. Consequences of IFRS 9 include higher standards enacted post-crisis have induced income statement volatility as more assets many large global banks to scale back (de- might be measured at fair value; and earlier risking) their correspondent banking relations. recognition of impairment losses on loans as Enforcement of AML/CFT regulations; the entities will have to make provisions for future introduction of the US Foreign Account Tax credit losses even if recovery is plausible1. Compliance Act (FATCA) are also seriously 3.17. Oman will adopt this reporting affecting the operations of select global banks standard from its effective date. In April 2017, in MENA region including Oman. As such, the business costs of correspondent banking on CBO issued implementation guidelines to account of enforcement of stricter AML/CFT ensure satisfactory implementation, promote guidelines have gone up steadily. Punitive consistency of application, facilitate greater penalties imposed on breach of such standards comparability across financial institutions, and have also contributed to such incremental address supervisory concerns. IFRS 9 prescribes costs. Correspondent banking relationships are becoming more demanding, more time 1 IFRS 9, Financial Instruments Understanding the consuming and more complex. Withdrawal basics, PwC.

Financial Stability Report - 2017 63 Chapter III an expected loss model for provisioning, hence Capital Buffers: the provisioning requirements under this 3.21. The Basel III capital proposal also standard are expected to be higher than that includes introduction of capital conservation under IAS 39. Nevertheless, to mitigate model and countercyclical buffers comprising risk CBO has adopted a conservative approach common equity. The purpose of capital to assess impairment allowance/ losses. If the conservation buffer is to hold buffers to protect impairment allowance/ loss calculated under the capital backing. When a bank dips into its IFRS 9 is less than what is needed under the capital buffers, the capital restoration measures existing provisioning requirements set by may be kicked in by carefully evaluating and CBO, then the difference must be transferred /or restricting dividend and bonus payouts. to an Impairment Reserve account. This Capital framework has also been made more Impairment Reserve would not be available countercyclical with countercyclical capital for payment of dividends and would not count buffer being required to be held in good times towards regulatory capital. to prepare for plausible downturns. 3.18. Considering that the banking sector 3.22. The capital conservation buffer was is well capitalized and the existing NPLs are introduced in Oman since January 2014 at adequately covered with specific provisions of the rate of 0.625 per cent of risk weighted 70 per cent and total provisions 148 per cent assets. From January 2017, it is increased to of NPLs, the banking sector appears to be well 1.25 per cent of risk weighted assets, while positioned for the implementation of IFRS 9. progressively it would increase to 2.5 per cent of risk weighted assets in 2019 when it is fully g) Basel III Implementation Status kicked-in. Capital Standards: 3.23. To contain buildup of systemic risk, 3.19. The core objective of the Basel III CBO also issued guidelines to introduce capital proposal is to improve the quality and counter-cyclical capital buffer of up to 2.5 per level of capital. This is achieved by stressing cent of risk weighted assets if CBO deems that the role of common equity as the best form of the credit growth is excessive and may lead to capital to withstand idiosyncratic and systemic build-up of system-wide risks. Following BIS recommendations, a host of indicators with shocks. The proposal includes holding of Credit-to-GDP gap (using various definitions substantially more capital, tighter definitions / aggregation of credit and GDP) as primary of capital, greater emphasis on higher quality guide are used to determine if countercyclical capital, and standards to ensure that other types capital buffer is warranted or not. As of of capital instruments are truly loss-absorbing. December 2016, the maximum counter- 3.20. CBO issued final guidelines on capital cyclical capital, if activated was 0.625 per cent. requirements under Basel III in 2013. Under It has been increased to a maximum of 1.25 per the guidelines, the minimum Common Equity cent of risk weighted assets with effect from Tier 1 ratio, Tier 1 capital ratio and total January 2017 while it will gradually increase Capital Adequacy ratio are 7 per cent (BIS to 2.5 per cent of risk weighted assets in 4.5 per cent), 9 per cent (BIS 6 per cent) and 2019. The implementation status of the capital 12 per cent (BIS 8 per cent) of risk weighted requirements in Oman and its comparison with assets, respectively. New capital requirements the BIS requirements is given in Table 3.1. will be gradually phased-in by 2019.

64 Financial Stability Report - 2017 Financial Sector Regulation and Infrastructure

Table 3.1 Capital as per cent of Risk Weighted Assets 2015 2016 2017 2018 2019 Common Equity Tier1 (CET1) excluding BIS 4.5 4.5 4.5 4.5 4.5 CCB and CCyB CBO 7 7 7 7 7 BIS 6 6 6 6 6 Tier 1 Capital CBO 9 9 9 9 9 BIS 8 8 8 8 8 Total Capital excluding Buffers CBO 12 12 12 12 12 Capital Conservation Buffers (CCB) 0.625 0.625 1.25 1.875 2.50 Countercyclical Capital Buffers (CCyB) 0 - 0.625 0 - 0.625 0 - 1.25 0 - 1.875 0 - 2.50 Systemic Capital Surcharge for D-SIBs - - 0.40 0.70 1.00

