School of Social Sciences

Master of Business Administration

Postgraduate Dissertation

“Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions.”

Georgios Psimopoulos

Supervisor: Pr. Nikolaos Tsagkarakis

Athens, Greece, July 2019

© Hellenic Open University, 2019 The content of this thesis/dissertation along with its results is owned by the Hellenic Open University and his author, where each of them has the sole and exclusive right to use, reproduce, and publish it (totally or partially) for educational or research purposes, with the obligation to make reference to the thesis’s title, the author’s name and to the Hellenic Open University where the dissertation was written.

“Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions.”

Georgios Psimopoulos

Supervising Committee

Supervisor : Co-Supervisor: Pr. Nikolaos Tsagkarakis Pr. Aikaterini Lyroudi

Athens, Greece, July 2019 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

“To my wife Giota, my daughter Dioni & my son Orestis for their support and understanding”

Postgraduate Dissertation iv Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

ABSTRACT

The Dissertation investigates the macroeconomic factors that have an impact on the rising portfolio of NPEs in the Greek banks taking into account the characteristics of the Greek banking system. The analysis is based on the NPLs of the four systemic banks (Alpha Bank, Eurobank, National bank of Greece, and Piraeus Bank).

The rapid growth of NPLs and the inability of banks to quickly impair them are related the broader macroeconomic environment, including sluggish growth, high unemployment, capital controls, and limited access to financial markets. In this context, the adoption of IFRS 9 has had a major impact on the loan loss provisions of the National Bank of Greece and Piraeus Bank, a lower impact on Eurobank and no impact on Alpha Bank. NBG and Piraeus Bank have seen a huge decrease in their total assets following the IFRS 9 implementation whereas Piraeus Bank experienced an increase in loans, and NBG incurred a decrease in deposits.

The prospects for 2019 are positive. Depositors are gaining confidence in the Greek banks, access to money and capital markets is enabled and the Greek economy demonstrates signs of recovery. A strategy that is expected to significantly reduce NPEs is the transfer of these loans from the banks’ balance sheets to Special Purpose Vehicles (SPVs), In doing so, banks’ portfolios will improve and the Greek banks will be able to maintain high capital adequacy.

Keywords : loan loss, impairment, non-performing loans, non-performing exposures, Greek banks, IFRS 9

Postgraduate Dissertation v Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

ΠΕΡΙΛΗΨΗ

Η Διατριβή διερευνά τους μακροοικονομικούς παράγοντες που επηρεάζουν το αυξανόμενο χαρτοφυλάκιο των μη εξυπηρετούμενων ανοιγμάτων ( ΝΡΕ s) στις ελληνικές τράπεζες , λαμβάνοντας υπόψη τα χαρακτηριστικά του ελληνικού τραπεζικού συστήματος . Η ανάλυση βασίζεται στα μη εξυπηρετούμενα δάνεια των τεσσάρων συστημικών τραπεζών (Alpha Bank, Eurobank, Εθνική Τράπεζα της Ελλάδος και Τράπεζα Πειραιώς ). Η ταχεία ανάπτυξη των μη εξυπηρετούμενων δανείων και η αδυναμία των τραπεζών να τα απομειώσουν συνδέονται με το ευρύτερο μακροοικονομικό περιβάλλον , συμπεριλαμβανομένης της γενικότερης οικονομικής ύφεσης , της υψηλής ανεργίας , των ελέγχων κεφαλαίου και της περιορισμένης πρόσβασης στις χρηματοπιστωτικές αγορές . Στο πλαίσιο αυτό , η εφαρμογή του ΔΠΧΑ 9 είχε σημαντικό αντίκτυπο στις προβλέψεις για ζημιές δανείων της Εθνικής Τράπεζας της Ελλάδος και της Τράπεζας Πειραιώς , μικρότερο αντίκτυπο στην Eurobank και καμία ουσιαστική επίδραση στην Alpha Bank. Η Εθνική Τράπεζα και η Τράπεζα Πειραιώς σημείωσαν τεράστια μείωση του συνολικού ενεργητικού τους μετά την εφαρμογή του ΔΠΧΑ 9, ενώ η Τράπεζα Πειραιώς σημείωσε αύξηση των δανείων και η Εθνική Τράπεζα σημείωσε μείωση στις καταθέσεις . Οι προοπτικές για το 2019 είναι θετικές . Οι καταθέτες κερδίζουν εμπιστοσύνη στις ελληνικές τράπεζες , η πρόσβαση στην αγορά χρήματος και κεφαλαίων είναι δυνατή και η ελληνική οικονομία παρουσιάζει σημάδια ανάκαμψης . Μία στρατηγική που αναμένεται να μειώσει σημαντικά τα NPEs είναι η μεταφορά αυτών των δανείων από τους ισολογισμούς των τραπεζών σε Οχήματα ειδικού σκοπού (SPVs). Με τον τρόπο αυτό θα βελτιωθούν τα χαρτοφυλάκια των τραπεζών και οι ελληνικές τράπεζες θα μπορέσουν να διατηρήσουν υψηλή κεφαλαιακή επάρκεια .

Λέξεις -κλειδιά : ζημία δανείων , απομείωση , μη εξυπηρετούμενα δάνεια , μη εξυπηρετούμενα ανοίγματα , ελληνικές τράπεζες , ΔΠΧΑ 9

Postgraduate Dissertation vi Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Abstract ...... v Περίληψη ...... vi Table of Contents ...... vii List of Figures ...... ix List of Tables...... xi 1. Introduction ...... 1 2. Literature Review ...... 3 2.1 Global financial crisis and the rise of NPLs ...... 3 2.2 The relationship between NPLs and credit risk ...... 5 2.3 Financial crisis and the rise of NPLs in the Asian economies ...... 6 2.4 Financial crisis and the rise of NPLs in the euro area and Greece ...... 7 3. Overview of the Greek banking system ...... 10 3.1 Introduction to the banking system ...... 10 3.2 The Greek banking system ...... 13 3.2.1 Alpha Bank ...... 15 3.2.2 Eurobank ...... 16 3.2.3 National Bank of Greece ...... 21 3.2.4 Piraeus Bank ...... 23 3.2.5 Comparative analysis between the four systemic banks ...... 25 4. Nonperforming exposures (NPEs)...... 29 4.1 Defining NPEs ...... 29 4.2 Macroeconomic factors that affect NPEs ...... 31 4.2.1 GDP growth ...... 31 4.2.2 Unemployment ...... 32 4.2.3 Inflation ...... 33 4.3 Macroeconomic factors and NPEs during the 2008 financial crisis ...... 34 4.4 Forbearance and NPEs ...... 39 4.5 Provisions for impaired loans and earnings management ...... 40 5. The Introduction of IFRS 9 ...... 43 5.1 Introducing IFRS 9 ...... 43 5.2 Main characteristics ...... 43

Postgraduate Dissertation vii Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

5.2.1 Initial measurement of financial assets ...... 44 5.2.2 Financial liabilities measurement ...... 47 5.3 Provisions determination before and after IFRS 9 ...... 48 5.3.1 Expected credit losses (ECL) model ...... 50 6. Macroeconomic Determinants of NPEs in the Greek banks ...... 52 6.1 Gross Domestic Product (GDP) ...... 52 6.2 Consumer spending ...... 53 6.3 Government spending ...... 54 6.4 Unemployment rate and inflation rate ...... 55 6.5 Interest rates ...... 57 7. Impact of IFRS 9 and Strategies to reduce NPEs ...... 60 7.1 The impact of IFRS 9 on the Greek NPEs ...... 60 7.1.1 Alpha Bank ...... 60 7.1.2 Eurobank ...... 64 7.1.3 National Bank of Greece ...... 67 7.1.4 Piraeus Bank ...... 71 7.2 Strategies to reduce NPEs ...... 75 8. Conclusions and Recommendations ...... 77 8.1 General conclusions ...... 77 8.2 Suggestions and recommendations ...... 79 References ...... 80 Appendix ...... 87

Postgraduate Dissertation viii Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Figure 2-1: Countries with NPL ratio above 10% (2014) ...... 3 Figure 2-2: Non-performing loans in the euro area (2018) ...... 8 Figure 3-1 Number of EU-28 credit institutions (2008-2017) ...... 11 Figure 3-2 Number of EU-28 branches (2007-2017) ...... 12 Figure 3-3 Number of bank staff in the EU banks (2007-2017) ...... 12 Figure 3-4 Evolution of the Greek banking system (2009-2016) ...... 15 Figure 3-5 Comparing LTD ratios ...... 25 Figure 3-6 Comparing NIM ratios ...... 26 Figure 3-7 Comparing Net profit ...... 26 Figure 3-8 Loan Loss Provisions (2011-2018) ...... 27 Figure 3-9 Provisions/Loans ratio (2011-2018) ...... 28 Figure 3-10 NPL ratio (2011- 2018) ...... 28 Figure 4-1 EU NPLs (% global total) (2010-2017) ...... 35 Figure 4-2 EU NPLs (% total gross loans) (2008-2017) ...... 35 Figure 4-3 EU NPLs and GDP growth (2008-2017) ...... 37 Figure 4-4 EU NPLs and unemployment rate (2008-2017) ...... 38 Figure 4-5 EU NPLs and inflation rate (2008-2017) ...... 38 Figure 5-1 Summary of classification and measurement model for financial assets .. 46 Figure 5-2 IFRS 9 three-stage ECL model for impairment of financial assets ...... 49 Figure 5-3 Impact of a significant increase in credit risk ...... 51 Figure 6-1 Greece NPLs and GDP growth (2008-2017) ...... 53 Figure 6-2 Greece NPLs and consumer spending (% GDP) (2008-2017) ...... 54 Figure 6-3 Greece NPLs and government spending (% GDP) (2008-2017) ...... 55 Figure 6-4 Greece NPLs and unemployment rate (2008-2017) ...... 56 Figure 6-5 Greece NPLs and inflation rate (2008-2017) ...... 56 Figure 6-6 Greece NPLs and interest rates (2008-2017) ...... 57 Figure 7-1 Alpha Bank loans and deposits (2017 & 2018) ...... 62 Figure 7-2 Alpha Bank demand for loans and deposits (2017 & 2018) ...... 63 Figure 7-3 Alpha Bank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) ...... 63 Figure 7-4 Eurobank loans and deposits (2017 & 2018) ...... 66 Figure 7-5 Eurobank demand for loans and deposits (2017 & 2018) ...... 66

Postgraduate Dissertation ix Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Figure 7-6 Eurobank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) ...... 67 Figure 7-7 NBG loans and deposits (2017 & 2018) ...... 69 Figure 7-8 NBG demand for loans and deposits (2017 & 2018) ...... 70 Figure 7-9 NBG Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) ...... 70 Figure 7-10 Piraeus Bank loans and deposits (2017 & 2018) ...... 73 Figure 7-11 Piraeus Bank demand for loans and deposits (2017 & 2018) ...... 73 Figure 7-12 Piraeus Bank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) ...... 74

Postgraduate Dissertation x Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 3-1 Number of branches of Greek credit institutions (2009) ...... 13 Table 3-2 Number of branches of Greek credit institutions (2016) ...... 14 Table 3-3 Alpha Bank Basic Figures (2008-2017) ...... 18 Table 3-4 Alpha Bank Basic ratios (2008-2017) ...... 18 Table 3-5 Eurobank Basic Figures (2008-2017) ...... 19 Table 3-6 Eurobank Basic ratios (2008-2017) ...... 19 Table 3-7 National Bank of Greece Basic Figures (2008-2017) ...... 22 Table 3-8 National Bank of Greece Basic ratios (2008-2017) ...... 22 Table 3-9 Piraeus Bank of Greece Basic Figures (2008-2017) ...... 24 Table 3-10 Piraeus Bank of Greece Basic ratios (2008-2017) ...... 24 Table 4-1 Macroeconomic factors and NPLs in the EU (2008-2017) ...... 36 Table 4-2 Forbearance measures for NPEs ...... 40 Table 5-1 IFRS 9 and IAS 39 classification and measurement categories ...... 44 Table 5-2 Accounting for asset reclassifications ...... 45 Table 5-3 IFRS 9 business model classifications ...... 46 Table 5-4 Fair value designation options under IFRS 9 ...... 47 Table 5-5 Differences between IAS 39 and IFRS 9 ...... 48 Table 6-1 Macroeconomic factors and NPLs in Greece (2008-2017) ...... 58 Table 7-1 Alpha Bank recalculation of basic figures under IFRS 9 ...... 61 Table 7-2 Alpha Bank recalculation of ratios under IFRS 9 ...... 62 Table 7-3 Eurobank recalculation of basic figures under IFRS 9 ...... 64 Table 7-4 Eurobank recalculation of ratios under IFRS 9 ...... 65 Table 7-5 NBG recalculation of basic figures under IFRS 9 ...... 68 Table 7-6 National Bank of Greece recalculation of ratios under IFRS 9 ...... 68 Table 7-7 Piraeus Bank recalculation of basic figures under IFRS 9 ...... 71 Table 7-8 Piraeus Bank recalculation of ratios under IFRS 9 ...... 72 Table 7-9 Summary of IFRS 9 impact on basic figures in four banks ...... 74

Postgraduate Dissertation xi Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

1.

The banking sector is the backbone of a country's financial system and a key factor in the development of the national economy. In fact, a country cannot have a developed economy without a developed banking system, and a healthy banking system cannot exist if the country's economy does not rely on solid foundations. The recent financial crisis begun from the US banking sector and soon turned into a global financial crisis. In the case of the Greek banking system, the opposite was the case as the Greek banks were healthy before the crisis, but the country’s debt crisis has turned into a banking crisis, thereby compromising the growth of the Greek banks.

The worsening quality of the banks’ loan portfolios is the main root of complications in the banking system in the developed economies. Certainly, the increase in loan defaults highlights the relationship between macroeconomic and financial shocks and the relationship between the friction in the credit market and the risk of financial instability. In this context, Non- performing exposures (NPEs) and non-performing loans (NPLs) have attracted a lot of attention in recent decades. Demirguc-Kunt (1989) refers to the quality of asset considering as an indicator of bank insolvency and failure, whereas Richard (2011) notes that NPLs in commercial banks in developing economies can determine the prospect of a bank failures mainly because the funds are used for different purposes than the ones agreed between the bank and the loan holder. Today, banks all over the world, and especially in the European Union, maintain a high level of non-performing loans, which compromises their liquidity and solvency and may even lead to bank failure or economic stagnation (Messai and Jouini, 2013). Empirical evidence from the Italian banks for the period 2011-2014 shows NPLs were more than €340 billion at the end of the third quarter of 2015 (18.7% of total loans) of which approximately €273 billion were business loans. Also, the recovery rate for liquidations was about 40% whereas the management of NPLs absorbed 2.8% of banks’ operating costs (Carpinelli et.al., 2017). Research on banking crises in 14 OECD countries, Karim et.al. (2013) determine that a significant cause is the banks’ capital and liquidity ratios as well as their NPLs. Schoenmaker and Véron (2016) investigate the banking sector in Austria, Belgium, France, Germany, Greece, Italy, The Netherlands, Portugal, and Spain and find that it is not heterogeneous in terms of bank size, governance, and ownership, but it also presents

Postgraduate Dissertation 1 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” substantial variations in bank strength, which explains the heterogeneity in non-performing loan between different EU member states.

Non-performing exposures (NPEs) are increasingly affecting the banking system through the provisions that strongly distress their profit and loss (P&L) statements. The purpose of the Dissertation is to investigate the macroeconomic factors behind the NPEs increase in recent years by considering the characteristics of the Greek banking system and its systemic banks. In this context, the research objectives are: First, to present the main characteristics of the Greek systemic banks' NPEs. Second, to recognize the macroeconomic factors that contribute to the NPEs increase in recent years. To define and if possible, assess the impact of the new accounting standard IFRS 9. Third, to present the measures that the Greek systemic banks have adopted to reduce their NPEs. Fourth, to suggest strategies that may lower NPEs taking into consideration the IFRS 9 impact.

The rest of the Thesis is organized as follows: Chapter 2, presents the related literature review. Chapter 3 describes the Greek banking system and presents a comparative analysis of the four systemic banks in the sample. Chapter 4 analyses the macroeconomic factors that affect NPEs, provides several definitions of NPEs and explains how provisions for impaired loans are related to earnings management. Chapter 5, introduces the reader to the IFRS 9, presenting its main characteristics and explaining how provisions are determined before and after its implementation. Chapter 6 analyses the key determinants of NPEs. Chapter 7 suggests strategies to reduce NPEs. Chapter 8 summarizes the conclusions of the Dissertation and provides suggestions for further research.