Systemic Capital Surcharge Liquidity Standards: 3.24. CBO formulated its framework to identify 3.26. Basel III liquidity regulations mandate and regulate D-SIBs in Oman in January 2015. The adherence to a short-term Liquidity Coverage framework allows for systemic capital surcharge of Ratio (LCR) to withstand a 30-day crisis; and a up to 3.5 per cent. Under the framework, the Banks longer-term Net Stable Funding Ratio (NSFR) to are ranked by their systemic importance using an reduce the inherent maturity mismatch in banks’ indicators based approach and are placed in five balance sheets. LCR requires banks to hold buckets based on their systemic importance within sufficient high-quality liquid assets (HQLAs) the banking sector. The higher loss absorbency that can be easily and quickly converted to cash requirements are commensurate with the degree of to cover expected liquidity outflows in a stress systemic importance of banks and the surcharge is scenario over a 30-day period. Whereas, NSFR required to be met by common equity tier 1 capital. attempts to ensure that banks maintain a stable For Bank Muscat, which is designated as a D-SIB in funding profile in relation to the composition of Oman, a systemic capital surcharge of one per cent their assets and off-balance sheet activities over a of risk weighted assets was decided. The systemic one year time horizon. capital surcharge will be implemented in three 3.27. CBO issued guidelines for LCR and installments. The first phase of 40 basis points of related disclosures in 2014. The LCR was phased surcharge as a percentage of risk weighted assets in from January 2015 with a requirement of has been activated from 1st of January 2017, and it having LCR of 60 per cent or more. Effective will fully phase-in by January 2019. from January 2017, the LCR requirements Leverage Ratio are increased to minimum of 80 per cent. The minimum requirements will be increased by 3.25. An underlying feature of the financial 10 percentage points each year until fully crisis was the build-up of excessive leverage in implemented by January 2019. the banking system despite maintenance of strong risk based capital ratios. Basel III standards seek 3.28. Banks were required to report their to address this issue by placing a limit on the size NSFR positions during an observation period of on- and off-balance sheet activities that banks running until 2016. In October 2016, CBO can undertake in relation to their capital base. As issued final guidelines on NSFR and related per the roadmap of implementation of Basel III disclosures. Effective 1st of January 2018, the standards, CBO will issue guidelines for leverage NSFR requirements would become binding with ratio during 2017 and the prescribed ratio will be a minimum ratio of 100 per cent. applicable with effect from January 2018.

Financial Stability Report - 2017 65 Chapter III

PAYMENT AND SETTLEMENT SYSTEMS 3.30. The obligations arrived at from the net clearing positions of retail payment system like Aggregate Value & Volume ECC, ACH, and OmanNet Switch get settled Aggregate values decreased but payments in through the RTGS, thereby being the backbone volumes have seen a rise of the payment and settlement infrastructure and systemically important financial market 3.29. The aggregate values of the transactions infrastructure. While, retail systems have a through the Payment and Settlement Systems total value of RO 22.78 billion, with daily (PSS) operated by CBO, witnessed a moderate average size of each transaction at around RO decrease of 8.08 per cent in 2016 to reach RO 61 million. On a year-on-year basis, there had 172.78 billion from RO 187.97 billion in 2015 been a slight increase in retail-value of 1.01 per (Graph 3.1). Real Time Gross Settlement System cent. (RTGS) transactions dominate the system in terms of value (nearly 87 percent) and it plays a 3.31. Aggregate volume transfers, on the other critical role in the overall economic activity of hand, registered a significant increase during Oman, with a total value of RO 149.99 billion, or 2016 (Graph 3.2). Total number of payments on average around RO 410 million per day. On a increased by 47.52 per cent, from around 37 year-on-year basis, there had been a decrease in million transactions in 2015 to 55.90 million RTGS-value of 9.32 per cent. in 2016. Retail systems led this increase with a total share of around 55.40 million (99.11 per cent). On a year-on-year basis, there had been Graph 3.1 a significant increase in retail-volume of 48.17 Trends in Value per cent. Worth mentioning, retail Payment Systems are designed for large volumes of low value transactions; when compared to the RTGS system which generally caters to large value 200 RO, Billions transactions. While RTGS has significantly 150 lower share in terms of volume (less than 1 per 100 cent) with total volume of transactions executed

50 through RTGS stood at 497 thousand.

0 3.32. On a year-on-year basis, there had 2012 2013 2014 2015 2016 been a decrease in RTGS-volume of 1.02 per Retail Value RTGS Value Value cent when compared to the increase in the volume of transactions processed through the retail payment systems. However, the increase Graph 3.2 in payments transactions reflects primarily Trends in Volume the economic growth of the country and the continuous improvements in information technology and security system that has 60 RO, Millions increased the efficiency and reliability of the 50 payment system. However, the slowdown in 40 RTGS system activities when compared to the 30 20 last three years reflects the lower growth rate in 10 the economy. 0 2012 2013 2014 2015 2016 RTGS Volume Retail Volume Volume

66 Financial Stability Report - 2017 Financial Sector Regulation and Infrastructure

Retail payments 3.36. Furthermore, Automated Clearing Housing forms the second popular form of 3.33. Within retail payment transactions, electronic-based payment after ECC with total Electronic Clearing Cheque forms the preferred value of RO 3.14 billion and with 11.20 per cent mode of payment in terms of value compared to share of the value of all retail transactions. ACH other retail payment systems (Graph 3.3). also was second in the list in terms of volume 3.34. ECC continued to dominate payments with 8.64 per cent share. ACH is generally used in value terms; transactions through ECC for multiple credits and multiple debits as payroll, accounted for 73.11 per cent of the total value utility bills, dividends, EMI payments, etc. of all retail transactions. 3.37. In addition to that, OmanNet registered 3.35. In terms of volume, OmanNet has the the highest growth rate in both terms of value largest share with 83.43 per cent compared to and volume (34.43 per cent and 58.77 per cent, the volume from other retail payment systems respectively) in 2016. (Graph 3.4). Although it comes third in terms 3.38. For the banks operating in Oman, the of value, with share of around 13.11 percent OmanNet Switch provides a gateway to the other during 2016. switches in GCC countries. OmanNet has already established links with Kuwait (KNET), Bahrain (BENEFIT), Qatar (NAPS), United Arab Emirates (UAE Switch) and Saudi Arabia (SPAN). Graph 3.3 3.39. ACH came second in place after OmanNet Trends in Value and it registered growth rate of 11.20 per cent and 14.03 per cent for value and volume, respectively. The increasing usage of ACH growth rates indicate 25 RO, Billions the growing preference of consumers to select 20 electronic means for payment as most suitable for 15 handling bulk and repetitive small value payments 10 (e.g. Salary, Pension, interest/ dividend, recovery 5 of monthly bills/ loan installments etc.).