Postgraduate Dissertation 2 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

2.

2.1 Global financial crisis and the rise of NPLs

The recent financial crisis has caused a surge in non-performing loans in most nations. An increasing share of NPLs in the loan portfolio of banks implies a higher risk affecting both their liquidity and profitability while indicating a worsening balance sheet. According to Balgova et.al. (2016), the global financial crisis has further elevated the problem of NPLs as in 2014, 33 countries had more than 10% in impaired loans whereas the NPL ratio was higher than 15% in 20 of them. What is even more interesting is that some of the worst cases of NPLs are noted in advanced economies: 34% in Greece, 21% in Ireland, and 17% in Italy re NPLs Also, in countries outside the EU were also affected – 22% in Albania and in Serbia, 19% in Ukraine and 16.5% in Montenegro. Finally, on the top of the list is Cyprus with 45% and San Marino with 43% (Figure 2-1).

Countries With NPL Ratio Above 10% (2014) 50,0% 45,0% 40,0% 45,0%

35,0% 43,0% 30,0%

25,0% 34,0% 20,0% 15,0% 22,0% 22,0% 21,0%

10,0% 19,0% 17,0% 16,5% 5,0% 0,0% Italy Serbia Cyprus Tunisia Ghana Greece FYROM Ireland Croatia Burundi Albania Senegal Ukraine Slovenia Djibouti Bulgaria Pakistan Hungary Portugal Grenada Romania Moldova Maldives Tajikistan St. Vincent St. Azerbaijan SanMarino Mauritania Kazakhstan Sierra Leone Sierra Montenegro Yemen, Rep. Yemen,

Bosnia & Herzegovina & Bosnia Figure 2-1: Countries with NPL ratio above 10% (2014) Source: Balgova et.al. (2016)

Postgraduate Dissertation 3 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Ghosh (2015) claims that since the onset of the crisis, non-performing loans have been a constant headache for the regulators and the banks because they are deemed as responsible for many bank failures. In the US, the rising defaulting rate of loans and mortgage foreclosures along with a concurrent rise in NPLs highlights the links between regional and national macroeconomic shocks and the vulnerability of the banking sector. Unlike other industries, the banking sector suffers from the contagion effect, which causes a chain reaction following the failure of one bank to the entire sector. As a result, the stability of the banking system is compromised while the contagion can be spread on a global level. Beck et.al. (2013) use data from 75 countries between 2002-2012 and find that GDP growth, interest lending rate, exchange rates, and share prices are the key determinants of NPL increase. Saba et. al. (2012) investigate the US banking sector between 1985 and 2010 and conclude GDP per capita, inflation, and total loans have a relative impact on NPL ratio, but they are not strongly correlated. The problem with the sharp increase in the NPLs is the uncontrolled lending without abiding by the creditworthiness criteria, especially when the economy is booming. A research on the advanced economies evidences a link between NPLs and macroeconomic performance: a sharp increase in NPL causes a crippling macroeconomic performance in the short-term (Nkusu, 2011). Klein (2013) examines non-performing loans in Central, Eastern and Southeastern Europe (CESSE) during the period 1998 to 2011 and concludes that the level of impaired loans can be attributed to macroeconomic factors, including the unemployment rate, the exchange rate and inflation, which all lead to an increase in NPLs as opposed to GDP growth, which leads to lower levels of non-performing loans. He further concludes that a healthy and sustainable growth cannot be achieved without a healthy and robust banking system. In the long-term, the increase in the NPLs causes a decline in the GDP growth, and a higher unemployment and inflation. According to a dynamic panel for the period 1995–2008 on a sample of 80 banks in the GCC region (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates), the NPL ratio is positively correlated to economic growth and negatively correlated to interest rates and risk aversion. The findings suggest that the cumulative effect of macroeconomic shocks in concert with bank-specific factors such as risk-taking and efficiency can determine the level s of NPLs (Espinoza and Prasad, 2010).

Postgraduate Dissertation 4 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

2.2 The relationship between NPLs and credit risk

The credit risk is a major challenge in commercial banking, which arises as a result of impaired loans. The decisions of financing a loan applicant should be accompanied by the use of robust credit risk assessment models so that debtors can estimate the probability of the default for the potential borrower (Mileris, 2012). Following the years of the financial crisis, the credit quality of loan portfolios in most European countries worsened mainly as a result of the economic recession. Although loan performance is strongly related to the economic cycle, the decline of loan quality was not the same in all countries. For example, countries on the periphery of the eurozone (Cyprus, Greece, Italy, and Portugal) are still experiencing high levels of non-performing loans in concert with banking system distress and government- funded bank recapitalizations (Charalambakis et.al., 2017).

Cucinelli (2015) seeks to explain bank lending behavior during the financial crisis, and especially if an increasing credit risk led banks to reduce their lending activity. She also investigates whether there are any differences in the lending behavior between cooperative and commercial banks in Italy for the period 2007-2013. Her conclusions suggest that credit risk has a negative effect on bank lending behavior as banks are more reluctant to loan money to riskier borrowers, especially as the NPL ratio increases. According to Accornero et al. (2017), banks with higher NPL ratios do not lower credit supply more than banks with lower NPLs. Also, exogenous increases in NPLs are inversely related to bank lending.

By investigating the behavior of sovereign ratings and macroeconomic determinants, such as GDP growth, debt-to-GDP ratio, investment-to-GDP ratio and fiscal balance-to-GDP ratio, Boumparis et.al. (2019) find a strong link between sovereign and banking credit risk which both affect non-performing loans. Ekanayake and Azeez (2015) investigate the determinant factors of credit risk using NPLs on a sample of 9 commercial banks in Sri Lanka from 1999 to 2012 and assert that the increase of NPLs can be explained by macroeconomic factors, primarily GDP growth and inflation and bank specific factors such as bank efficiency, bank size, and loan to asset ratio. Evidence from the Brazilian sector shows an inverse relationship between credit quality, non-performing loans, and GDP growth (Vazquez et al., 2012). Further, evidence from the Bulgarian banking system for the period 2001– 2010 uses non- performing loans to assess credit risk. The authors identify spillover effects from the Greek crisis due to the strong presence of Greek banks in Bulgaria. Also, the credit risk determinants

Postgraduate Dissertation 5 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” of Bulgarian banks are interrelated with macroeconomic and industry-specific factors, but also exogenous factors such as the Greek debt crisis (Nikolaidou and Vogiazas, 2014). Gila- Gourgoura and Nikolaidou (2017) analyze the credit risk determinants in the Spanish banking system by using quarterly data from the Central Bank of Spain and the European Central Bank. Their findings suggest that macroeconomic variables, bank-specific factors, and interest rates determine the level of NPLs in the Spanish banks both in the short and the long-term.

2.3 Financial crisis and the rise of NPLs in the Asian economies

Evidence from China shows that the country has had a long-standing problem with NPLs, which practically impeded the development of domestic banks. This forced the Chinese regulatory authorities to provide substantial capital to the banking sectors and scrutinize the non-performing loans since 2003. According to Suzuki and Miah (2017) the extreme accumulation of NPLs in China can be explained by the failure to address the NPL crisis in the form financial system. This caused an economic slowdown with an impact on the performance of Chinese banks. Using a sample of Chinese commercial banks between 2007 and 2014, Guan et. al. (2017) find that the carbon intensity of loans (CIL) is strongly and positively related to NPLs because CIL is a major indicator of bank green credit policy. Zhang et.al. (2016) report that the increase in the NPL ratio of the Chinese banks (commercial, state- owned, and joint stock) has increased the risk in lending and has further deteriorated the quality of loans as well as the stability of the financial system.

Evidence from Japan shows that NPLs are mainly responsible for the slowdown of the Japanese economy and ongoing stagnation. This is because non-performing loans are basically a liability that needs to be bailed out by the government. The delay of the Japanese government to provide adequate capital towards the stabilization of the economy led to a failing banking system and economic slowdown. Hence, Barseghyan (2010) argues that when the government provides deposit guarantees to the banks, the increase of NPLs in concert with a delay in a government bailout lead to a constant decline in aggregate economic activity. Evidence from South Asia (Bangladesh, India, Nepal, and Pakistan) between 1997 and 2012 shows that bank size, concentration ratio, GDP growth, and inflation are factors that have a major impact on non-performing loans (Islam and Nishiyama, 2017), whereas evidence from Indonesia, Malaysia, Philippines Thailand, and Singapore between 1999 and 2014 finds that

Postgraduate Dissertation 6 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” real interest rate, inflation rate, and money supply (M2) have a positive relationship with non- performing loans (Loo et.al., 2017). Chavan and Gambacorta (2016) investigate the NPLs in the Indian banking sector and reveal that 1% in loan growth is related to a 4.3% increase in the NPL ratio, especially during expansionary phases. Also, NPL ratios of Indian banks are sensitive to interest rate changes and economic growth.

Macit (2017) investigates how NPLs surged between 2005 and 2010 in the Turkish banking sector along with the impact of the macroeconomic determinants. By taking a sample of the 15 largest Turkish commercial banks based on their share in total loans, the author concludes that banks with higher equity to total assets ratio and a higher net interest margin have a higher NPL ratio. In contrast, when the net loans to total assets ratio improves, the NPL ratio decreases. Also, public banks and foreign banks have a higher NPL ratio. A research on 20 Turkish banks between 2006 and 2012 concludes that bank solvency, bank profitability, bank credit quality, and bank product diversification, as well as economic growth and the financial crisis are the key determinants of NPLs (Isik and Bolat, 2016).

2.4 Financial crisis and the rise of NPLs in the euro area and Greece

During the financial crisis, bank profitability has been in the microscope of regulators and policymakers in their effort to increase the capital adequacy of the European banks. In fact, the recovery of the eurozone is subject to the successful management of over 1 trillion NPLs, mostly concentrated in the peripheral economies. Hence, there is a strong need to implement a more radical strategy towards resolving NPLs than simply enhancing supervisory measures and national regulatory frameworks (Avgouleas and Goodhart, 2017). Evidence from 9 countries of the Euro area between 2006 and 2013 finds that following high credit growth and high leverage strategies, the European banks have focused on higher returns through the reduction of their NPL portfolio (Rossi et.al., 2018). Evidence from Italian banks holds that macroeconomic and bank-specific factors affect NPLs, including quality and risk attitude, moral hazard, and lending policy (Milani, 2017), whereas a research on a sample of 85 banks from Italy, Greece and Spain between 2004 and 2008 determines that GDP growth rate, real interest rate, and unemployment rate can strongly affect NPLs (Messai and Jouini, 2013).

Between June 2016 and June 2018, non-performing loans in the euro area ranged between 1.1% and 44.8%. The largest stock of NPLs held by European banks can be seen in Greece

Postgraduate Dissertation 7 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” and Cyprus, which both have significantly higher NPL ratios than all other EU countries and the EU average (Figure 2-2).

Non-performing loans in the euro area (2018)

50,0% 45,0% 40,0% 35,0% 30,0% 25,0% 20,0% 15,0% 10,0% 5,0% 0,0% EU Italy Spain Malta Latvia France Cyprus Poland Ireland Greece Austria Croatia Finland Estonia Norway Sweden Belgium Bulgaria Slovakia Slovenia Hungary Portugal Denmark Germany Lithuania Netherlands Luxembourg Czech Republic United Kingdom

Jun-16 Jun-17 Jun-18

Figure 2-2: Non-performing loans in the euro area (2018) Source: Magnus et.al. (2018)

Greece is the economy that has been mostly affected by the crisis. Following a series of domestic and international factors, the Greek economy sunk into recession with a direct impact on the Greek banking system. Konstantakis et.al. (2016) try to explain the causal factors of NPLs in the Greek banking sector between 2001 and 2015 and conclude that both macroeconomic and financial factors are responsible for the surge of the Greek NPLs while the rising percentage of the NPLs is associated with Greek bank failures. Anastasiou et. al. (2019) study the causes of NPLs in the euro area between 2003 and 2016 on a quarterly basis and conclude that NPLs have followed an upward trend in the peripheral economics after 2008 (Greece, Spain, Italy, Ireland) mostly as a result of the worsening macroeconomic conditions. The results prove that the periphery of the euro area have been mostly affected by the crisis and is certainly more vulnerable than the other European economies. Louzis et al. (2012) consider the determinants of NPLs by investigating the Greek banking system and assessing nine Greek banks between 2003 and 2009. Their results show that the determinant factors vary based on the type of the NPL. For example, consumer loans are more sensitive to

Postgraduate Dissertation 8 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” changes in lending rates and the GDP growth whereas mortgages are less affected by macroeconomic factors. Chalkiadis (2019) investigates the strategies for the NPLs management and the impact of IFRS 9 on NPLs on the four systemic Greek banks and concludes that IFRS 9 has a considerable impact on the loan loss provisions and capital adequacy.

Postgraduate Dissertation 9 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

3.

3.1 Introduction to the banking system

The banking system includes organizations that act as intermediaries between depositors and borrowers, thereby ensuring the liquidity and capital adequacy of the system and contributing to the healthiness of the economy. Its effectiveness depends on a credible institutional framework, which regulates the functioning of society in economic terms while supporting development processes. The banking system consists of two types of banks, the Central Bank - the coordinator of domestic banks regarding their policies – and the commercial banks, which are regulated and controlled by the Central Bank. The Central Bank of any economy determines the lending rates, controls the domestic money supply, issues bonds, and plays a central role in the course of the fiscal policy so as to guarantee that the government will be able to meet its obligations in the case of fiscal deficit. On the other hand, commercial banks seek to meet their foreign exchange needs of their customers, manage their funds to maintain capital adequacy and act as financial intermediaries between depositors and borrowers. Also, they are required by the Central Bank to maintain a percentage of deposits available in cash so as to remain liquid and be able to meet their payments (BIS, 2010).

The European Union has set up the Banking Union with the main objectives of ensuring that European banks remain strong enough to cope with the financial crisis, prevent situations where European taxpayers' money is used to rescue unsustainable banks, reduce fragmentation the market by harmonizing financial sector rules, and enhancing fiscal stability in the euro area and the European Union as a whole. In essence, the banking system is the main banking supervision and consolidation system, which guarantees the credibility of the banking sector in the euro area and the EU, ensuring that the consolidation of troubled banks is done with minimal impact on the real economy. The members of the Banking Union are the states belonging to the eurozone and non-euro area member states who wish to participate (European Council, 2019). Between 2008 and 2017, the number of EU-28 credit institutions decreased by 30.8%, from 7,676 to 5,308 while their branches decreased by 0.9% from 565 to 560, although in 2012 the decrease was 7.6% and in 2014 6.5%. This downward trend

Postgraduate Dissertation 10 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” includes factors such as mergers in the banking sector with a view to enhancing profitability (Figure 3-1).

Number of EU-28 Credit Institutions (2008-2017) 9000

8000

7000

6000

5000 7676 7520 7315 4000 7162 6979 6832 6317 6109 5681 3000 5308

2000

1000 565 559 540 546 547 535 560 0 522 530 528 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Branches Credit institutions

Figure 3-1 Number of EU-28 credit institutions (2008-2017) Source: EBF (2018)

The downward trend is also seen in the number of bank branches that decreased by 21.4% from 233,333 in 2007 to 183,418 in 2017 (Figure 3-2).

Postgraduate Dissertation 11 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Number of EU-28 bank branches(2007-2017) 250000

200000

150000

233333 237702 232588 229239 223136 217831 211084 100000 203564 198391 189270 183418

50000

0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Branches

Figure 3-2 Number of EU-28 branches (2007-2017) Source: EBF (2018)

Finally, the downsizing of the European banks led to an 11.4% decrease in the bank staff from 3,103,000 people in 2009 to 2,740,000 people in 2017 (Figure 3-3).

Number of bank staff in the EU banks (2007-2017) 3200000

3100000

3000000

2900000

2800000 3103000 3100000 3080000 2980000 2700000 2920000 2860000 2830000 2780000 2600000 2740000

2500000 2009 2010 2011 2012 2013 2014 2015 2016 2017

Bank staff

Figure 3-3 Number of bank staff in the EU banks (2007-2017) Source: EBF (2018)

Postgraduate Dissertation 12 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

3.2 The Greek banking system

The Greek banking system is mainly characterized by the existence of bank Groups, which organize their financial interests by incorporating companies that support the operations of the mother company. Subsidiaries are mainly companies that operate in the financial sector, such as insurance companies and mutual fund management companies as well as public limited liability companies and companies operating in the industrial, commercial, hotel, and technology sector. Because of the specific structure of the Greek banking system, bank Groups maintain economic power and can influence the Greek economy.

The evolution of the Greek banking sector over the last decade includes issues such as capital structure, lending portfolio, and risk management. As the Greek banks have been strongly affected by the global financial crisis, their problems were a catalyst for major developments in the Greek economy. The structure, organization, and operation of the Greek banking system has been influenced and identified in recent years by a number of factors concerning the regulatory and supervisory framework of the system, the economic and administrative barriers to entry, mergers and acquisitions that have taken place over the past twenty years, and the presence of foreign banks in Greece. Ensuring higher capital adequacy and better efficiency has forced the industry to consolidate its financial institutions and proceed with restructuring. The supervisory role of the Bank of Greece, the role of the bodies representing the social partners in the system and the role of the complementary organizations involved contribute to the strengthening of the banking system as well as to the treatment of endemic asymmetric information (Economic Chamber of Greece, 2010).

Following the financial crisis, the Greek banks had to be restructured. As seen in Table 3-1, in 2009, there were 4,163 credit institutions out of which 3,634 (87.3%) were Greek credit institutions, employing 57,737 people out of a total of 66.969 people (86.2%).

Table 3-1 Number of branches of Greek credit institutions (2009)

Number of branches Rest of Bank Attica Thessaloniki Total Greece Staff Total 1,687 407 2,069 4,163 66,969 A. Credit Institutions 1,677 405 1,839 3,921 63,342 Β. Banking Associations 7 1 169 177 1,293 C. Bank of Greece 3 1 61 65 2,334

Postgraduate Dissertation 13 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Α1. Greek Credit Institutions 1,503 381 1,750 3,634 57,737 National Bank of Greece 212 52 311 575 12,534 Alpha Bank 190 49 192 431 7,501 Commercial Bank of Greece 144 36 188 368 5,206 EFG Eurobank - Ergasias 207 49 176 432 7,573 Piraeus Bank 152 44 161 357 5,049 General Bank of Greece 60 16 63 139 1,752 Marfin - Εgnatia Bank 93 22 71 186 2,753 Agricultural Bank of Greece 115 34 333 482 6,488 Attica Bank 41 10 29 80 1,134 Millennium Bank 92 26 45 163 1,494 Proton Bank 22 2 8 32 533 Probank 59 6 37 102 1,100 Panhellenic Bank 11 6 14 31 145 First Business Bank 10 2 7 19 279 Aspis Bank 34 8 31 73 1,020 Post Bank 57 17 80 154 2,419 Deposits & Loans Fund 2 1 1 4 474 Investment Bank of Greece 1 1 3 5 243 Aegean Baltic Bank 1 1 40

Source: HBA (2009)

In 2012 and 2013, several mergers and acquisitions in the Greek banking sector took place while the ongoing crisis led many foreign banks to cease their operations in Greece due to the higher default risk of the Greek economy. As a result, in 2016, 2,210 credit institutions employed 41,211 people. Of these 2,206 branches were Greek banks (99.8%) employing 41,119 people (99.8%). Compared to 2009, the number of branches decreased by 39.3% (from 3,634 to 2,210) and the number of bank staff decreased by 28.8% (from 57,737 to 41,119) (Table 3-2).

Table 3-2 Number of branches of Greek credit institutions (2016)

Number of Branches Rest of Bank Attica Thessaloniki Total Greece staff Total 886 223 1,101 2,210 41,211 Greek institutions 882 223 1,101 2,206 41,119 Piraeus Bank 218 64 380 662 13,192 National Bank of Greece 195 46 268 509 9,935 Alpha Bank 231 51 235 517 8,543 EFG Eurobank - Ergasias 194 54 190 438 8,153

Postgraduate Dissertation 14 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Attica Bank 30 7 28 65 782 HSBC Bank 14 1 - 15 403 Citibank - - - - 111 Foreign institutions 4 - - 4 92 Bank of America Merrill 1 1 12 Lynch BNP Paribas Securities 1 1 27

Deutsche Bank 1 1 10

Royal Bank of Scotland 19

Unicredit Bank 1 1 24

Source: HBA (2016)

Between 2009 and 2016, the number of branches operating in Greece decreased by 46.9% from 4,163 branches to 2,210 branches with a consequent decrease of 38.5% in the number of bank staff, from 66,969 people to 41,211 people (Figure 3-4).

Evolution Of The Greek Banking System (2009-2016) 80000

70000

60000

50000

40000 66969 59967 30000 56611 54745 50167 44332 44402 41211 20000

10000

0 4163 3743 3575 3453 2886 2562 2418 2210 2009 2010 2011 2012 2013 2014 2015 2016 Branches Bank staff

Figure 3-4 Evolution of the Greek banking system (2009-2016) Source: HBA (2016)

3.2.1 Alpha Bank

Between 2008 and 2018, Alpha Bank's total assets decreased by 6.5% from €65.27 billion to € 61.00 billion. A decrease of 13.8% is also observed in total liabilities from €61.33 billion to €52.86 billion, while an increase of 106.6% is noted in total equity from €3.94 billion to €8.14

Postgraduate Dissertation 15 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” billion. Loans decreased by 20.7%, from €50.71 billion to €40.23 billion with a corresponding decrease of 9.0% in deposits from €42.55 billion to €38.73 billion. As a result, a large increase of 219.5% is seen in loan losses provisions from €541.75 million to €1.73 billion. The bank’s net interest income decreased by 2.4% from €1.80 billion to €1.76 billion, operating revenue increased by 11.4% from €2.34 billion to €2.60 billion, and operating expenses decreased by 1.4% from €1.78 billion to €1.16 billion. Finally, net profit was down by 89.7% from €513.45 million to €53.0 million (Table 3-3).

Over the same period, LTD ratio decreased by 15.3% from 119.17% to 103.86% following the decrease in deposits. The decrease in net profit generated a decreased ROA, down by 0.7% from 0.79% to 0.09% and a decreased ROE, down by 12.4% from 13.03% to 0.65%, despite the huge increase in equity. Net interest margin increased by 0.1% from 2.76% to 2.88% due to the increase in net interest income and the decrease in total assets. Equity over total assets increased by 7.3% from 6.04% to 13.35% and equity over total liabilities increased by 9.0% from 6.43% to 15.40% due to the increase in equity. Finally, provisions over loans increased by 3.2% from 1.07% to 4.30% following the increase in loan losses provisions. With respect to capital adequacy ratio, it increased by 9.5% from 8.30% to 17.80% whereas the NPL ratio deteriorated from 3.90% to 46.70% (Table 3-4).

3.2.2 Eurobank

Between 2008 and 2018, Eurobank’s total assets decreased by 38.8% from €82.20 billion to € 50.27 billion and total liabilities decreased by 40.8% from €77.76 billion to €45.88 billion. Total equity decreased by 5.3% from €4.62 billion to €4.38 billion. Loans decreased by 47.5%, from €55.88 billion to €29.35 billion and deposits decreased by 36.2% from €45.66 billion to €29.13 billion. Unlike, Alpha Bank, loan losses provisions decreased by 31.6% from €886.0 million to €606.0 million. Eurobank’s net interest income decreased by 55.8% from €2.39 billion to €1.05 billion, operating revenue decreased by 53.0% from €3.12 billion to €1.46 billion, and operating expenses decreased by 57.6% from €1.57 billion to €664.0 million. Finally, net profit was down by 94.9% from €652.0 million to €33.0 million (Table 3- 5).

Over the same period, LTD ratio decreased by 21.6% from 122.39% to 100.75% following the decrease both in loans and deposits. The losses generated led to a decrease in ROA by

Postgraduate Dissertation 16 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

0.7% from 0.79% to 0.07% and in ROE by 13.3% from 14.10% to 0.75%. Net interest margin decreased by 1.1% from 3.20% to 2.10% following the decrease in net interest income and in total assets. The increase in equity generated an increased equity over total assets ratio, up by 3.1% from 5.62% to 8.71% and an equity over total liabilities ratio, up by 3.6% from 5.96% to 9.54%. Finally, provisions over loans increased by 0.5% from 1.59% to 2.06% and capital adequacy ratio increased by 5.7% from 10.40% to 16.10% whereas the NPL ratio deteriorated from 2.70% to 39.00% (Table 3-6).

Postgraduate Dissertation 17 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 3-3 Alpha Bank Basic Figures (2008-2017)

€ml 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 Total assets 61,006.7 60,813.0 64,872.3 69,297.5 72,935.5 73,697.3 58,357.3 59,148.0 66,798.3 69,596.0 65,270.0 Total equity 8,143.1 9,626.7 9,113.4 9,053.2 7,706.6 8,367.7 772.6 1,966.2 5,783.9 5,973.4 3,940.7 Total liabilities 52,863.6 51,186.3 55,758.9 60,244.3 65,228.9 65,329.5 57,584.7 57,181.8 61,014.4 63,622.7 61,329.3 Loans 40,228.3 43,318.2 44,408.8 46,186.1 49,557.0 51,678.3 40,495.3 44,875.7 49,304.7 51,399.9 50,704.7 Deposits 38,731.8 34,890.4 32,946.1 31,434.3 42,900.6 42,484.9 28,451.5 29,399.5 38,292.5 42,915.7 42,546.8 Loan Loss Provisions 1,730.6 1,005.4 1,168.0 2,987.6 1,853.2 1,923.2 1,668.9 1,130.3 884.8 676.3 541.8 Net interest income 1,756.0 1,942.6 1,924.1 1,897.5 1,938.5 1,657.8 1,397.3 1,783.7 1,818.6 1,762.6 1,798.6 Operating revenue 2,604.9 2,466.7 2,387.1 2,220.9 2,443.5 2,360.4 1,506.1 2,283.5 2,249.4 2,383.0 2,338.7 Operating expenses 1,162.4 1,293.0 1,225.5 1,266.9 1,645.1 1,425.9 1,178.7 1,096.3 1,148.5 1,201.9 1,178.3 Net profit 53.0 89.5 19.5 - 1,236.7 - 329.7 2,979.3 - 1,085.9 - 3,809.9 86.0 349.1 513.4 Source: Annual Reports Table 3-4 Alpha Bank Basic ratios (2008-2017)

2018 2017 2016 2015 2014 2013 2012 20 11 2010 2009 2008 LTD (loans to deposits) 103.86% 124.15% 134.79% 146.93% 115.52% 121.64% 142.33% 152.64% 128.76% 119.77% 119.17% ROA (return on assets) 0.09% 0.15% 0.03% -1.78% -0.45% 4.04% -1.86% -6.44% 0.13% 0.50% 0.79% ROE (return on equity) 0.65% 0.93% 0.21% -13.66% -4.28% 35.61% -140.55% -193.77% 1.49% 5.84% 13.03% NIM (net interest margin) 2.88% 3.19% 2.97% 2.74% 2.66% 2.25% 2.39% 3.02% 2.72% 2.53% 2.76% Equity / Total Assets 13.35% 15.83% 14.05% 13.06% 10.57% 11.35% 1.32% 3.32% 8.66% 8.58% 6.04% Equity / Total Liabilities 15.40% 18.81% 16.34% 15.03% 11.81% 12.81% 1.34% 3.44% 9.48% 9.39% 6.43% Provisions/Loans 4.30% 2.32% 2.63% 6.47% 3.74% 3.72% 4.12% 2.52% 1.79% 1.32% 1.07% Capital adequacy 17.80% 18.30% 17.10% 16.60% 14.30% 16.10% 8.90% 8.40% 11.80% 11.60% 8.30% NPL ratio 46.70% 45.00% 53.30% 50.40% 44.90% 44.90% 25.90% 21.20% 10.40% 5.70% 3.90% Source: Annual Reports and own work

Postgraduate Dissertation 18 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 3-5 Eurobank Basic Figures (2008-2017)

€ml 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 Total assets 50,275.0 51,448.0 66,432.0 73,553.0 75,518.0 77,586.0 67,653.0 76,822.0 87,199.0 84,269.0 82,202.0 Total equity 4,378.0 6,442.0 7,394.0 7,132.0 6,304.0 4,523.0 - 655.0 875.0 6,094.0 6,314.0 4,623.0 Total liabilities 45,897.0 45,006.0 59,038.0 66,421.0 69,214.0 73,063.0 68,308.0 75,947.0 81,105.0 77,955.0 77,579.0 Loans 29,354.0 30,866.0 39,058.0 39,893.0 42,133.0 53,498.0 47,841.0 48,094.0 56,268.0 55,837.0 55,878.0 Deposits 29,135.0 25,015.0 34,031.0 31,446.0 40,878.0 41,535.0 30,752.0 32,459.0 44,435.0 46,808.0 45,656.0 Loan Loss Provisions 606.0 716.0 741.0 2,265.0 2,264.0 1,920.0 1,655.0 1,333.0 1,273.0 1,177.0 886.0 Net interest income 1,055.0 1,100.0 1,463.0 1,463.0 1,470.0 1,294.0 1,461.0 2,039.00 2,103.00 2,341.0 2,385.0 Operating revenue 1,464.0 1,507.0 1,907.0 1,762.0 1,796.0 1,587.0 1,756.0 2,456.0 2,730.0 3,040.0 3,117.0 Operating expenses 664.0 672.0 903.0 1,017.0 1,035.0 1,071.0 1,052.0 1,198.0 1,280.0 1,471.0 1,566.0 Net profit 33.0 11.0 254.0 - 1,155.0 - 1,196.0 - 1,154.0 - 1,453.0 - 5,508.0 68.0 362.0 652.0 Source: Annual Reports

Table 3-6 Eurobank Basic ratios (2008-2017)

2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008

LTD (loans to deposits) 100.75% 123.39% 114.77% 126.86% 103.07% 128.80% 155.57% 148.17% 126.63% 119.29% 122.39% ROA (return on assets) 0.07% 0.02% 0.38% -1.57% -1.58% -1.49% -2.15% -7.17% 0.08% 0.43% 0.79% ROE (return on equity) 0.75% 0.17% 3.44% -16.19% -18.97% -25.51% 221.83% -629.49% 1.12% 5.73% 14.10% NIM (net interest margin) 2.10% 2.14% 2.20% 1.99% 1.95% 1.76% 2.05% 2.54% 2.63% 2.80% 3.20% Equity / Total Assets 8.71% 12.52% 11.13% 9.70% 8.35% 5.83% -0.97% 1.14% 6.99% 7.49% 5.62% Equity / Total Liabilities 9.54% 14.31% 12.52% 10.74% 9.11% 6.19% -0.96% 1.15% 7.51% 8.10% 5.96% Provisions/Loans 2.06% 2.32% 1.90% 5.68% 5.37% 4.02% 3.69% 2.77% 2.26% 2.11% 1.59%

Postgraduate Dissertation 19 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Capital adequacy 16.10% 18.00% 17.90% 17.40% 16.60% 11.30% 10.80% 12.00% 11.70% 12.70% 10.40% NPL ratio 39.00% 42.60% 46.30% 21.70% 25.30% 29.40% 22.80% 12.10% 8.20% 5.20% 2.70% Source: Annual Reports and own work

Postgraduate Dissertation 20 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

3.2.3 National Bank of Greece

Between 2008 and 2017, NBG’s total assets decreased by 35.8% from €101.32 billion to €65.09 billion. A decrease is also seen in total liabilities, down by 36.1%, from €93.06 billion to €59.46 billion and in total equity, down by 31.8% from €8.27 billion to €5.64 billion. Loans decreased by 56.8%, from €69.81 billion to €30.13 billion and deposits decreased by 36.4% from €67.66 billion to €43.03 billion. Loan losses provisions decreased by 42.0% from €538.0 million to €312.0 million and net interest income decreased by 69.4% from €3.58 billion to €1.09 billion. NBG’s operating revenue decreased by 73.2% from €4.93 billion to €1.32 billion and operating expenses decreased by 65.6% from €2.42 billion to €834 million. Finally, net profit was down by 103.2% from €1.55 billion to -€50.0 million (Table 3-7).