0 ACH ECC OmanNet 3.40. Comparing to 2015, the decline in ECC Value 2015 Value 2016 growth rate by 4.87 per cent in 2016 was a major reason behind the overall slowdown in the growth rate of the aggregate value of retail transactions in the system. However, ECC growth rate increased Graph 3.4 slightly by 7.70 per cent in terms of number of Trends in Volume transactions processed in 2016. 3.41. Typically, the increase in the usage of

60 RO, Millions ECC, ACH, and OmanNet reflects the quality 50 of financial infrastructure in the country and the 40 level of technological development in the financial 30 system of an economy. As the availability of these 20 modes increase and consumers rely more on 10

0 electronic transactions, the efficiency, and safety ACH ECC OmanNet of the overall financial sector increase and become Volume 2015 Volume 2016 all solid.

Financial Stability Report - 2017 67 Chapter III

Stability of the System Daily Aggregate Clearing Balances Graph 3.5 Clearing Balances of all the banks have been in Daily Aggregate Closing Balances (2016& 2015) shortage in 2016

3.42. Daily average aggregate closing (clearing) balance for the year of 2016 at RO

5,000 RO, millions 1.48 billion was lower by 53.25 per cent as 4,000 compared to RO 3.16 billion for 2015. The 3,000 increase in daily average aggregate closing 2,000 balance in 2015 was due to some large foreign 1,000 deposits in Oman. 0 Dec-­‐14 Jun-­‐15 Dec-­‐15 Jun-­‐16 Dec-­‐16 3.43. By the same token, maximum daily closing balance for the year of 2016 was RO 3.51 billion. This is a decline by 20.34 per cent as against RO 4.41 billion for 2015. Similarly, Graph 3.6 minimum daily closing balance also declined by Liquidity Concentration 2016 34.24 per cent to RO 1.03 billion as against RO 1.56 billion in 2015 (Graph 3.5). The minimum 0.55 and maximum showed a volatile of 2016 with 0.50 0.45 difference between the two ranges reaching 0.40 0.35 about RO2.49 billion. 0.30 0.25 1 0.20 3.44. The HHI for most of the days in 2016 0.15 remained low, with daily average of around 0.10 0.05 0.14, suggesting low concentration in liquidity 0.00 Dec-­‐15 Mar-­‐16 Jun-­‐16 Sep-­‐16 Dec-­‐16 held by participants (Graph 3.6). This is a significant decrease in liquidity concentration level from the previous year’s daily average of 0.38 on the HHI. Graph 3.7 Liquidity Concentration (2016 & 2015) 3.45. Liquidity concentration level has decreased for the first quarter of 2016 with a daily average of 0.22 dramatically from 0.42 for 0.55 last quarter of 2015 on the Hefindahl–Hirchman 0.50 0.45 Index (HHI) (Graph 3.7). 0.40 0.35 0.30 0.25 0.20 1 Herfindahl-Hirschman Index (HHI) is used to assess 0.15 the degree of concentration of the system in liquidity 0.10 0.05 and payment. For the liquidity concentration, the 0.00 index is calculated for the daily closing balance in the Dec-­‐14 Jun-­‐15 Dec-­‐15 Jun-­‐16 Dec-­‐16 clearing for the participating banks as follows: The index ranges between zero and one, with larger values of index pointing to higher concentration in the system.

68 Financial Stability Report - 2017 Financial Sector Regulation and Infrastructure

3.46. However, during the second and the 3.48. After the exclusion of FOREX third quarters of the year the index experienced transactions between local financial entities some elements of intermittent temporary and the Central Bank of Oman outside the concentration, which is presumably due to payment and settlement system, the average seasonal impact (Holidays, Holy Month of daily payment concentration level in the system Ramadan, and Eid Occasions). Furthermore, the continued to remain moderate at 0.22 (Graph concentration levels ranged from a minimum of 3.8). Nevertheless, the concentration ranged 0.08 to a maximum of 0.49, which denotes that between a minimum of 0.0 to as high as 1.0, during the year, liquidity concentration levels which suggest that payment is not made evenly stayed relatively unstable especially for the first by all participants and that significant share of quarter of 2016. However, during the second, payment is made by only a few number of banks. third, and fourth quarter of 2016, liquidity Such a scenario could pose a systemic risk to concentration levels are relatively stable. For the payment and settlement system because if any of the banks active in payments failed for instance, the average concentration levels are any reason to make payment on time, the inflow 0.13 (Q2), 0.11 (Q3), 0.12 (Q4). of other participants will be impacted, and the Daily payment concentration case might get magnified through interbank channel, resulting in disturbance to the sector Overall Daily Payment Concentration continued and the economy at large. to remain moderate Shares in Payment System Activates 3.47. As in the case of liquidity concentration, the daily HHI of payment concentration One fourth of the payment in the system is was calculated using payment data from controlled by one bank – An alarming Feature RTGS, which showed relatively low payment from Financial Stability Perspective concentration in the system. Table 3.1

Shares in the Payment System

Bank 1 27.48%

Bank 2 11.73% Graph 3.8 Bank 3 10.13% Daily Payment Concentration 2016 Bank 4 10.09%

Bank 5 7.94% 1.2 Bank 6 7.35% 1 Bank 7 5.89% 0.8 0.6 Bank 8 6.74%

0.4 Bank 9 4.66% 0.2 Others 7.98% 0 Jan-­‐16 Mar-­‐16 May-­‐16 Jul-­‐16 Sep-­‐16 Nov-­‐16 3.49. Another form of vulnerability stems from the fact that each payment involves a paying as well as receiving bank. Therefore, the payment might not get executed if either banks involved failed, suggesting that every