Over the same period, LTD ratio decreased by 33.1% from 103.18% to 70.04% following the decrease both in loans and deposits. Both ROA and ROE are down by 1.6% from 1.53% to - 0.08% and by 19.6% from 18.70% to -0.89%, respectively. Net interest margin decreased by 1.9% from 3.53% to 1.68% following the decrease in net interest income and in total assets. Equity over total assets increased by 0.5% from 8.16% to 8.66% and equity over total liabilities increased by 0.6% from 8.88% to 9.48%. Finally, provisions over loans increased by 0.3% from 0.77% to 1.04% and capital adequacy ratio increased by 5.9% from 10.30% to 16.20% whereas the NPL ratio deteriorated from 3.00 to 42.10% (Table 3-8).

Postgraduate Dissertation 21 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 3-7 National Bank of Greece Basic Figures (2008-2017)

€ml 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 Total assets 65,095.0 64,768.0 78,531.0 111,232.0 115,212.0 110,930.0 104,798.0 113,770.0 120,745.0 113,394.0 101,323.0 Total equity 5,638.0 7,379.0 6,907.0 9,099.0 9,612.0 7,111.0 - 2,284.0 6,177.0 9,655.0 9,828.0 8,267.0 Total liabilities 59,457.0 57,389.0 71,624.0 102,133.0 105,600.0 103,819.0 107,082.0 107,593.0 111,090.0 103,566.0 93,056.0 Loans 30,134.0 37,941.0 41,643.0 45,375.0 68,109.0 67,250.0 69,135.0 71,496.0 77,262.0 74,753.0 69,808.0 Deposits 43,027.0 40,265.0 40,459.0 45,929.0 64,929.0 62,876.0 58,722.0 59,544.0 68,039.0 71,194.0 67,657.0 Loan Loss Provisions 312.0 807 .0 784.0 4,263.0 2,523.0 1,373.0 2,966.0 3,439.0 1,365.0 1,295.0 538.0 Net interest income 1,094.0 1,532.0 1,648.0 1,905.0 1,998.0 3,157.0 3,365.0 3,843.0 4,148.0 3,940.0 3,580.0 Operating revenue 1,320.0 1,594.0 1,832.0 1,780.0 3,564.0 3,771.0 3,527.0 4,372.0 4,641.0 5,077.0 4,926.0 Operating expenses 834.0 828.0 1,006.0 1,302.0 1,357.0 2,572.0 2,349.0 2,571.0 2,510.0 2,530.0 2,422.0 Net profit - 50.0 - 412.0 - 2,887.0 - 2,608.0 66.0 809.0 - 2,127.0 - 12,344.0 406.0 923.0 1,546.0 Source: Annual Reports Table 3-8 National Bank of Greece Basic ratios (2008-2017)

2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 LTD (loans to deposits) 70.04% 94.23% 102.93% 98.79% 104.90% 106.96% 117.73% 120.07% 113.56% 105.00% 103.18% ROA (return on assets) -0.08% -0.64% -3.68% -2.34% 0.06% 0.73% -2.03% -10.85% 0.34% 0.81% 1.53% ROE (return on equity) -0.89% -5.58% -41.80% -28.66% 0.69% 11.38% 93.13% -199.84% 4.21% 9.39% 18.70% NIM (net interest margin) 1.68% 2.37% 2.10% 1.71% 1.73% 2.85% 3.21% 3.38% 3.44% 3.47% 3.53% Equity / Total Assets 8.66% 11.39% 8.80% 8.18% 8.34% 6.41% -2.18% 5.43% 8.00% 8.67% 8.16% Equity / Total Liabilities 9.48% 12.86% 9.64% 8.91% 9.10% 6.85% -2.13% 5.74% 8.69% 9.49% 8.88% Provisions/Loans 1.04% 2.13% 1.88% 9.40% 3.70% 2.04% 4.29% 4.81% 1.77% 1.73% 0.77% Capita l adequacy 16.20% 17.00% 16.30% 14.60% 13.50% 11.20% 9.20% 8.30% 13.70% 11.30% 10.30% NPL ratio 42.10% 39.90 % 32.40% 25.60% 24.80% 22.30% 19.40% 9.80% 5.20% 3.10% 3.00% Source: Annual Reports and own work

Postgraduate Dissertation 22 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

3.2.4 Piraeus Bank

Between 2008 and 2018, the total assets of Piraeus Bank increased by 12.7% from €54.89 billion to €61.88 billion. An increase is also seen in total liabilities, up by 4.8%, from €51.86 billion to €54.37 billion and in total equity, up by 1448.1% from €3.02 billion to €7.51 billion. Loans increased by 3.8%, from €38.31 billion to €39.76 billion and deposits increased by 43.0% from €31.29 billion to €44.74 billion. Also, loan losses provisions increased by 37.1% from €388.0 million to €532.0 million and net interest income increased by 21.6% from €1.16 billion to €1.41 billion. Piraeus Bank’s operating revenue increased by 13.9% from €1.65 billion to €1.88 billion and operating expenses increased by 29.4% from €897.0 million to €1.16 billion. Finally, net profit was down by 45.1% from €315.0 million to €173.0 million (Table 3-9).

Over the same period, LTD ratio decreased by 33.6% from 122.43% to 88.86% despite the increase both in loans and deposits. ROA decreased by 0.3% from 0.57% to 0.28% and ROE by 8.1% from 10.41% to 2.30%. Net interest margin increased by 0.2% from 2.11% to 2.28% whereas equity over total assets increased by 6.6% from 5.51% to 12.13% and equity over total liabilities by 8.0% from 5.83% to 13.80%. Finally, provisions over loans increased by 0.30% from 1.01% to 1.34%. Piraeus’ capital adequacy ratio increased by 3.8% from 9.90% to 13.65% whereas the NPL ratio deteriorated from 5.10% to 32.80% (Table 3-10).

Postgraduate Dissertation 23 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 3-9 Piraeus Bank of Greece Basic Figures (2008-2017)

€ml 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 Total assets 61,880.0 67,416.6 81,504.4 87,528.0 89,290.0 92,009.6 70,408.5 49,352.3 57,561.3 54,280.0 54,890.0 Total equity 7,506.0 9,544.2 9,823.7 9,907.6 7,210.2 8,543.0 - 2,324.0 2,711.0 3,2 74.0 3,614.0 3,025.0 Total liabilities 54,374.0 57,872.4 71,680.6 77,620.4 82,079.8 83,466.6 72,732.5 46,641.3 54,287.3 50,666.0 51,865.0 Loans 39,757.0 44,719.5 49,707.6 50,591.2 57,143.0 62,365.8 44,612.7 37,058.0 38,218.0 37,688.0 38,313.0 Deposits 44,739.0 42,715.3 42,364.8 38,951.9 54,732.8 54,279.0 36,971.0 22,038.0 28,675.0 30,755.0 31,294.0 Loan Loss Provisions 532.0 2, 020.0 1,003.9 3,486.8 3,708.8 2,363.8 2,057.2 7,863.0 585.0 491.0 388.0 Net interest income 1,410.0 1,63 9.0 1,764.6 1,877.2 1,9 82.9 1,662.2 1,027.5 1,173.0 1,188.0 1,105.0 1,160.0 Operating revenue 1,882.0 2, 146.0 2,226.5 2,393.1 2,451.7 5,945.5 2,217.3 1,213.0 1,477.0 1,663.0 1,652.0 Operating expenses 1,161.0 1,1 06 .0 1,189.2 1,472.7 1,443.0 1,637.3 907.4 796.0 837.0 893.0 897. 0 Net profit 173.0 - 13.0 - 40.1 - 1,861.4 - 1,945.2 2,516.2 - 520.6 - 6,577.0 20.0 235.0 315.0 Source: Annual Reports

Table 3-10 Piraeus Bank of Greece Basic ratios (2008-2017)

2018 2017 2016 2015 20 14 2013 2012 2011 2010 2009 2008 LTD (loans to deposits) 88.86% 104.69% 117.33% 129.88% 104.40% 114.90% 120.67% 168.16% 133.28% 122.54% 122.43% ROA (return on assets) 0.28% -0.02% -0.05% -2.13% -2.18% 2.73% -0.74% -13.33% 0.03% 0.43% 0.57% ROE (return o n equity) 2.30% -0.14% -0.41% -18.79% -26.98% 29.45% 22.40% -242.60% 0.61% 6.50% 10.41% NIM (net interest margin) 2.28% 2.43% 2.16% 2.14% 2.22% 1.81% 1.46% 2.38% 2.06% 2.04% 2.11% Equity / Total Assets 12.13% 14.16% 12.05% 11.32% 8.07% 9.28% -3.30% 5.49% 5.69% 6.66% 5.51% Equity / Total Liabilities 13.80% 16.49% 13.70% 12.76% 8.78% 10.24% -3.20% 5.81% 6.03% 7.13% 5.83% Provisions/Loans 1.34% 4.52% 2.02% 6.89% 6.49% 3.79% 4.61% 21.22% 1.53% 1.30% 1.01% Capital adequacy 13.65% 16.30% 17.60% 17.50% 12.50% 14.00% 9.70% 8.70% 9.60% 9.80% 9.90% NPL ratio 32.80% 34.40% 36.60% 39.50% 38.80% 36.60% 23.00% 14.00% 7.50% 5.10% 5.10% Source: Annual Reports and own work

Postgraduate Dissertation 24 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

3.2.5 Comparative analysis between the four systemic banks

By comparing the LTD ratios of the four systemic banks for the period 2008-2018, it is seen that the National Bank of Greece has the lowest ratios (103.4% on average) whereas the highest LTD ratios belong to Alpha Bank (128.14% on average) and Eurobank (124.52% on average). Piraeus Bank has an average LTD ratio of 120.65% (Figure 3-5). The general trend of all LTD ratios is downward, mostly as a result of the decrease in loans and deposits. Even though Piraeus Bank is the only bank that increased its deposits by 43.0%, the small improvement in loans (+3.8%) could not generated an upward LTD ratio.

Comparing LTD ratios (2008-2018)

180,00% 160,00% 140,00% 120,00% 100,00% 80,00% 60,00% 40,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Alpha Bank Eurobank NBG Piraeus Bank Linear (Alpha Bank) Linear (Eurobank) Linear (NBG) Linear (Piraeus Bank)

Figure 3-5 Comparing LTD ratios Source: Annual Reports and own work

Regarding the NIM ratio, Alpha Bank outperforms all other banks followed by Piraeus Bank and Eurobank whereas NBG incurred a decrease (Figure 3-6). The significant decrease in NBG’s net interest income (-69.4%) along with the decrease in total assets (- 35.8%) justifies the decline by 1.85% in NIM ratio. The same holds true for Eurobank that incurred a 55.8% decrease in net interest income and -38.8% in total assets, leading to 1.10% decrease in NIM ratio. In contrast, Alpha Bank incurred a minor decrease both in net interest income and in total assets (-2.4% and -6.5%, respectively) whereas Piraeus Bank increased its net interest income by 21.6% and its total assets by 12.7%, thereby slightly improving the NIM ratio by 0.12% and 0.17% respectively.

Postgraduate Dissertation 25 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Comparing NIM ratios (2008-2018)

4,00%

3,50%

3,00%

2,50%

2,00%

1,50%

1,00%

0,50%

0,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Alpha Bank Eurobank NBG Piraeus Bank

Figure 3-6 Comparing NIM ratios Source: Annual Reports and own work

As seen in Figure 3-7, the net profit of all four banks significantly deteriorated in 2011. Overall there are great fluctuation in the net profit following the 2008 crisis.

Comparing Net profit (2008-2018)

4.000,0 2.000,0 - 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 -2.000,0 -4.000,0 -6.000,0 -8.000,0 -10.000,0 -12.000,0 -14.000,0 Alpha Bank Eurobank NBG Piraeus Bank

Figure 3-7 Comparing Net profit Source: Annual Reports and own work

Since the major deterioration in the results of all banks took place in 2011, we estimate the loan loss provisions between 2011 and 2018. As seen in Figure 3-8, in 2011 Piraeus Bank

Postgraduate Dissertation 26 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” had the highest amount of loan loss provisions (€7,863.0 million) followed by NBG (€3,439.0 million). Through 2018, loan loss provisions for all four banks decreased, although slight increases took place in 2014 and 2015. Consequently, provisions over loans ratio for Piraeus Bank reached 21.22% in 2011, whereas in 2015 the highest ratio of 9.40% is seen in NBG. Through 2018, the trend is downward (Figure 3-9).

Loan Loss Provisions (2011-2018) 8.000,0

7.000,0

6.000,0

5.000,0

4.000,0

3.000,0

2.000,0

1.000,0

0,0 2011 2012 2013 2014 2015 2016 2017 2018 Alpha Bank 1.130,3 1.668,9 1.923,2 1.853,2 2.987,6 1.168,0 1.005,4 1.730,6 Eurobank 1.333,0 1.655,0 1.920,0 2.264,0 2.265,0 741,0 716,0 606,0 NBG 3.439,0 2.966,0 1.373,0 2.523,0 4.263,0 784,0 807,0 312,0 Piraeus Bank 7.863,0 2.057,2 2.363,8 3.708,8 3.486,8 1.003,9 2.020,0 532,0 Figure 3-8 Loan Loss Provisions (2011-2018) Source: Annual Reports and own work

Postgraduate Dissertation 27 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Provisions/Loans ratio (2011-2018) 22,00%

17,00%

12,00%

7,00%

2,00%

-3,00% 2011 2012 2013 2014 2015 2016 2017 2018 Alpha Bank 2,52% 4,12% 3,72% 3,74% 6,47% 2,63% 2,32% 4,30% Eurobank 2,77% 3,69% 4,02% 5,37% 5,68% 1,90% 2,32% 2,06% NBG 4,81% 4,29% 2,04% 3,70% 9,40% 1,88% 2,13% 1,04% Piraeus Bank 21,22% 4,61% 3,79% 6,49% 6,89% 2,02% 4,52% 1,34% Figure 3-9 Provisions/Loans ratio (2011-2018) Source: Annual Reports and own work

Regarding the NPL ratio, the trend is upward in all four banks between 2011 and 2018 (Figure 3-10).

NPL ratio (2011-2018)

60,00%

50,00%

40,00%

30,00%

20,00%

10,00%

0,00% 2011 2012 2013 2014 2015 2016 2017 2018 Alpha Bank 21,20% 25,90% 44,90% 44,90% 50,40% 53,30% 45,00% 46,70% Eurobank 12,10% 22,80% 29,40% 25,30% 21,70% 46,30% 42,60% 39,00% NBG 9,80% 19,40% 22,30% 24,80% 25,60% 32,40% 39,90% 42,10% Piraeus Bank 14,00% 23,00% 36,60% 38,80% 39,50% 36,60% 34,40% 32,80%

Figure 3-10 NPL ratio (2011- 2018) Source: Annual Reports and own work

Postgraduate Dissertation 28 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

4.

4.1 Defining NPEs

A non-performing loan is an amount of borrowed money for which the borrower has not made the scheduled payments for a specified period. Although the exact details of the NPL situation vary according to the terms of the loan, the common element is zero capital or interest payments. In the banking sector, commercial loans are considered non-performing if the borrower has made no interest or capital payments for 90 days or 180 days depending on the sector and the type of loan (Segal, 2019). For example, the European Central Bank (ECB) requires comparability of assets for the risk exposures assessment across all euro area central banks and sets out multiple criteria that can trigger NPL classification when performing bank stress tests (Lautenschläger, 2019).

The European Banking Authority (EBA) uses a uniform definition of "non-performing exposure" (NPE) in order to overcome the problems resulting from different definitions relating to non-performing loans. Although the definition of NPE is required only for the purposes of supervisory information, the institutions are strongly encouraged to use the NPE definition in both internal risk management and public financial reporting. In addition, the NPE definition is used in several relevant supervisory exercises such as asset quality control, stress testing, and transparency exercises (ECB, 2017).

European supervisors usually determine a loan to be non-performing when there are signs that the debtor is unlikely to repay the loan due to financial difficulties or if more than 90 days have passed without any payment of the agreed installments. For retailers, financial difficulties can be the result of job loss, which inhibits a borrower to repay their mortgage as agreed, whereas for companies it may be the outcome of lower cash flows. Thus, NPE is a concept that extends beyond the definition of “impaired” and “default”. In fact, all impaired exposures and all defaulted exposures are automatically NPEs, but NPEs may also incorporate exposures that are not recognized as “impaired” or “defaulted” within a certain accounting or regulatory framework.

Postgraduate Dissertation 29 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

According to the ECB, non-performing exposures meet one or both of the following criteria:

1. Open assets are overdue for more than 90 days.

2. Debtors are deemed unlikely to fully cover their credit obligations without collateral and guarantees, irrespective of the level of past liabilities or the number of days of delay.

Exposure may be non-performing only if there was a legal obligation for compulsory payment. In the absence of a legal obligation or a mandatory payment, non-payment is not a violation. However, banks should carefully evaluate whether non-payment is related to other events that justify the classification of a loan as NPL. If it is uncertain whether a legal obligation exists, banks should consider whether the recognition of an NPE is the result of differences from isolated disputes that are unrelated to the debtor’s solvency. In this case, the debtor does not need to be classified as insolvent and his debts are not classified as NPEs. On the other hand, if a debtor goes bankrupt, then it falls within the predetermined events set by the banks for a loan to automatically be classified as non- performing. Therefore, banks should regularly assess the creditworthiness and repayment ability of their customers, both retailers and companies (ECB, 2017).

According to the International Monetary Fund (Bloem and Freeman, 2005), non- performing loans meet the following criteria:

1. The debtor has not made interest and / or capital payments for at least 90 days or more.

2. Interest payments equal to 90 days or more have been capitalized, refinanced or delayed by agreement.

3. Payments are delayed less than 90 days, but there is no certainty that the borrower will make payments in the future.

Postgraduate Dissertation 30 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

4.2 Macroeconomic factors that affect NPEs

4.2.1 GDP growth

Several papers in the banking literature investigate the connection between macroeconomic environment and loan quality, addressing the impact of macroeconomic factors on non- performing exposures. During economic expansion, there is a relatively small number of non-performing loans, as both consumers and firms have an adequate stream of income and revenues to meet their borrowing obligations in predetermined deadlines. However, as the booming phase continues, credit is provided to lower-quality debtors and when recession sets in, NPLs increase (Messai and Jouini, 2013). Further, the failure of lower- quality borrowers to service their loan obligations during a recession is caused by the decrease in asset values of collateral and the following tightening of credit as banks become more risk-averse (Geanakoplos, 2009).

Fofack (2005) explores the leading roots of nonperforming loans in several countries in Sub-Saharan Africa during the economic and banking crises in the 1990s. His empirical evidence reveals a huge increase in NPEs in concert with high credit risk. Further, results show a strong causality between NPEs and GDP growth, appreciation of real exchange rate, interest rates, net interest margins, and interbank loans. The findings verify that non- performing loans are highly driven by macroeconomic volatility. Jimenez et.al. (2006) take on a large panel of corporate loans granted by Spanish banks over the period 1984-2000 and find that the use of collateral is determined differently depending on the segment of the credit market, e.g. short or long-term, new or old borrower, etc. Rinaldi and Sanchis- Arellano (2006) use a panel of household loans in seven eurozone countries (Belgium, France, Finland, Ireland, Italy, Portugal, and Spain) for the period 1989Q3 to 2004Q2. Their findings suggest that, in the long run, a surge in the ratio of indebtedness to income is related to higher levels of NPLs, unless: (1) the household income increases as well, and (2) inflation is relatively stable. In the short run, a rising debt ratio cannot be easily offset by household income, thereby putting the household sector in a riskier financial position. Quagliarello (2007) investigates the relationship between NPLs and GDP growth for a large sample of Italian banks between 1985-2002 and determines that loan loss provisions and NPLs show a cyclical pattern that is related to the business cycle.

Postgraduate Dissertation 31 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Bofondi and Ropele (2011) study the loan quality of Italian banks both to households and firms with respect to macroeconomic determinants and underline that the quality of lending is primarily explained by the growth and the general state of the economy, the cost of borrowing and the burden of debt. Erdinç and Abazi (2014) assert that the surge in the NPLs in Europe following the crisis led to severe banking distress and constrained bank lending. Their evidence shows that NPLs are particularly sensitive to GDP growth, and inflation. By investigating a sample of non-performing loans in Nigerian banks between 1995 and 2009, Inekwe (2013) identifies a strong relationship between NPEs and GDP.

4.2.2 Unemployment

High unemployment rates create a turbulent economic environment, in which the banking sector and, particularly commercial banks, face a higher credit risk due to the lower streams of income of their borrowers. Households may be impacted by a reduction in the base pay or long-term unemployment while the corporate borrowers may face a weaker demand for their products due to lower household income available. This vicious cycle further incorporates adverse house prices, corporate bankruptcy, and higher unemployment rates.

By studying the Nordic banking system over the period 1993–2005, Berge and Boye (2007) find that NPLs are significantly correlated to unemployment and interest rates. Evidence from a large sample of households in the Euro area shows that the country level data on NPLs is subject to the level of unemployment in the country as well as to the responses of the economy to an interest rate shock, an income shock, and a house price shock. The findings suggest that declining collateral values are due to inefficient legal systems or blockages in judicial procedures that eventually increase bank losses (Ampudia et.al., 2016). Gerardi et.al. (2017) measure a borrower’s ability to service their debt based on household-level data, such as income, employment status, and mortgage characteristics. The authors argue that the probability of default primarily depends on income and unemployment, as the latter is linked to the uncertainty regarding future income and the lending rates. Herkenhoff and Ohanian (2019) evaluate the impact of foreclosure delays on the U.S. labor market and determine that they decrease employment by 0.75% and nearly double the stock of default mortgages but also allow mortgagors to remain in their homes.

Postgraduate Dissertation 32 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

In the cases of severe foreclosure delays employment can be decreased by up to 1.3%. The borrowing limits in an economy depend on the frequency of liquidity shocks as well as the level of complementarity between credit and labor markets. Evidence on U.S. labor and credit markets over the period 1980-2008 shows that a surge in unsecured credit accounts for about 75% of the decline in the long-term average unemployment rate (Bethune et.al., 2015). Evidence from Eastern Europe between 1998 and 2011 concludes that the level of non-performing loans in an economy is primarily associated to macroeconomic factors, including GDP growth, unemployment rate, and inflation as well as bank-related factors, such as equity-to-asset ratio and return on equity (ROE) which are negatively correlated with NPLs. On the other hand, the loan-to-asset ratio is positively correlated to NPLs. Although bank-related factors have a noteworthy impact on NPLs, their overall explanatory power is relatively low (Klein, 2013). Akinlo and Emmanuel (2014) investigate the determinants of NLPs in Nigeria and conclude that credit risk is related to macroeconomic conditions with the aggregate NPL ratio serving as a proxy for the banking sector probability of default based on overall loan exposure. In the short term, unemployment has a negative impact on NPLs.

4.2.3 Inflation

As far as inflation is concerned, there is no clear link between it and non-performing loans. On one hand, higher inflation can make debt servicing easier because it lowers the real value of the loan outstanding, but on the other hand, it also reduces the real income when wages are sticky or cut. Nkusu (2011) argues that in countries with variable loan rates, a rise in the inflation rate can lead to higher loan installments due to monetary policy actions undertaken by the government to combat inflation.

Khan et.al. (2018) argue that NPLs ratio is the most important determinant of bank survival, especially in a macroeconomic environment that is unfavorable. By considering GDP per capita, inflation, and total loans as independent variables, the authors perform econometric analysis on a sample of US NPLs for the period 1985-2010. Their findings show that the selected macro factors have a significant impact on non-performing loans, however, inflation is inversely related to the NPLS ration. Memdani (2017) investigate the determinants of non-performing exposures in the Indian banking sector using a sample of

Postgraduate Dissertation 33 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” public sector banks (PSBs), private banks (PBs) and foreign banks (FBs) for the period 2005-2014. Their analysis shows that per capita income and inflation have a significant impact on NPEs in concert with bank-specific variables such as size and loans-to-total loans ratio. Evidence from 34 advanced countries shows that NPLs are affected by current account deficit, credit growth, income per capita, inflation and money stock. Especially during the 2008 crisis, credit growth and current account deficit are the most important determinants of NPLs along with inflation (Kauko 2012). Škarica (2014) investigates the determinants of the changes in the NPL ratio in seven Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czech Republic, Hungary, Latvia, Romania, and Slovakia) between 2007 and 2012. The findings suggest that the high levels of NPLs in these countries is the economic slowdown as expressed by GDP, unemployment and the inflation rate. A research on the factors that affect the NPL ratio of Eurozone’s banks for the period 2000-2008 takes into account the impact of the crisis and suggest that the soundness of European banks has been called into question. The most important macro-variables are GDP growth, public debt as a percentage of GDP, house prices, unemployment, inflation, and lending rates (Makri et.al., 2014).

4.3 Macroeconomic factors and NPEs during the 2008 financial crisis

During the global financial crisis, non-performing loans increased significantly on banks' balance sheets, creating a major challenge for policymakers around the world. Also, deregulation strengthened competition among European banks. Makri et.al. (2014) argue that competition increases credit risk and affect the banks’ loan portfolios in terms of non- performing loans, as a result of loose borrowing criteria and lack of adequate control over a borrower’s creditworthiness. The sharp increase of NPLs is most evident in some European countries, especially in southern Europe, resulting in a higher rate of EU NPLs, 7.48% in 2012. However, the ratio of NPLs as a percentage of global total shows a decrease across the European Union, which can be attributed to enhanced bank lending activities in recent years. In 2017, the EU non-performing loans ratio is marginally below the global average of 3.74%, to 3.45%, suggesting that NPLs are no longer a specific European problem and are related to the broader macroeconomic environment (Figure 4-1).

Postgraduate Dissertation 34 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

EU NPLs % global total (2010-2017) 8,00% 7,48% 7,00% 6,41% 6,00% 6,01%

5,39% 5,48% 5,00% 4,91% 4,52% 4,00% 4,09% 4,16% 3,72% 4,01% 4,01% 3,92% 3,78% 3,74% 3,00% 3,45%

2,00% 2010 2011 2012 2013 2014 2015 2016 2017 EU World

Figure 4-1 EU NPLs (% global total) (2010-2017) Source: World Bank (2019)

Non-performing loans in the euro area as a percentage of total gross loans grew by 0.39% between 2008 and 2017, from 2.81% to 3.20%. However, in 2012 and 2013, NPLs were 8.10% and 7.89% of the total gross loans in the eurozone, respectively (Figure 4-2).

EU NPLs (% total gross loans) (2008-2017) 9,00%

8,10% 8,00% 7,89%

7,00% 6,74% 6,00% 5,60% 5,17% 5,35% 5,00% 4,87% 4,44% 4,00%

3,20% 3,00% 2,81%

2,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Figure 4-2 EU NPLs (% total gross loans) (2008-2017) Source: World Bank (2019a)

Postgraduate Dissertation 35 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Over the period 2008-2017, EU NPLs increased by 0.39% from 2.81% to 3.20%. EU GDP grew by 1.97% from 0.48% to 2.46%, and unemployment rate by 0.66% from 6.96% to 7.61%. In contrast, inflation declined by 0.30% from 1.64% to 1.34% over the same period. The data prove the inverse relationship between NPLs and inflation and the positive association between NPLs, GDP, and unemployment.

Table 4-1 Macroeconomic factors and NPLs in the EU (2008-2017)

2008 2009 2010 2011 2012

NPLs (% total gross loans) 2.81% 5.17% 5.60% 6.74% 8.10% GDP growth 0.48% -4.35% 2.24% 1.76% -0.40% Unemployment 6.96% 8.87% 9.51% 9.60% 10.42% Inflation 1.64% 0.93% 2.22% 2.75% 2.22% 2013 2014 2015 2016 2017 NPLs (% total gross loans) 7.89% 5.35% 4.87% 4.44% 3.20% GDP growth 0.26% 1.78% 2.35% 2.04% 2.46% Unemployment 10.82% 10.21% 9.38% 8.54% 7.61% Inflation 0.85% -0.17% 0.09% 1.10% 1.34% Source: World Bank, Inflation.eu (2019)

Minimizing NPLs is a prerequisite for economic growth. NPLs are likely to hinder economic growth and reduce economic efficiency, leading to macroeconomic imbalances and systemic shocks. In the developed economies evidence shows that macroeconomic conditions affect credit risk. Hence, the quality of loans is positively related to GDP growth (Figure 4-3).

Postgraduate Dissertation 36 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

EU NPLs and GDP growth (2008-2017)

9,00%

7,00%

5,00%

3,00%

1,00%

-1,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

-3,00%

-5,00%

NPLs GDP

Figure 4-3 EU NPLs and GDP growth (2008-2017) Source: World Bank (2019) and own work

Empirical evidence shows that non-performing loans demonstrate anti-cyclical behavior. This means that declining GDP and rising unemployment can have a major negative impact on NPLs. For example, the intensification of recession in Greece, along with the political uncertainty, led to a sharp increase in the NPLs of the Greek banks.

Between 2008 and 2017, average EU unemployment rate is 9.19% and average NPLs are 5.42%, both moving in the same direction. In contrast, average EU inflation is 1.30% but the trend is opposite to that of the NPLs. For example, when NPLs peak in 2012 and 2013 to 8.10% and 7.89%, respectively, inflation hits low to 2.22% and 0.85%, respectively (Figure 4-5).

Postgraduate Dissertation 37 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

EU NPLs and unemployment rate (2008-2017) 12,00%

10,00%

8,00%

6,00%

4,00%

2,00%

0,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

NPLs Unemployment

Figure 4-4 EU NPLs and unemployment rate (2008-2017) Source: World Bank (2019) and own work

EU NPLs and inflation rate (2008-2017)

9,00%

7,00%

5,00%

3,00%

1,00%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 -1,00%

NPLs Inflation

Figure 4-5 EU NPLs and inflation rate (2008-2017) Source: World Bank, Inflation.eu (2019) and own work

Postgraduate Dissertation 38 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

4.4 Forbearance and NPEs

Under the Basel definition, non-performing exposures are credit impaired for accounting purposes, which equates to Stage 3 of the IFRS 9 provisioning model explained in the following Chapter. Forbearance is an impermanent deferment of a loan payment granted by the creditor and takes place when the borrower experiences financial difficulties (Bholat et.al., 2018). In this context, the objective of forbearance measures pertaining to NPEs is “to assist non-performing borrowers to exit their non-performing status, or to prevent performing borrowers from reaching a non-performing status.” On the other hand, supervisory experience shows that forbearance solutions may not fully meet above objectives, thereby leading to unnecessary delays in effectively tackling asset quality issues. This is most evident when forbearance measures granted during financial difficulties contain repeated grace periods but do not address the over-indebtedness problem of a borrower compared with its repayment capability (ECB, 2017).

A major consideration when investigating different forbearance solutions is to distinguish between short-term and long-term measures or a combination of both with different time horizons. Generally, short-term forbearance measures involve temporary restructured repayment options – up to two years - to address financial difficulties in the short-term. Short-term forbearance measures are offered provided that the borrower: (1) has experienced a recognizable event which has caused temporary liquidity constraints, and (2) has consistently demonstrated a good financial relationship with the bank (e.g. significant capital repayment prior to liquidity constraints) and is definitely willing to cooperate with the bank towards forbearance. Events that caused temporary liquidity constraints should be evidenced formally via written documentation with evidence that the borrower’s income is expected to recover in the short-term or based on a short-term forbearance measure. The bank maintains the right to review the agreed forbearance measures if the financial situation of the loan holder improves and the bank can capitalize on more favorable conditions (ECB, 2017).

Long-term forbearance measures should be considered provided that the borrower: (1) can afford such a solution, and (2) the imposition of long-term forbearance will lead to a significant reduction of the borrower’s outstanding balance. The bank maintains the right to perform additional reviews in order to ensure that long-term forbearance measures are

Postgraduate Dissertation 39 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” viable and do not result in numerous repeated forbearance measures having been granted to the same NPL (ECB 2017).

Table 4-2 summarizes short-term and long-term forbearance measures.

Table 4-2 Forbearance measures for NPEs

Short-term forbearance measures Long-term forbearance measures Arrears Capitalization Interest rate reduction Arrears repayment plan Loan term extension Reduced payment above interest only Split balance Reduced payment below interest only Partial debt forgiveness/ Write-down Interest only Operational restructuring Grace period Debt to Equity swap Source: Chalkiadis (2019)

4.5 Provisions for impaired loans and earnings management

One of the most widespread practices that affect financial reporting quality is earnings management. The extent to which and the reasons why banks employ income smoothing practices have attracted the attention of academics, investors, and regulators alike. According to Shen and Chih (2005), 75% of banks in 48 countries use earnings management. The incentive of banks to manage earnings is closely associated with the risk and return relationship whereas stronger investor protection and higher accounting disclosure transparency can lower banks’ incentives for earnings management. Hence, banks should adopt international quality control standards to reduce earnings management practices and diminish the impact of stakeholders’ decisions on financial reporting quality (Talab et.al., 2018).