Financial Stability Report - 2017 69 Chapter III bank is systemically important to payment and Transactions in Cheques settlement if its share in the payment turnover Bounced Cheques Continued to Feature High – is large relative to other banks. For assessing Insufficient Funds Lead the Reasons of Unpaid this risk, the Node Risk Index (NRI) has been Cheques calculated for every bank in the system as follows: 3.51. The duration of cheque processing payment made+payment received cycle form an important element in improving NRI= total turnover the efficiency and lowering credit risk of the 3.50. The average risk index value for all system. The shorter the time required for the banks worked out to around 4.20 per cent processing the cheques, the more efficient is (Table 3.1). The top bank in Oman continued the system and lower is the credit risk of non- to dominate payment with 27.48 per cent of the availability of expected funds. Moreover, less total turnover. However, around 60 per cent delay in processing the cheques can increase of the total turnover of financial transactions the velocity of money, which in turn impacts the stood dominated by four banks, suggesting that GDP of the economy positively and contributes more than half of the payment activity would towards enrichment of the economy. Graph be at risk should these four banks experienced 3.10 reveals that cheques are processed under problems. two channels – Regular Clearing and Special Clearing. The cheques presented by the participant banks in the regular clearing cycle Graph 3.9 before 12 p.m. are settled on the same day, and Shares in Payment System Activities the cheques deposited after 12 p.m. are settled on the next working day free of charge. Special

clearing, on the other hand, caters to urgent Bank 9 Others cheques and has an accelerated settlement 5% 8% Bank 1 within two on a business day. Banks using Bank 8 27%

7% special clearing session for presenting their cheques are charged a processing fee, which is Bank 7 6% equivalent to transaction charges specified for Bank 6 7% RTGS transactions (RO 3). This additional cost Bank 2 might have led to the decline in the number Bank Bank 5 4 12% Bank 3 8% 10% 10% of cheques using the special clearing facility from 1,747 in 2015 to 1,432 in 2016, while increasing the numbers of cheques using the regular channels from 4.08 million in 2015 to Graph 3.10 4.44 million in 2016 as it may be deemed a Cheque Clearing Duration better option due to its increasing efficiency in processing time and free of cost. 1432 3.52. In general, the total number of cheques, which were subject to the cheque clearing process in 2016, increased by 8.81 percent compared to last year, amounting to 4.44 4439247 million cheques. In 2016, bounced cheques increased as well and reached 373,082 cheques Regular Special Clearing from 282,209 cheques.

70 Financial Stability Report - 2017 Financial Sector Regulation and Infrastructure

3.53. Occasionally, a cheque can bounce due Graph 3.11 Reasons for unpaid cheques (Thousands) to a minor unintentional mishap. However, there are other more serious situations which can include criminal activity. Insufficient funds continue to lead the list of reasons of bounced cheques (74.88 per cent), followed up by account closed or “legally blocked” account (9.79 per cent), and then MICR Encoding errors (4.05 per cent). Overall, bounced cheques in Account Closed / Frozen / Transferred the system increased to 373,082 from 282,209 MICRInsuf�icient Encoding Fund errors Percentage Unpaid (RHS) (32.20 per cent) in 2016. In addition to that, as a percentage of total cheques, bounced cheques witnessed an increase from 6.91 per cent in 2015 to 8.40 per cent in 2016 (Graph 3.11).

Financial Stability Report - 2017 71 Chapter IV Stress Testing of the Banking Sector

Despite the macroeconomic conditions expressed in Chapter I due to the fall in oil prices in 2016, banks remain resilient to stressed scenarios at the aggregate level. Results of the different solvency stress tests did not flag an increased vulnerability of the solvency of banking sector mainly due to their high capital adequacy ratio as well as their limited exposure to equity and forex. The robustness of the banking sector is also echoed in the macro-financial stress test where system solvency remains above Basel III’s requirements even in the severe scenario’s shock level. Further, concentration to large corporate borrowers has seen a low risk to local banks and moderate to foreign banks. In terms of liquidity, banks continue to maintain comfortable level as evidenced from the results of the stress testing.

SOLVENCY STRESS TESTING : Top-down Stress Testing Graph 4.1 Losses in thousands resulted from the different risk 4.1. The CBO’s stress testing exercise simulates factors under the assumed stress scenarios

the individual and joint impacts of credit, equity,

interest rate, and forex shocks over a year of stress on the operating bank’s capital to risk weighted 107,535 (12%) 68,393 asset ratio (CRAR). The four different shocks are (8%) assumed to occur simultaneously and the total 83,564 (9%) impact is charged to the capital of the banks and 621,464 the Risk Weighted Assets (RWA) are assumed to (71%) be adjusted for losses. By using the balance sheet approach, the financial positions of the banks as Credit Shock Interest Rate Shock Forex Shock Equity Shock at the end of December 2016 have been stress tested and the impact on the capital adequacy of the banking system has been examined. The balance sheet approach has an advantage of Graph 4.2 assessing the elements of the banks’ balance CRAR of local banks after shocks under balance sheet approach sheets and identifying risk drivers. The detailed methodology used in conducting the solvency 25% CBO Requirement 12.625% stress tests providing the scheme of shocks used 20% for stress testing suggest that these shocks are 15% quite stringent. (Box 4.1). CRAR 10% 20.50% 21.63%

5% 16.13% 14.43% 13.99% 13.71% 13.64% 12.34% 11.87% 10.52% 4.2. Under the assumed stress scenarios, the 0% Bank A Bank B Bank C total losses of the entire banking system amounts Bank D Bank E Bank F to RO 880.9 million during the year. Credit risk Bank G Bank H Bank I All Local Banks factor is the largest contributor with a share of 71 per cent in the total losses followed by equity risk, interest risk and foreign risk which are