Karaoglu (2005) argues that banks use gains from loan transfers and securitizations to manage accounting information for regulatory and other purposes, such as analyst forecasts of revenue. The use of securitizations for earnings management is positively correlated to the degree of financial reporting discretion available to bank managers. Also, securitizations with some forms of retained interest can be accounted for as sales and affect profits and regulatory capital, allowing capitalization of expected future income. The study

Postgraduate Dissertation 40 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” concludes that banks use profits from loan sales and securitizations, after controlling for other financial incentives for loan securitization, such as comparative advantage, financing, and risk management. Managers use their discretionary power in a biased way, motivated by market-related incentives, thus raising concerns about the reliability of disclosures of bank risks and the fair value reporting. Liu and Ryan (2006) present the complex nature of income normalization in setting bank forecasts for loan losses and borrowing costs. It appears that while banks manage provisions for loan losses loan charge-offs for smoothing income collection, banks’ discretionary behavior is limited by whether they maintain homogeneous or heterogeneous loans and these restrictions are bound differently in the banking business cycle. Fonseca and Gonzalez (2008) investigate the determinants of income smoothing through loan loss provisions management using a sample of 4,546 banks from 41 countries. Their findings show that income smoothing with loan loss provisions is different across countries and subject to banking institutions, regulation, supervision, financial structure, and development of the financial system. Income smoothing diminishes in proportion to investor protection, the extent of accounting disclosure, restrictions on bank activities and supervision, while it increases within proportion to the development of the financial system. Kosmidou (2008) examines the determinants of the performance of Greek banks during the period of EU economic integration (1990-2002), approaching an unbalanced set of time series of 23 banks. Findings show that high return on average assets (ROAA) is linked to capitalized banks and lower cost and income ratios. Findings suggest that the increase in money supply does not have a significant effect on earnings, while banks' assets to GDP, the capitalization of stock markets to assets and the concentration of banks all are statistically significant and negatively related to the ROAA. Therefore, a high ROAA ratio is linked to well-capitalized banks and cost-effective management (lower cost/revenue ratio).

Cheng et. al. (2011) investigate the relationship between capital incentives and profits management in the banking industry and find that bank managers with high equity incentives tend to employ earning management, but only when capital adequacy ratios are close to minimum capital requirements. Further, there is a positive relationship between equity incentives and profit management in banks with possible regulatory intervention, indicating a stronger incentive to avoid such interventions through earnings management. Using a panel of public banks, Hribar et. al. (2017) explore whether the managerial

Postgraduate Dissertation 41 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” sentiment is linked to errors in accrual accounting estimates and determine a negative association to loan loss provisioning and a positive association to future charges-off per dollar of provisions. Although fundamentals account for most of the variance in the forecast, it seems that managerial sentiment has a gradual and economically significant impact on loan loss provisioning. Ozili and Outa (2017) observe that loan loss provisions (LLPs) interact with accounting, institutional, tax and fiscal frameworks across different. Managerial discretion in loan loss provisioning is strongly related to income smoothing, capital management, and tax management. Highly concentrated banking sectors with a high level of NPLs are also characterized by higher credit risk, which is related to (LLPs). Evidence from Italian banks shows that LLPs are higher in regional banking systems, typically characterized by a higher loan concentration and a lower degree of competition. In these banks, CEOs tend to engage in earnings management practices seeking to stabilize the banks’ income flows over time (Aristei and Gallo, 2019).

Postgraduate Dissertation 42 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

5.

5.1 Introducing IFRS 9

Following the global financial crisis of 2008, the International Accounting Standards Board (IASB) introduced the International Financial Reporting Standard 9 (IFRS 9), seeking to further stabilize the financial and banking system. IFRS 9, effective 1 January 2018, has introduced new accounting rules for a wide range of issues, including financial assets, financial liabilities, impairment assessment, fair value options, and hedge accounting. The new regime enhances accounting decisions by incorporating forward-looking information when assessing credit losses to timely recognize provisions and introduces a new reclassification system of financial assets (Ntaikou et.al., 2018).

The transition from IAS 39 to IFRS 9 has been concluded in July 2014 with the replacement of International Accounting Standards (IAS) 39. The main reason for the replacement is that IAS 39 was considered too complex, inconsistent with the way companies manage their operations and risks and failing to recognize credit losses on loans and receivables only until too late in the credit cycle. The financial crisis has accelerated the replacement of IAS 39 and the new standards have been developed in three phases in order to separately deal with the classification and measurement of financial assets, impairment, and hedging, respectively (PWC, 2016).

5.2 Main characteristics

IFRS 9 measures all financial assets and liabilities at fair value at initial recognition, except for trade receivables, which are measured at the transaction price as stated in IFRS 15 because they do carry a significant financing component, especially if the expected term is less than one year. For an accountant to determine whether a significant financing component exists, there are certain issues that need to be taken under consideration such as the difference between the cash price and the transaction price of the asset, the term of the receivable, and the prevailing interest rates (PWC, 2016).

Postgraduate Dissertation 43 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

5.2.1 Initial measurement of financial assets

Within the scope of IFRS 9, all financial instruments are initially recognized at fair value plus or minus transaction costs, - a requirement that is consistent with IAS 39. Financial asset classification and measurement is determined at initial recognition, but, if certain conditions are met, an asset may need to be reclassified. However, all assets under IFRS 9 are measured at:

amortized cost;

fair value through other comprehensive income (FVTOCI); or

fair value through profit or loss (FVTPL).

The FVTOCI classification is compulsory for certain debt instrument assets unless the fair value option (FVTPL) is selected. In contrast, the FVTOCI classification for equity investments is optional. Debt instruments are classified at FVTOCI and interest income, foreign currency gains or losses, and impairment gains or losses are recognized directly in profit or loss. Equity investments are measured at fair value in the statement of financial position and value changes are recognized in profit or loss, except for those equity investments for which the company chooses to present their value changes in the other comprehensive income (OCI). In all cases, the option to elect an equity instrument at FVTOCI is made at initial recognition and is irrevocable, resulting in all gains and losses being presented in OCI except dividend income which is recognized in profit or loss (Deloitte, 2013).

Under IAS 39, based on how assets are classified, their measurement is determined. In contrast, Under IFRS 9, the basis on which assets are measured determines how they are classified (Table 5-1).

Table 5-1 IFRS 9 and IAS 39 classification and measurement categories

IAS 39 IFRS 9 Classifications Classifications and measurement models Measurement model Loans and receivables Amortized Cost Amortized Cost FVPL FVPL FVPL Available for sale FVOCI FVOCI Held to maturity Amortized Cost Source: PWC (2016)

Postgraduate Dissertation 44 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Reclassification of financial assets is compulsory between amortized cost, FVTPL, and FVTOCI. Reclassification within the scope of IFRS 9 is not allowed for financial liabilities, equity investments measured at FVTPL or FVTOCI, and/or financial assets measured at the fair value. If a financial asset is reclassified, the company should apply the reclassification from the reclassification date forward. 1 Finally, previously recognized gains, losses or interest are not reclassified (Table 5-2).

Table 5-2 Accounting for asset reclassifications

From To Requirement Amortized Cost FVPL Fair value measured at reclassification date and any difference between fair value and the amortized cost is recognized in P&L FVPL Amortized Fair value at the reclassification date becomes the Cost new gross carrying amount Amortized Cost FVOCI Fair value measured at reclassification date and any difference is recognized in OCI FVOCI Amortized Cumulative gain or loss previously recognized in Cost OCI is removed from equity and applied against the fair value of the financial asset at the reclassification date, FVPL FVOCI Asset continues to be measured at fair value, but subsequent gains and losses are recognized in OCI. FVOCI FVPL Asset continues to be recognized at fair value and the cumulative gain or loss previously recognized in OCI is reclassified from equity to P&L. Source: PWC (2016)

IFRS 9 specifies how to determine whether a business model manages financial assets seeking to collect contractual cash flows or to sell financial assets as well. When sales of financial assets are quite frequent and not insignificant in value (either individually or in aggregate), it should be assessed whether they are performed in the aim of collecting contractual cash lows. Further, this can be the case if such sales of financial assets are made close to maturity and the proceeds from the sales are roughly the amount of the

1 The reclassification date is the first day of the first reporting period following the change in business model that results in the entity reclassifying financial assets.

Postgraduate Dissertation 45 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” remaining contractual cash flows (Table 5-3). In fact, with this process, IFRS 9 assesses the entity’s business model for managing financial assets in relation to the classification of financial assets (Deloitte, 2013).

Table 5-3 IFRS 9 business model classifications

Holding to collect Holding to collect Other contractual cash contractual cash flows flows and sell Over-arching Collecting cash flows Collecting cash flows and Sales are integral, objective is fundamental, sales selling assets are both collecting cash flows are supplementary fundamental is supplementary Examples of In response to an As a part of liquidity Within a program of why sales increase in asset’s management, maintaining active buying and happen in each credit risk or to a specific interest yield selling to realize fair category manage credit profile or matching the values concentration risk maturity of financial assets and liabilities Illustrative B4.1.4 B4.1.4C B4.1.5 examples in IFRS 9 Source: PWC (2016)

Figure 5-1 shows how financial assets are classified and measured under IFRS 9.

Figure 5-1 Summary of classification and measurement model for financial assets Source: PWC (2016:12)

Postgraduate Dissertation 46 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Another consideration is that, under IFRS 9, the cost may be used as the basis for fair value measurement in limited situations - for instance, when there is not enough recent information available to estimate the fair value or when cost denotes the best estimate of fair value within an extensive range of probable fair value measurements. Also, although an entity is not allowed to recognize changes in the fair value of an FVOCI equity instrument in P&L, IFRS 9 allows changes in the fair value of FVOCI equity investments to be transferred directly from the equity account in OCI and to be accumulated in retained earnings. Table 5-4 summarizes the fair value designation options under IFRS 9.

Table 5-4 Fair value designation options under IFRS 9

Option Condition for applying IFRS 9 IAS 39 Eliminates or significantly reduces an accounting mismatch that otherwise would arise from measuring FVPL Yes Yes assets or liabilities or recognizing the gains and losses on them on different bases. A group of financial assets and/or financial liabilities whose performance is evaluated on a fair value basis, FVPL a documented risk management strategy. Also, No Yes information about the group is provided internally to key management personnel. Contract contains one or more embedded derivatives FVPL not closely related to the economic risks and No Yes characteristics of the host contract Any asset that otherwise would qualify for FVOCI No Yes measurement at Amortized Cost. Source: PWC (2016)

5.2.2 Financial liabilities measurement

Under IAS 39, the change in the fair value of financial liabilities is recognized in profit and loss. Under IFRS 9, financial liabilities held for trading, such as derivative liabilities, are measured at fair value with all changes being recognized in profit or loss. The FVTPL liabilities are recognized in OCI for the change in fair value attributable to changes in the company’s credit risk unless: OCI inclusion creates or enlarges an accounting mismatch in P&L or the liability is a financial guarantee contract or a loan commitment. Also, the IFRS 9 eliminated the cost exemption for derivative liabilities settled through unquoted equity instruments whose fair value cannot be determined firmly (PWC, 2016).

Postgraduate Dissertation 47 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 5-5 summarizes the key differences between IAS 39 and IFRS 9. The major changes that IFRS 9 introduces concern the classification and measurement of financial instruments. Further, it introduces the estimation of expected credit losses (ECL) model to unify different impairment methods to a single model that focuses on the probability of a loan default rather on incurred losses (as in the case of IAS 39).

Table 5-5 Differences between IAS 39 and IFRS 9

IAS 39 IFRS 9

The fair value. The amortized The amortized cost. Fair value cost value. Costs (for the Subsequent through other comprehensive share-based instruments, measurement income (FVOCI) or through profit or which do not have a reliable loss (FVTPL). fair value measurement). Fair value through profit or The amortized cost. Fair value Types of loss (FVTPL). Held-to-maturity through other comprehensive classification (HTM). Loans and receivables income (FVOCI) or through profit or (LAR). Available for sale (ASF). loss (FVTPL). Reclassification shall be Reclassification prohibited through profit or Change of business model. loss after initial recognition. All equity instruments The fair value of the instrument for Equity available for sale, are the purpose of trade. The irrevocable instruments classified at fair value through choice for the category through other other comprehensive income. comprehensive income. A unified model of impairment, Several models of impairment. which applies to all financial Impairment Incurred loss model. instruments. The model of Expected Credit Loss (ECL). Source: Ntaikou et.al. (2018)

5.3 Provisions determination before and after IFRS 9

Under IFRS 9, the impairment of loans is recognized in three stages (Figure 5-2):

Stage 1: expected credit losses generated by default events that take place following a loan purchase, are recognized within 12 months and establish a loss. Further, 12-month ECL on subsequent reporting dates applies to loans with no

Postgraduate Dissertation 48 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

substantial increase in credit risk since their initial recognition while the effective interest rate (EIR) is calculated on the gross carrying amount of the loan without deducting expected credit losses. A substantial increase in credit risk since initial recognition is determined by assessing the change in the risk of default over the expected life of the loan – in other words by comparing the change in the probability of default to the among of expected credit losses.

Stage 2: If the credit risk of a loan has increased substantially since initial recognition (on an individual or a collective basis) and is considered high, lifetime ECLs are recognized. The calculation of interest revenue is the same as for Stage 1.

Stage 3: - If the credit risk of a loan increases to the point where it is considered credit-impaired, interest revenue is calculated on the amortized cost (the gross carrying amount minus the loss allowance). Lifetime ECLs are recognized in the same way as in Stage 2.

Figure 5-2 IFRS 9 three-stage ECL model for impairment of financial assets Source: Ntaikou et.al. (2018)

Postgraduate Dissertation 49 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

5.3.1 Expected credit losses (ECL) model

A substantial increase in credit risk indicates a substantially higher probability of default. Under IFRS 9, an entity may use different approaches to estimate whether credit risk has increased significantly provided that the approach complies with the IFRS 9 requirements. This means that the approach should not explicitly state a probability of default occurring as an input, but rather provide a list of factors that may lead to an assessment of probability default. Also, although the assessment of a loss allowance should be based on an individual asset basis, some factors or indicators may be unavailable at an instrument level. Hence, under the expected credit losses (ECL) model, the allowance for credit losses is calculated by discounting the cash losses incurred in various default scenarios and multiplying these losses by the probability of each scenario occurring. The allowance for credit losses is the sum of these probability weighted outcomes (Ntaikou et al., 2018).

Within the scope of IFRS 9’s general impairment model, the allowance for expected credit losses (ECL) is calculated at a 12-month period and provided that, at the reporting date, the credit risk of a financial instrument has not increased significantly since initial recognition. The same holds true if the entity has selected the “low credit risk” operational simplification 2 or if the total level of credit risk is low. In the opposite case where credit risk has increased significantly since initial recognition, the credit loss allowance is measured at lifetime expected credit losses instead of at a 12-month period (Grant Thornton, 2016) (Figure 5-3).

2 An entity may assume that the credit risk on a financial instrument has not increased significantly since initial recognition if the financial instrument is determined to have low credit risk at the reporting date. This is an optional simplification and is designed to relieve entities from tracking changes in the credit risk of high-quality assets.

Postgraduate Dissertation 50 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Figure 5-3 Impact of a significant increase in credit risk Source: Grant Thornton (2016:9)

Postgraduate Dissertation 51 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

6.

Although most Greek banks were not exposed to "toxic products", like in the case of US and European banks, the prolonged recession of the Greek economy has dramatically increased non-performing loans. Both macroeconomic and bank-related factors are responsible for NPLs, but macro variables, such as GDP, consumer spending, government spending, unemployment rate, inflation, and interest rates can better explain non- performing loans.

6.1 Gross Domestic Product (GDP)

Gross Domestic Product (GDP) is the sum of all goods produced by an economy over a period of one year, and it is calculated as the sum of consumption (C), investment (I), government spending (G), and net exports (NX). GDP growth is positively related to non- performing loans. Generally, when an economy shows a positive GDP rate it means that the economy is growing, and household income is enough for consumers to cover their debts. As GDP grows, consumer spending is rising, leading to new loan applications. Following the 2008 crisis, NPLs dramatically increased as Greek consumers were unable to service their debt (Figure 6-1).

Postgraduate Dissertation 52 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Greece NPLs and GDP growth (2008-2017) 50,00%

40,00%

30,00%

20,00%

10,00%

0,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 -10,00%

NPLs GDP

Figure 6-1 Greece NPLs and GDP growth (2008-2017) Source: World Bank (2019) and own work

6.2 Consumer spending

Consumer spending represents voluntary private household consumption and/or money exchange for durable goods, non-debit goods, and services. In a free economy, the level of private consumption expenditure is equal to the total market value of economic output. In the supply and demand equation, consumer spending is the demand side and output is the supply side. When economists or policymakers report total demand, they refer to the combined market value of all consumer spending in a given economy at a specific price level.

As seen in Figure 6-2, consumer spending as a percentage of GDP is positively correlated with non-performing loans, as when consumer spending increases, the economy is growing, and consumers can service their debt.

Postgraduate Dissertation 53 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Greece NPLs and consumer spending (% GDP)

90,00% (2008-2017) 80,00% 70,00% 60,00% 50,00% 40,00% 30,00% 20,00% 10,00% 0,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 -10,00% NPLs Consumer spending (% GDP)

Figure 6-2 Greece NPLs and consumer spending (% GDP) (2008-2017) Source: World Bank (2019) and own work

6.3 Government spending

General government expenditure as a percentage of GDP is an indication of the size of the government in a country as it includes expenditure by central, state, and local governments and social security funds. The wide variation of this indicator highlights the diversity of countries' approaches to the provision of public goods and services and the provision of social protection.

Government spending as a percentage of GDP is inversely related to NPLs because when the government downsizes spending means that the economy is not growing, and consumers cannot pay off their debts (Figure 6-3).

Postgraduate Dissertation 54 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Greece NPLs and government spending (% GDP) (2008-2017) 50,00%

40,00%

30,00%

20,00%

10,00%

0,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 -10,00% NPLs Government spending (% GDP)

Figure 6-3 Greece NPLs and government spending (% GDP) (2008-2017) Source: World Bank (2019) and own work

6.4 Unemployment rate and inflation rate

The unemployment rate represents the number of unemployed as a percentage of the total labor force, which consists of the unemployed plus those who receive a base pay or are self-employed. Unemployed people are available for work and have taken active measures to find a job over the last four weeks. When unemployment is high, and some people are discouraged and stop looking for work, then they are excluded from the workforce. This means that the unemployment rate can be reduced or stable increasing, although there has been no significant improvement in the labor market.

Inflation is the rate of increase in the general price level for goods and services. Central banks are trying to curb inflation - and avoid deflation - in order to keep the economy stable, growing at a smooth pace. With the onset of the recent financial crisis, central banks used monetary policy instruments to control inflation. The US Federal Reserve maintained interest rates close to zero and followed a bond purchase program known as quantitative easing.

Unemployment is positively associated with non-performing loans, as when unemployment rises, it means that the economy is not growing, and consumers cannot pay off their debts (Figure 6-4). In contrast, inflation is inversely related to non-performing

Postgraduate Dissertation 55 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” loans, as when inflation decreases, the supply of money to the economy is reduced and consumers are unable to service their debts (Figure 6-5).

Greece NPLs and unemployment rate (2008-2017) 48,00%

38,00%

28,00%

18,00%

8,00%

-2,00% 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 NPLs Unemployment

Figure 6-4 Greece NPLs and unemployment rate (2008-2017) Source: World Bank (2019) and own work

Greece NPLs and inflation rate (2008-2017)

45,00%

35,00%

25,00%

15,00%

5,00%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 -5,00%

NPLs Inflation

Figure 6-5 Greece NPLs and inflation rate (2008-2017) Source: World Bank (2019a) and own work

Postgraduate Dissertation 56 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

6.5 Interest rates

Interest rates represent the percentage of the capital a lender offers to a borrower for the use of assets. Interest rates are applied in many lending situations as consumers borrow money to buy homes, to fund tuition, fees, to start a business, etc. Businesses receive loans to fund capital projects and expand their operations by buying fixed and long-term assets such as land, buildings, machinery, trucks, etc. The money borrowed must be reimbursed either as a lump sum on a predetermined date or in monthly installments. The money to be repaid exceeds the amount of borrowing, as the lenders want to be compensated for their loss of money during the loan and cover the opportunity cost (for example, the lender could invest the funds instead of lending them). The difference between the total repayment amount and the principal is the interest payable, calculated based on the interest rate applicable to the amount of the principal. Banks typically charge higher interest rates to revolving loans, like credit cards because this type of loans is more expensive to manage as well as to riskier customers who may not be able to fully cover their debt.

As seen in Figure 6-6, interest rates are inversely related to non-performing loans. This is because lending rates tend to adversely affect the quality of assets by determining the level of non-performing loans.

Greece NPLs and interest rates (2008-2017)

45,00%

35,00%

25,00%

15,00%

5,00%

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 -5,00%

NPLs Interest rates

Figure 6-6 Greece NPLs and interest rates (2008-2017) Source: World Bank (2019) and own work

Postgraduate Dissertation 57 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

The Greek economy is an interesting case to study the determinant of NPLs, given the recessionary conditions that drive the economy since 2008. In 2009, GDP fell by 4.30% and NPLs increased by 6.95%. In 2010, financial markets started losing confidence in Greece and the ability of its economy to service its huge public debt. Upon receipt of the first bailout from the European union and the IMF, Greece’s GDP fell by 5.48% causing an increase in the NPLs to 9.12%. Further recessionary pressures, rapidly surged NPLs to 14.43% in 2011, 23.27% in 2012. The upward trend of the NPLS continues through 2017 (45.57% of total gross loans) whereas GDP gradually improves but remains negative in 2015 and 2016 (Table 6-1).

Over the period 2008-2017, NPLs grew by 40.9% from 4.67% to 45.57%, GDP grew by 1.84% from -0.34% to 1.51%, consumer spending as a percentage of GDP grew by 1.33% from 67.37% to 68.70%, government spending as a percentage of GPD fell by 0.91% from 20.44% to 19.81%, unemployment rate grew by 14.20% from 7.80% to 22.00%, inflation fell by 1.32% from 1.97% to 0.65%, and interest rates fell by 2.59% from 7.03% to 4.44% (Table 6-1).

It is seen that when unemployment surges in 2012 (24.44%) and 2013 (27.47%), NLPs hit high to 23.27% and 31.90% respectively. Also, when inflation hits its low in 2015 (- 0.17%), NPLS hit their high, 36.65%. Finally, in 2015, interest rates are at their lowest rate over the investigated period, 5.09%, and NPLs are at their highest rate, 36.65% (Table 6-1).

Table 6-1 Macroeconomic factors and NPLs in Greece (2008-2017)

2008 2009 2010 2011 2012

NPLs (% total gross loans) 4.67% 6.95% 9.12% 14.43% 23.27% GDP growth -0.34% -4.30% -5.48% -9.13% -7.30% Consumer spending (% GDP) 67.37% 68.13% 69.37% 69.88% 69.91% Government spending (% GDP) 20.72% 23.31% 22.20% 21.79% 21.74% Unemployment 7.80% 9.62% 12.71% 17.86% 24.44% Inflation 1.97% 2.64% 5.17% 2.42% 0.80% Interest rates 7.03% 5.83% 5.51% 6.21% 6.03% 2013 2014 2015 2016 2017 NPLs (% total gross loans) 31.90% 33.78% 36.65% 36.30% 45.57% GDP growth -3.24% 0.74% -0.44% -0.19% 1.51%

Postgraduate Dissertation 58 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Consumer spending (% GDP) 70.77% 70.21% 69.44% 69.18% 68.70% Government spending (% GDP) 20.44% 20.28% 20.30% 20.06% 19.81% Unemployment 27.47% 26.49% 24.90% 23.50% 22.00% Inflation -1.71% -2.61% -0.17% 0.02% 0.65% Interest rates 5.71% 5.43% 5.09% 5.16% 4.44% Source: World Bank, Inflation.eu (2019a)

Postgraduate Dissertation 59 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

7.

In the first part of this chapter, an empirical analysis of the impact on the 4 Greek systemic banks’ assets, liabilities and equity after the IFRS 9 application, will be presented. The data base used is the respective annual reports and the software used to derive the calculations and graphs is MS Excel. In the second part of the chapter, several strategies that the banks intend to use in order to reduce their NPEs, will be referred.

7.1 The impact of IFRS 9 on the Greek NPEs

7.1.1 Alpha Bank

Within 2018, Alpha Bank recognized the transfer of €34,159 of Greek corporate bonds from Level 1 to Level 2 following an above-the limit increase of the liquidity margin set for the classification of the market as active. Further, government bonds of €69,842 in value were transferred from Level 2 to Level 1 following the in-the-limit movement of the liquidity margin set for the classification of the market as active. Also, a bond of €10,457 bond and a derivative of €10,643 were transferred from Level 3 to Level 2, since observable parameters were used for valuation purposes. Listed shares of €1,113 in value were transferred from Level 3 to Level 1 due to their valuation on the stock exchange value. With respect to debt restructuring, Alpha Bank acquired the option to purchase a stake in its share capital, recognizing a derivative with a fair value of €14,097 (31.12.2017: € 14,812).

During 2017, a €22,971 bond was transferred from Level 2 to Level 3 since non- observable parameters were used for valuation purposes and a bond of €10 was transferred from Level 3 to Level 2 since observable parameters were used for valuation purposes.

The impact of IFRS 9 on the financial assets, financial liabilities, and equity of Alpha Bank is seen both in 2018 and 2017 figures (See Appendix). The valuation impact on financial assets under IFRS 9 amounts to €1.03 billion, decreasing financial assets from

Postgraduate Dissertation 60 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

€60.81 billion in 2017 to €59.77 billion in 2018 (-1.7%). Further, the valuation impact on financial liabilities amounts to €109.2 million, increasing financial liabilities from €51.18 billion in 2017 to €51.29 billion in 2018 (+0.2%). Finally, the valuation impact on total equity amounts to €1.14 billion, decreasing total equity from €9.63 billion in 2017 to €8.48 billion in 2018 (-11.9%). No other changes are seen in the remaining basic figures following the adoption of IFRS 9 (Table 7-1).

By restating the amounts following the IFRS 9 impact, Alpha Bank’s net interest margin, equity/total assets, and equity/total liabilities ratios have increased compared to IAS 39 whereas ROE has decreased (Table 7-2).

Table 7-1 Alpha Bank recalculation of basic figures under IFRS 9

UNDER IAS 39 2018 2017 Diff (€) Diff (%) Total assets 61,006.7 60,813.0 193.7 0.3% Total equity 8,143.1 9,626.7 - 1,483.6 -15.4% Total liabilities 52,863.6 51,186.3 1,677.3 3.3% Loans 40,228.3 43,318.2 - 3,089.9 -7.1% Deposits 38,731.8 34,890.4 3,841.4 11.0% Loan Loss Provisions 1,730.6 1,005.4 725.2 72.1% Net interest income 1,756.0 1,942.6 - 186.5 -9.6% Operating revenue 2,604.9 2,466.7 138.2 5.6% Operating expenses 1,162.4 1,293.0 - 130.7 -10.1% Net profit 53.0 89.5 - 36.6 -40.8% UNDER IFRS 9 2018 2017 Diff (€) Diff (%) Total assets 59,774.7 60,807.8 - 1,033.1 -1.7% Total equity 8,484.4 9,626.7 - 1,142.3 -11.9% Total liabilities 51,290.3 51,181.1 109.2 0.2% Loans 40,228.3 43,318.2 - 3,089.9 -7.1% Deposits 38,731.8 34,890.4 3,841.4 11.0% Loan Loss Provisions 1,730.6 1,005.4 725.2 72.1% Net interest income 1,756.0 1,942.6 - 186.5 -9.6% Operating revenue 2,604.9 2,466.7 138.2 5.6% Operating expenses 1,162.4 1,293.0 - 130.7 -10.1% Net profit 53.0 89.5 - 36.6 -40.8% Source: Alpha Bank annual report (2018) and own calculations

Postgraduate Dissertation 61 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Table 7-1 Alpha Bank recalculation of ratios under IFRS 9

UNDER IAS 39 2018 2017 Diff ROA (return on assets) 0.09% 0.15% -0.06% ROE (return on equity) 0.65% 0.93% -0.28% NIM (net interest 2.88% 3.19% -0.32% Equitymargin) / Total Assets 13.35% 15.83% -2.48% Equity / Total Liabilities 15.40% 18.81% -3.40% UNDER IFRS 9 2018 2017 Diff ROA (return on assets) 0.09% 0.15% -0.06% ROE (return on equity) 0.62% 0.93% -0.31% NIM (net interest 2.94% 3.19% -0.26% Equitymargin) / Total Assets 14.19% 15.83% -1.64% Equity / Total Liabilities 16.54% 18.81% -2.27% Source: Alpha Bank annual report (2018) and own calculations Following IFRS 9, Alpha Bank’s loans decreased by 7.1% from €43.32 billion in 2017 to €40.23 billion in 2018 and deposits increased by 11.0% from €34.89 billion in 2017 to €38.73 billion in 2018 (Figure 7-1).

Alpha Bank Loans and Deposits (2017 & 2018)

38.731,8 Deposits 34.890,4

40.228,3 Loans 43.318,2

- 5.000,0 10.000,0 15.000,0 20.000,0 25.000,0 30.000,0 35.000,0 40.000,0 45.000,0

2018 2017

Figure 7-1 Alpha Bank loans and deposits (2017 & 2018) Source: Alpha Bank annual report (2018) and own work

If the demand for loans is higher than the demand for deposits, the net interest margin tends to increase. This rule of thumb applies in the case of Alpha Bank as the net interest

Postgraduate Dissertation 62 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” margin increased from 2.88% to 2.94% following IFRS 9 recalculation and the demand for loans is higher than the demand of deposits (Figure 7-2).

Alpha Bank demand for loans and deposits (2017 & 2018) 50.000,0 43.318,2 45.000,0 40.228,3 38.731,8 40.000,0 34.890,4 35.000,0 30.000,0 25.000,0 20.000,0 15.000,0 10.000,0 5.000,0 - 2017 2018

Loans Deposits

Figure 7-1 Alpha Bank demand for loans and deposits (2017 & 2018) Source: Alpha Bank annual report (2018) and own work The equity/total assets and equity/total liabilities ratios indicate the percentage that Alpha Bank is funding its total assets and total liabilities by equity. As seen in Figure 7-3, both ratios are way below 100%, which means that the bank’s assets and liabilities are mainly financed with debt. Also, following the IFRS 9 implementation both ratios have slightly deteriorated.

Alpha Bank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018)

20,00% 18,81% 18,00% 16,54% 15,83% 16,00% 14,19% 14,00% 12,00% 10,00% 8,00% 6,00% 4,00% 2,00% 0,00% Equity / Total Assets Equity / Total Liabilities 2017 2018

Figure 7-2 Alpha Bank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018)

Postgraduate Dissertation 63 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Source: Alpha Bank annual report (2018) and own work

7.1.2 Eurobank

Eurobank adopted IFRS 9 in the first quarter of 2018 and applied the Exemption of the Standard allowing non-reclassification of comparatives of the previous period. Consequently, the Bank's comparative figures for 2017 are presented in accordance with IAS 39.

The valuation impact on financial assets under IFRS 9 amounts to €2.75 billion, decreasing financial assets from €51.45 billion in 2017 to €48.70 billion in 2018 (-5.3%). Financial liabilities decreased by €962.0 million, from €45.01 billion to €44.04 billion in 2018 (-2.1%). The valuation impact on total equity amounts to €1.79 billion, decreasing total equity from €6.44 billion to €4.65 billion (-27.8%). Loans decreased by €921.0 million from €30.87 billion to €29.95 billion (-3.0%), loan loss provisions increased by €27 million from €716 million to €743 million (+3.8%), operating revenues decreased by €1.06 billion from €1.51 billion to €441,2 million (-70.7%), and operating expenses increased by €411.7 million from €672.0 million to €1.08 billion (+61.3%). No changes are seen in deposits, net interest income, and net profit (Table 7-3).