72 Financial Stability Report - 2017 Stress Testing of the Banking Sector jointly accounting for 29 per cent of total losses 4.5. As for foreign banks, they keep very (Graph 4.1). CRAR of the entire banking system high CRAR compared to local banks but would drop from 16.8 per cent as at the end of their share to total banking assets is only December 2016 to 13.92 per cent. 6.0 per cent. Under the stress scenarios, the 4.4. local banks showed a high resilience to aggregate CRAR of foreign banks would absorb comfortably the assumed losses. The drop from 19.96 per cent to 17.81 percent, aggregate CRAR of local banks would drop comfortably above the CBO requirement from 16.47 % to 13.64% maintaining a good of 12.625%. Despite most of foreign banks margin over the required CBO’s CRAR of showed a very high capacity to absorb losses, 12.625%. At individual basis, three local banks two of them would drop slightly below the would fall below the CBO required regulatory CBO requirement of 12.625 percent, however, capital CBO of 12.625 per cent, however, they they are still above Basel III requirement of are still above Basel III requirement of 10.5 per cent. In such a case, the amount required to 10.5 percent (Graph 4.3). recapitalize the local banks would be RO 81.5 Reverse Stress Testing million (Graph 4.2). 4.6. Under this approach, resilience of the banking system is assessed in a scenario of increasing Non-Performing Loans (NPLs)

Graph 4.3 by computing the level of maximum increase CRAR of foreign banks after shocks under balance in NPLs the banks could withstand without sheet approach compromising the minimum capital adequacy 140% 140% 140% requirement of 12.625 per cent. 120% 120% 120% CBOCBOCBO Requirement Requirement Requirement 12.625% 12.625% 12.625% 100% 100% 100% 4.7. The current NPLs of three local 80% 80% 80% CRAR CRAR CRAR 60% 60% 60% banks should increase by double before the 40% 40% 40% 96.66% 96.66% 96.66% 128.17% 128.17% 128.17% CBO’s required CRAR of 12.625 per cent 30.08% 30.08% 30.08% 17.81% 17.81% 17.81% 25.90% 25.90% 25.90% 24.60% 24.60% 25.46% 25.46% 24.60% 25.46% 12.35% 12.35% 16.64% 16.64% 12.35% 20% 20% 20% 16.64% 12.08% 12.08% 12.08% 0% 0% 0% is breached. The remaining four banks have Bank Bank Bank J J J Bank Bank Bank K K K Bank Bank Bank L L L Bank Bank Bank M M M Bank Bank Bank N N N Bank Bank Bank O O O more capacity to absorb further NPLs. Their Bank Bank Bank P P P Bank Bank Bank Q Q Q Bank Bank Bank R R R All All All foreing foreing foreing banks banks banks current NPLs level would increase by almost four times before breaching CBO’s required CRAR. The test is clearly in line with above balance sheet approach in showing a good Graph 4.4 capacity for local banks to absorbe the Increase in the current NPLs before CRAR drops below assumed losses (Graph 4.4). CBO requirement for local banks 4.8. For foriegn banks, NPLs of two banks should be doubled before their CRAR breach 4.2 4.0 3.9 3.7 the CBO required CRAR of 12.625 per 2.4 2.0 1.9 cent. Other banks showed a high resilience towards a rapid increase in their current BANK A BANK B BANK C BANK D BANK E BANK F BANK G NPLs as they have low levels of NPLs and *Execluding *Excluding Islamic islamic Banks banks due to their due negligible to thier current negligible NPLs current NPLs high underutilized capital ( Graph 4.5 ).

Financial Stability Report - 2017 73 Chapter IV

Box 4.1 Shock Levels for Solvency Stress Test (Balance sheet Approach)

Type of Risk Level of Shocks

Migration of loans to lower categories based on the following hypothetical transition matrix. Credit Risk (Loan Portfolio) Transition Matrix for Loans (in per cent) Pe rforming Pe rforming Migration from Substandard Doubtful Loss (Standard) (Special Mentioned)

Migration to Pe rforming (Standard) 90 Pe rforming (Special Mentioned) 85 Substandard 10 15 75 Doubtful 25 50 Loss 50 100

That is, assuming that under stressed conditions, 10 percent of the Performing loans will be downgraded to Sub-standard, 25 percent of Sub-standard loans will be downgraded to Doubtful, and 50 percent of Doubtful loans will be downgraded to Loss category.

Credit Risk Hypothetical shock of 1 percent of the total non-marketable investments (Investments) and placements (excluding investment in shares and government or central bank instruments) to be applied, assuming that 1 percent of the investment portfolio will be directly classified in the Loss category in stressed conditions.

Equity Price 50 per cent adverse movement in the equity prices in respect of a bank’s Risk own investments only.

Foreign 15 percent adverse movement applied to the net forex exposure. Exchange Risk

Interest Rate Adverse movement in the interest rates by 200 basis points. The earning Risk impact for one year time horizon is considered.

74 Financial Stability Report - 2017 Stress Testing of the Banking Sector

Name concentration stress test

4.9. Under this approach, we simulate Graph 4.5 the impact of the failure of the five largest Increase in the current NPLs before CRAR drops below corporate borrowers of each banks. As CBO requirement for foreign banks the large credits are generally covered by collaterals / bank guarantees / government guarantees, etc., to a significant extent, it 56.8 was felt that it would be sufficient to assess 27.8 27.0 24.7

16.3 the impact assuming 50 per cent provision 9.9 2.2 1.9 requirement. Further, banks assumed to BANK J BANK K BANK L BANK M BANK N BANK O BANK P BANK Q

*Execluding one foreing bank because it has zroe NPLs. maintain 50 per cent of their profits of the *Excluding one foreign bank because it has zero NPLs last four quarters and be used as a first line of defense against assumed losses.

4.10. It is observed that name concentration risk for local banks is low. All local banks are Graph 4.6 able to withstand individual group defaults Impact of default of 5 largest borrowers on local banks’ CRAR due to conservative single obligor limits.

CBOCBO requirement requirment of 12.625% of 12.625% However, under a very severe scenario of 20.00 5 largest groups defaulting simultaneously, 15.00 three local banks’ CRAR will drop below 10.00 CBO requirement of 12.625 per cent (Graph 5.00 4.6). 0.00 Bank A Bank B Bank C Bank D Bank E Bank F Bank G

Group I Fails Group II Fails Group III Fails 4.11. As for foreign banks, The CRAR of two Group IV Fails Group V Fails Top 5 Groups Fail CBO Requirement banks will drop below the CBO’s requirement if any of its five largest borrowers default. The higher name concentration for foreign banks is primarily because foreign banks are Graph 4.7 allowed to lend against the strength of the Impact of default of 5 largest borrowers on foreign capital of their parent bank despite having banks’ CRAR CBOCBO requirement requirment of 12.625% of 12.625% 35 less local capital. However, foreign banks 30 25 are guaranteed by their parent company for 20 15 any shortfall in their minimum capital levels, 10 5 hence, limiting the risk to the system from 0 -­‐5 Bank J Bank K Bank L Bank M Bank N Bank Q Bank R the failure of foreign banks caused by name -­‐10 -­‐15 concentration (Graph 4.7). -­‐20 Group I Fails Group II Fails Group III Fails Group IV Fails Group V Fails Top 5 Groups Fail CBO Requirement

Financial Stability Report - 2017 75 Chapter IV

module is used within the existing stress testing Table 4.1 framework. For the contagion stress test, it is CRAR after Inter-bank Contagion assumed that banks need to make provisions

CRAR after Cross-border against their domestic interbank exposures CRAR before Banks and Domestic Interbank to counterparty banks maintaining CRAR of Contagion Contagion 13.625 per cent or less (that is one per cent above the regulatory minimum of 12.625 per Bank A 16.90% 16.46% cent inclusive of Capital Conservation Buffer). Bank B 17.43% 17.29% The level of required provisions depends on the CRAR of the counterparty and increases Bank C 18.68% 18.29% progressively as the CRAR of counterparty Bank D 14.41% 14.08% decreases. The banks are stressed by assuming a loss of 10 per cent of their cross-border Bank E 16.11% 16.02% interbank exposure. Once banks are hit by this Bank F 13.96% 13.70% shock, the affected banks need to create new provisions for losses from this shock, which Bank G 15.04% 14.89% may also move additional banks to CRAR Bank H 27.19% 27.19% territories of higher riskiness and thus higher provisioning against their exposures. Bank I 14.16% 14.12% After this first round, a second round is run, Bank J 32.80% 32.20% again with banks creating additional provisions Bank K 27.28% 27.23% for their interbank exposures as per the new (possibly lower) CRAR of counterparty Bank L 27.06% 27.06% banks. Like before, these new provisions are Bank M 96.91% 96.77% deducted from capital and risk weighted assets, decreasing CRAR of some banks even further. Bank N 127.62% 127.62% This iterative “domino effect” is repeated till Bank O 18.63% 18.63% the new iterations do not result in additional

Bank P 14.36% 14.21% provisioning requirements for any bank. An overview of the methodology used to conduct Bank Q 23.65% 23.65% contagion stress test on interbank exposure is

Bank R 24.51% 33.58% given in (Box 4.2).

All Banks 16.8% 16.32% The results showed that, for all banks cross- border and domestic interbank contagion effect Contagion Analysis: Domestic and cross- was very minimal on their capital adequacy. border interbank markets are necessary for Overall, the interbank contagion continues not proper functioning of banking and financial to have a significant impact on the sector as a sector. However, failure of one bank in the whole, maintaining a systemic average CRAR interbank network may lead to failures in others of 16.32 per cent after fully absorbing the due to domino effect as occurred during the complete cycle of additional provisions (Table global financial crisis of 2007-09. To stress test 4.1). These results were not surprising given domestic and cross-border interbank exposures that the domestic interbank market in Oman and to capture connectivity-related risks to is not quite active and CBO has put in place the overall banking sector’s solvency, an prudent limits on overseas exposures of banks. independent domino like multi-round contagion

76 Financial Stability Report - 2017 Stress Testing of the Banking Sector

Macro Stress Testing: banks through empirical relationships between 4.12. Macro-financial stress testing has been key risk parameters [e.g., non-performing loan made a key element of systemic risk surveillance (NPL) ratio] of the banking system and relevant mechanism in Oman. Designed to focus on macroeconomic variables, such as GDP, stock systemic risk, the resilience of the Omani market, inflation and interest rate. Box 4.3 banking system to macro-economic shocks is provides the methodology of the macro stress test tested through a macro stress test framework. The framework for Oman used to estimate the default framework consists of a macro-financial model, rate over the year of 2017 and Table 4.2 shows the which estimates credit losses (i.e. default rate) for assumptions used for the explanatory variables.

Table 4.2

Assumptions/Scenarios/Projections for Macro Stress Test for 2017

Stock Change in Nominal Projected Year / Scenarios GDP Growth CPI Inflation Market GDP Growth Interest Rate Default Rate Return

Baseline Scenario 5.7% 0.0% 5.1% 1.07% 6.96% 0.43%

Moderate Scenario 3.5% -2.3% 7.1% 3.00% -30.00% 0.98%

Severe Scenario 0.7% -5.0% 10.1% 7.00% -50.00% 1.69%

4.13. The current aggregate CRAR of entire Graph 4.8 banking system would drop from 16.8 per CRAR of local banks after shocks under moderate macro scenarios cent as at December 2016 to 15.43 per cent and 14.31 per cent Under moderate and severe

CBO Requirement 12.625% 25% macro stress testing scenarios, respectively, 20% showing a comfortable level of solvency for the 15% entire banking system.

CRAR 10% 21.97% 23.21% 17.43% 16.07%

15.63% 4.14. Under the moderate macro stress test 5% 15.14% 13.67% 15.18% 12.23% 13.22% 0% scenarios, one local bank will drop slightly Bank A Bank B Bank C Bank D Bank E below the CBO regulatory capital requirement of Bank F Bank G Bank H Bank I All Banks 12.625% and under the severe macro scenarios two local banks would be below CBO’s capital requirement, however, these banks in both scenarios would maintain a CRAR of more than Graph 4.9 Basel III requirement of 10.5 per cent (Graphs CRAR for local banks after shocks under severe macro 4.8 & 4.9). scenarios 4.15. As for foreign banks, most banks can

CBO Requirement 12.625% comfortably pass the moderate assumed losses 25% without compromising the CBO required 20% capital and that is mainly due to their high level 15% of CRAR they currently maintain. Further, CRAR 10%

5% assuming more severe stress scenarios will not 14.93% 16.25% 22.24% 14.55% 20.56% 14.37% 12.65% 14.05% 12.05% 10.74% 0% really lead to solvency issues for foreign banks Bank A Bank B Bank C Bank D Bank E except for one bank for which CRAR would Bank F Bank G Bank H Bank I All Banks drop slightly below CBO capital requirement of 12.625 per cent (Graphs 4.10 & 4.11).

Financial Stability Report - 2017 77 Chapter IV

LIQUIDITY STRESS TESTING: 4.16. The liquidity stress tests carried out at CBO are aimed to assess the number of days banks would be able to withstand a run on their deposits. A reference period of thirty days is Graph 4.10 adopted for the liquidity stress testing horizon CRAR of foreign banks after shocks under moderate for all banks. Banks cannot generate new cash macro scenarios (capital and interbank markets are impaired) and

140% they first use cash, CBO balances to meet funding 120% CBO Requirement 12.625% needs, then only sell securities (Box 4.4). 100% 80% 4.17. As of December 2016, under the liquidity

CRAR 60%

40% 128.92% shock scenarios, despite the current economic 96.75% 31.31% 18.92% 17.70% 26.30% 26.41% 26.14% 13.23% 20% 13.24% condition and the low oil revenues into the 0% Omani economy, banks remain in a relatively Bank J Bank K Bank L Bank M Bank N good liquidity position vis-à-vis international Bank O Bank P Bank Q Bank R All Banks benchmarks, their positions under stressed shocks continue to display a good level of ability to face a bank run . As at end December 2016, the banking system as a whole would be able to Graph 4.11 sustain a liquidity shock for an average of 18 days CRAR of foreign banks after shocks under severe macro with cash only and a total of 20 days with cash scenarios and securities together compared 19 days and 24 days at the end of December 2015, respectively 140% (Graph 4.12). 120% 100% CBO Requirement 12.625% 80% 4.18. On individual basis, three banks can

CRAR 60% sustain sudden deposit withdrawals to 10 days, 40% 127.84% 96.62% eight banks between 15 days to 20 days and five 25.25% 16.66% 25.51% 12.03% 17.92% 30.07% 25.63% 20% 12.74% 0% banks more than 25 days. However, banks should Bank J Bank K Bank 1 L Bank M Bank N be able to survive more days since they will be Bank O Bank P Bank Q Bank R All Banks able in practice to liquidate more than 20% of their securities as assumed in the liquidity stress scenarios (Graph 4.13).

Graph 4.12 Graph 4.13 Average days of survival using cash and securities CRAR of foreign banks after shocks under moderate macro scenarios

35 30 30 -­‐ 24 25 25 1 13 19 19 19 20 2 12 20 18 18 17 18 20 20 16 5 1 2 5 5 15 15 11 5 30

Days Days 2 6

Days Days 24 10 2 22 1 10 2 17 16 16 15 15 14 5 12 10 11 1 10 10 12 7 9 8 6 5 -­‐ 0 Bank Bank 1 Bank 2 Bank 3 Bank 4 Bank 5 Bank 6 Bank 7 Bank 8 9 Bank Bank 10 Bank 11 Bank 12 Bank 13 Bank 14 Bank 15 16 All Banks Jul-­‐16 Dec-­‐15 Jan-­‐16 Feb-­‐16 Mar-­‐16 Apr-­‐16 May-­‐16 Jun-­‐16 Aug-­‐16 Sep-­‐16 Oct-­‐16 Nov-­‐16 Dec-­‐16 Local Banks Foreign Banks Local Local banks banks ForeignForeing banks banks No. of days the banks can sustain with cash and securi6es No. of days the banks can sustain with cash

78 Financial Stability Report - 2017 Stress Testing of the Banking Sector

Box 4.2 Interbank contagion effects

To stress test domestic and cross-border interbank It was assumed that the interbank exposures comprise exposures and to capture connectivity-related risks to unsecured lending and banks make provisions the overall banking sector’s solvency, an independent against interbank claims based on the CRAR of the domino like multi-round contagion module was counterparty banks. The CRAR of the counterparty introduced1 within the existing stress testing banks is thus used as a proxy for riskiness of interbank framework. The contagion module was implemented exposures. The matrix of the provisions required using a matrix of interbank exposures as of September against different levels of counterparty CRAR is 30, 2014. given in Table 8.

Despite the relatively sparse matrix of domestic The initial shock to the system comes from an interbank exposures, with conservative assumptions assumed loss of 10 per cent of cross-border interbank on provisioning of interbank loans vis-à-vis banks at exposure. Once this shock hits, the affected banks risk (i.e. banks that had low capital to risk-weighted need to create new provisions for losses from the assets ratio (CRAR), the contagion risk produced an cross-border interbank exposures. This shock may additional stress to the banking system. also move additional banks to CRAR territories of higher riskiness and thus higher provisioning against Data and Methodology: their exposures.

A matrix of gross domestic interbank claims and In the first round, all banks make provisions against cross-border gross exposures of individual banks their gross exposures to banks having CRAR of 13.625 as of September 30, 2014 were used. The matrix per cent or less as per the schedule given in Table was relatively sparse, with connectivity indicators 8. These new provisions are directly deducted from (number of existing linkages out of all possible regulatory capital and risk-weighted assets (assuming linkages) of about 5 per cent only. a 100% risk weight on these loans), leading to a new (lower) CRAR, which may move some more banks Table 8 : Provisions for Domestic Interbank Claims to higher riskiness category, necessitating higher Assumed provisioning against exposure to such banks. Thus, CRAR of Banks after Shocks a second round is run, again with banks creating Provisioning additional provisions for their interbank exposures CRAR > 13.625% 0 as per the new (lower) CRAR of counterparty banks. Like before, these new provisions are deducted from 13.625% ≥ CRAR > 12.625% 10% capital and risk weighted assets, decreasing CRAR 12.625% ≥ CRAR > 8% 50% of some banks even further, this exercise is repeated 8% ≥ CRAR > 0% 80% until no more additional provisioning is required on account of interbank exposures to bank that move to CRAR ≤ 0% 100% the higher risk (lower CRAR) categories.

1 The contagion exercise was initiated as part of Follow-up IMF Technical Mission on Stress Testing

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Box 4.3 Macro Stress Test for Oman Assumptions, Scenarios and Projections

Using macroeconomic and banking sector data, (GDPGROWTH), lending rates (NOMINALRATE), namely, annual real GDP growth, quarterly stock inflation (INFLATION), and stock market returns market prices, quarterly consumer inflation, and (STOCKMARKET) were used. Real GDP growth is quarterly nominal rates of lending rate for 1999Q2 one of the most used explanatory variables for credit – 2012Q4, a macro-credit risk model is estimated risk given its usually high (negative) correlation for projecting the default rate for Oman by a simple with credit risk indicators due to its direct effect on Ordinary Least Squares (OLS) regression model. It borrowers’ income and thus their capacity to service uses the 12-month default rate, which expresses new the debt. Some papers only consider this variable for NPLs over a horizon of one year as a percentage of satellite models, and this variable is also often used the initial stock of performing loans, as the dependent for various rules of thumb elasticities (Hardy and variable, and main macro-financial variables (GDP Schmieder 2013; Schmieder et al. 2011). Second, as growth, lending rate, inflation, and stock market of consumer price inflation, literature on stress testing index) as explanatory variables. The forecasted models usually works with ex post rather than ex ante default rate - either itself or its long-run average - can real rates (i.e. using inflation of the given quarter as be also understood as a probability of default (PD). a proxy for inflation expectations), as these seem to be more correlated with actual defaults (Buncic and Among the dependent variables, the aggregate Melecky, 2012) . It is the inflation outcome after a default rate (DFRATE), calculated as new NPLs over loan has been granted, which influences borrower’s a period of four consecutive quarters as a percentage capacity to service the loan in real terms rather of the initial stock of performing loans, is a flow inflation expectations at the moment of taking up indicator that shows what proportion of performing the loan. Third, as of the stock market returns, given loans defaulted over a period of one year, and in that the existing stress testing framework in Oman principle it is the same indicator that is used by banks assumes a stock price shock, an inclusion of this to calculate probability of default (PD). Secondly, variable in the model linking the macro-financial the use of flow indicator (default rate capturing new environment with banks’ credit risk would provide NPLs) is superior to the use of stock indicators (such additional channel through which the stock price as the NPL ratio), as the flow indicator is much more shock impacts banks (in addition to market risk). linked to provisioning (credit losses), which impacts the overall profitability of banks and ultimately The model includes a lagged dependent variable to their solvency (Hardy and Schmieder, 2013) . The prevent auto-correlated residuals, and uses robust numerator is the 4-quarter sum of new NPLs, while standard errors to take care of possible residual the denominator is the stock of performing loans autocorrelation and heteroscedasticity. The signs (calculated as a stock of all loans minus stock of of the estimated coefficients are in line with NPLs) at the end of the previous quarter. The default expectations. The coefficient for the change in GDP rate for e.g. Q1:2010 is thus a ratio of new NPLs over growth is not very significant by standard measures Q1:2010-Q4:2010 and stock of performing loans at (p-value of 30%), but it was decided to keep it there the end of Q4:2009. (in other specifications, the GDP growth is significant, but other variables not or have wrong signs). The Among the explanatory variables, real GDP growth estimated equation is as below:

DFRATE = -0.009 + 0.88*DFRATE(-1) – 0.04*D(GDPGROWTH)+0.17*NOMINALRATE (-4.22) (15.67) (-1.04) (4.41) +0.009*INFLATION-.003*STOCKMARKET (1.65) (-2.00) Parenthetic figures are t-values. Adj R sq = 0.96 DW statistic = 1.35

80 Financial Stability Report - 2017 Stress Testing of the Banking Sector

The sign for inflation is not clear ex ante. While higher points increases the default rate by less than 0.04 inflation lowers the real debt burden, suggesting a percentage points. An increase of interest rates by 1 negative sign, higher inflation – especially if not percentage points increases the default rate by 0.17 reflected in wage inflation - may also decrease the percentage points, whereas an increase of inflation real disposable income of households and make by 1 percentage points increases the default rate repayment debt more difficult, suggesting a positive by 0.009 percentage points and a decrease of stock sign. The Omani experience confirms the latter market prices by 1 percentage points increases the argument amid the food price inflation in 2008-2009. default rate by 0.003 percentage points. Using these coefficients, the default rate for December 2015 is Using the above macro-financial model’s elasticity estimated at of 1.0, 2.8, and 4.2 per cent in the three estimates for all these variables, it may be seen scenarios. that a decrease of GDP growth by 1 percentage

Box 4.4 Assumptions underlying the liquidity stress testing

Item per day

Outflow of deposits (in %)

All type of deposits

Government 1

Corporations (incl. public and financial corp.) 1

Households (incl. non-profit org.) 0.1

Outflow of interbank funding (in %)

due to banks that are not renewed 1

Off-balance sheet items

Contingent credit that is drawn (in %) 2

Decline in value of liquid securities

Securities 2

Share of interbank claims that can be used in liquid assets (%)

Demand 100

up to 1M 75

Between 1M and 3M 50

Securities

portion of long-term securities that is in trading and AFS up to 1M 20

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Financial Stability Department Central Bank of Oman