Table 7-3 Eurobank recalculation of basic figures under IFRS 9

UNDER IAS 39 2018 2017 Diff ( €) Diff (%) Total assets 50,275.0 51,448.0 - 1,173.0 -2.3% Total equity 4,378.0 6,442.0 - 2,064.0 -32.0% Total liabilities 45,897.0 45,006.0 891.0 2.0% Loans 29,354.0 30,866.0 - 1,512.0 -4.9% Deposits 29,135.0 25,015.0 4,120.0 16.5% Loan Loss Provisions 606.0 716.0 - 110.0 -15.4% Net interest income 1,055.0 1,100.0 - 45.0 -4.1% Operating revenue 1,464.0 1,507.0 - 43.0 -2.9% Operating expenses 664.0 672.0 - 8.0 -1.2% Net profit 33.0 11.0 22.0 200.0% UNDER IFRS 9 2018 2017 Diff ( €) Diff (%) Total assets 48,696.0 51,448.0 - 2,752.0 -5.3% Total equity 4,652.0 6,442.0 - 1,790.0 -27.8% Total liabilities 44,044.0 45,006.0 - 962.0 -2.1% Loans 29,945.0 30,866.0 - 921.0 -3.0% Deposits 29,135.0 25,015.0 4,120.0 16.5% Loan Loss Provisions 743.0 716.0 27.0 3.8%

Postgraduate Dissertation 64 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Net interest income 1,055.0 1,100.0 - 45.0 -4.1% Operating revenue 441.2 1,507.0 - 1,065.8 -70.7% Operating expenses 1,083.7 672.0 411.7 61.3% Net profit 33.0 11.0 22.0 200.0% Source: Eurobank annual report (2018) and own calculations

By recalculating ratios, net interest margin, equity/total assets, and equity/total liabilities ratios have increased while ROE has decreased compared to IAS 39 (Table 7-4).

Table 7-4 Eurobank recalculation of ratios under IFRS 9

UNDER IAS 39 2018 2017 Diff ROA (return on assets) 0.07% 0.02% 0.04% ROE (return on equity) 0.75% 0.17% 0.58% NIM (net interest margin) 2.10% 2.14% -0.04% Equity / Total Assets 8.71% 12.52% -3.81% Equity / Total Liabilities 9.54% 14.31% -4.77% UNDER IFRS 9 2018 2017 Diff ROA (return on assets) 0.07% 0.02% 0.05% ROE (return on equity) 0.71% 0.17% 0.54% NIM (net interest margin) 2.17% 2.14% 0.03% Equity / Total Assets 9.55% 12.52% -2.97% Equity / Total Liabilities 10.56% 14.31% -3.75% Source: Eurobank annual report (2018) and own calculations Following IFRS 9, Eurobank’s loans decreased by 3.0% from €30.87 billion in 2017 to €29.94 billion in 2018 and deposits increased by 16.5% from €25.01 billion to €29.13 billion (Figure 7-4).

Postgraduate Dissertation 65 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Eurobank Loans and Deposits (2017 & 2018)

29.135,0 Deposits 25.015,0

29.945,0 Loans 30.866,0

- 5.000,0 10.000,0 15.000,0 20.000,0 25.000,0 30.000,0 35.000,0 40.000,0 45.000,0

2018 2017

Figure 7-4 Eurobank loans and deposits (2017 & 2018) Source: Eurobank annual report (2018) and own work

The demand for loans in Eurobank is higher than the demand for deposits (Figure 7-5). Hence, the net interest margin should increase. This rule of thumb applies in the case of Eurobank as the net interest margin increased from 2.10% to 2.17% following IFRS 9 adoption.

Eurobank demand for loans and deposits (2017 & 2018)

35.000,0 30.866,0 29.945,0 29.135,0 30.000,0 25.015,0 25.000,0

20.000,0

15.000,0

10.000,0

5.000,0

- 2017 2018 Loans Deposits

Figure 7-5 Eurobank demand for loans and deposits (2017 & 2018) Source: Eurobank annual report (2018) and own work

Postgraduate Dissertation 66 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Based on Eurobank’s equity/total assets and equity/total liabilities ratios, the Bank is funding its total assets and total liabilities mostly by debt. As seen in Figure 7-6, both ratios have deteriorated following the implementation of IFRS 9 and are way lower than 100%.

Eurobank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) 16,00% 14,31% 14,00% 12,52% 12,00% 10,56% 9,55% 10,00% 8,00% 6,00% 4,00% 2,00% 0,00% Equity / Total Assets Equity / Total Liabilities 2017 2018

Figure 7-6 Eurobank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) Source: Eurobank annual report (2018) and own work

7.1.3 National Bank of Greece

IFRS 9 adoption decreased NBG’s equity by €1.5 billion, of which €1.3 billion are attributed to changes in impairment requirements and €0.2 billion to classification and measurement (see Appendix).

Following the IFRS 9 adoption, NBG’s financial assets decreased by €3.34 billion from €52.32 billion in 2017 to €48.98 billion in 2018 (-6.4%). Financial liabilities decreased by €1.80 billion from €53.60 billion to €51.80 billion (-9.7%). Loans decreased by €6.97 billion from €37.94 billion to €30.97 billion (-18.4%), deposits decreased by €2.76 billion from €43.03 billion to €40.27 billion (-6.4%), and loan loss provisions increased by €1.22 billion from €10.25 billion to €11.48 billion (+12.0%). No changes are seen in equity, operating revenues, operating expenses, and net profit (Table 7-5).

Postgraduate Dissertation 67 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

By restating the financial ratios, NBG’s net interest margin, equity/total assets, and equity/total liabilities ratios have increased and ROA has decreased compared to IAS 39 (Table 7-6).

Table 7-5 NBG recalculation of basic figures under IFRS 9

UNDER IAS 39 2018 2017 Diff (€) Diff (%) Total assets 65,095.0 64,768.0 327.0 0.5% Total equity 5,638.0 7,379.0 - 1,741.0 -23.6% Total liabilities 59,457.0 57,389.0 2,068.0 3.6% Loans 30,134.0 37,941.0 - 7,807.0 -20.6% Deposits 43,027.0 40,265.0 2,762.0 6.9% Loan Loss Provisions 312.0 807.0 - 495.0 -61.3% Net interest income 1,094.0 1,532.0 - 438.0 -28.6% Operating revenue 1,320.0 1,594.0 - 274.0 -17.2% Operating expenses 834.0 828.0 6.0 0.7% Net profit - 50.0 - 412.0 362.0 -87.9% UNDER IFRS 9 2018 2017 Diff (€) Diff (%) Total assets 48,976.0 52,321.0 - 3,345.0 -6.4% Total equity 5,638.0 7,379.0 - 1,741.0 -23.6% Total liabilities 51,796.0 53,596.0 - 1,800.0 -3.4% Loans 30,972.0 37,941.0 - 6,969.0 -18.4% Deposits 40,265.0 40,265.0 - 0.0% Loan Loss Provisions 11,476.0 10,251.0 1,225.0 12.0% Net interest income 1,094.0 1,532.0 - 438.0 -28.6% Operating revenue 1,320.0 1,594.0 - 274.0 -17.2% Operating expenses 834.0 828.0 6.0 0.7% Net profit - 50.0 - 412.0 362.0 -87.9% Source: NBG annual report (2018) and own calculations

Table 7-6 National Bank of Greece recalculation of ratios under IFRS 9

UNDER IAS 39 2018 2017 Diff. ROA (return on assets) -0.08% -0.64% 0.56% ROE (return on equity) -0.89% -5.58% 4.70% NIM (net interest margin) 1.68% 2.37% -0.68% Equity / Total Assets 8.66% 11.39% -2.73% Equity / Total Liabilities 9.48% 12.86% -3.38% UNDER IFRS 9 2018 2017 Diff ROA (return on assets) -0.10% -0.79% 0.69%

Postgraduate Dissertation 68 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

ROE (return on equity) -0.89% -5.58% 4.70% NIM (net interest margin) 2.23% 2.93% -0.69% Equity / Total Assets 11.51% 14.10% -2.59% Equity / Total Liabilities 10.89% 13.77% -2.88% Source: NBG annual report (2018) and own calculations

Following IFRS 9 adoption, Eurobank’s loans decreased by 18.4% from €37.94 billion in 2017 to €30.97 billion in 2018 while deposits remained unchanged to €40.26 billion (Figure 7-7).

NBG Loans and Deposits (2017 & 2018)

40.265,0 Deposits 40.265,0

30.972,0 Loans 37.941,0

- 5.000,0 10.000,0 15.000,0 20.000,0 25.000,0 30.000,0 35.000,0 40.000,0 45.000,0

2018 2017

Figure 7-7 NBG loans and deposits (2017 & 2018) Source: National Bank of Greece annual report (2018) and own work

The demand for loans in NBG is lower than the demand for deposits (Figure 7-8). Hence, the net interest margin should decrease. However, this rule of thumb does not apply in the case of NBG as the net interest margin increased from 1.68% to 2.23% following IFRS 9 recalculation.

Postgraduate Dissertation 69 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

NBG demand for loans and deposits (2017 & 2018)

45.000,0 40.265,0 40.265,0 40.000,0 37.941,0

35.000,0 30.972,0 30.000,0 25.000,0 20.000,0 15.000,0 10.000,0 5.000,0 - 2017 2018 Loans Deposits

Figure 7-8 NBG demand for loans and deposits (2017 & 2018) Source: Eurobank annual report (2018) and own work Based on NBG’s equity/total assets and equity/total liabilities ratios, the Bank is funding its total assets and total liabilities mostly by debt. As seen in Figure 7-9, both ratios have deteriorated following the implementation of IFRS 9 and are way lower than 100%.

NBG Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018)

14,00% 12,86% 11,39% 12,00% 10,89% 9,82% 10,00%

8,00%

6,00%

4,00%

2,00%

0,00% Equity / Total Assets Equity / Total Liabilities 2017 2018

Figure 7-9 NBG Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) Source: National Bank of Greece annual report (2018) and own work

Postgraduate Dissertation 70 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

7.1.4 Piraeus Bank

IFRS 9 adoption in Piraeus Bank addressed the accounting requirements for financial instruments classification and measurement (See Appendix).

Following the IFRS 9 adoption, Piraeus Bank’s financial assets decreased by €1.9 billion from €49.17 billion in 2017 to €47.27 billion in 2018 (-3.9%). Financial liabilities decreased by €2.66 billion from €39.62 billion to €36.96 billion (-6.7%). Equity increased by €763.8 million from €9.54 billion to €10.31 billion (+8.0%). Loans increased by €118.0 million from €44.61 billion to €44.72 billion (+0.3%), and loan loss provisions increased by €1.78 billion from €15.60 billion to €17.39 billion (+11.4%). No changes are seen in deposits, net interest income, operating revenues, operating expenses, and net profit (Table 7-7).

By restating the financial ratios, Piraeus Bank’s ROA net interest margin, equity/total assets, and equity/total liabilities ratios have increased while ROE has decreased compared to IAS 39 (Table 7-8).

Table 7-7 Piraeus Bank recalculation of basic figures under IFRS 9

UNDER IAS 39 2018 2017 Diff (€) Diff (%) Total assets 61,880.0 67,416.6 - 5,536.6 -8.2% Total equity 7,506.0 9,544.2 - 2,038.2 -21.4% Total liabilities 54,374.0 57,872.4 - 3,498.4 -6.0% Loans 39,757.0 44,719.5 - 4,962.5 -11.1% Deposits 44,739.0 42,715.3 2,023.7 4.7% Loan Loss Provisions 532.0 2,020.0 - 1,488.0 -73.7% Net interest income 1,410.0 1,639.0 - 229.0 -14.0% Operating revenue 1,882.0 2,146.0 - 264.0 -12.3% Operating expenses 1,161.0 1,106.0 55.0 5.0% Net profit 173.0 -13.0 186.0 -1430.8% UNDER IFRS 9 2018 2017 Diff (€) Diff (%) Total assets 47,268.0 49,168.0 - 1,900.0 -3.9% Total equity 10,308.0 9,544.2 763.8 8.0% Total liabilities 36,960.0 39,623.8 - 2,663.8 -6.7% Loans 44,720.0 44,602.0 118.0 0.3% Deposits 44,739.0 42,715.3 2,023.7 4.7% Loan Loss Provisions 17,386.0 15,601.0 1,785.0 11.4% Net interest income 1,410.0 1,639.0 - 229.0 -14.0%

Postgraduate Dissertation 71 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Operating revenue 1,882.0 2,146.0 - 264.0 -12.3% Operating expenses 1,161.0 1,106.0 55.0 5.0% Net profit 173.0 - 13.0 186.0 -1430.8% Source: Piraeus Bank (2018) and own calculations

Table 7-8 Piraeus Bank recalculation of ratios under IFRS 9

UNDER IAS 39 2018 2017 Diff. ROA (return on assets) 0.28% -0.02% 0.30% ROE (return on equity) 2.30% -0.14% 2.44% NIM (net interest margin) 2.28% 2.43% -0.15% Equity / Total Assets 12.13% 14.16% -2.03% Equity / Total Liabilities 13.80% 16.49% -2.69% UNDER IFRS 9 2018 2017 Diff. ROA (return on assets) 0.37% -0.03% 0.39% ROE (return on equity) 1.68% -0.14% 1.81% NIM (net interest margin) 2.98% 3.33% -0.35% Equity / Total Assets 21.81% 19.41% 2.40% Equity / Total Liabilities 27.89% 24.09% 3.80% Source: Piraeus Bank (2018) and own calculations

Following IFRS 9 adoption, Piraeus Bank’s loans increased by 0.3% from €44.61 billion in 2017 to €44.72 billion in 2018 while deposits increased by 4.7% from €44.60 billion to €44.72 billion (Figure 7-10).

Postgraduate Dissertation 72 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Piraeus Bank Loans and Deposits (2017 & 2018)

44.739,0 Deposits 42.715,3

44.720,0 Loans 44.602,0

- 5.000,0 10.000,0 15.000,0 20.000,0 25.000,0 30.000,0 35.000,0 40.000,0 45.000,0 50.000,0

2018 2017

Figure 7-10 Piraeus Bank loans and deposits (2017 & 2018) Source: National Bank of Greece annual report (2018) and own work

The demand for loans in Piraeus Bank is higher than the demand for deposits (Figure 7- 11). Hence, the net interest margin should increase. This rule of thumb applies in the case of Piraeus Bank as the net interest margin increased from 2.28% to 2.98% following IFRS 9 recalculation.

Piraeus Bank demand for loans and deposits (2017 & 45.000,0 44.720,0 44.739,0 44.602,0 2018) 44.500,0

44.000,0

43.500,0

43.000,0 42.715,3

42.500,0

42.000,0

41.500,0 2017 Loans Deposits 2018

Figure 7-11 Piraeus Bank demand for loans and deposits (2017 & 2018) Source: Piraeus Bank (2018) and own calculations Based on Piraeus Bank’s equity/total assets and equity/total liabilities ratios, the Bank is funding its total assets and total liabilities mostly by debt. As seen in Figure 7-12, both

Postgraduate Dissertation 73 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” ratios have improved following the implementation of IFRS 9 abut are way lower than 100%.

Piraeus Bank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018)

30,00% 27,89%

24,09% 25,00% 21,81% 19,41% 20,00%

15,00%

10,00%

5,00%

0,00% Equity / Total Assets Equity / Total Liabilities 2017 2018

Figure 7-12 Piraeus Bank Equity/Total Assets & Equity/Total Liabilities ratios (2017 & 2018) Source: Piraeus Bank (2018) and own calculations Table 7-9 Summary of IFRS 9 impact on basic figures in four banks

2018 Provisions Total Assets Loans Deposits UNDER IAS 39 Alpha Bank 1,730.6 61,006.7 40,228.3 38,731.8 Eurobank 606.0 50,275.0 29,354.0 29,135.0 NBG 312.0 65,095.0 30,134.0 43,027.0 Piraeus Bank 532.0 61,006.7 39,757.0 44,739.0 UNDER IFRS 9 Alpha Bank 1,730.6 59,774.7 40,228.3 38,731.8 Eurobank 743.0 48,696.0 29,945.0 29,135.0 NBG 11,476.0 48,976.0 30,972.0 40,265.0 Piraeus Ba nk 17,386.0 47,268.0 44,720.0 44,739.0 Diff ( €m) Alpha Bank - (1,232.0) - - Eurobank 137.0 (1,579.0) 591.0 - NBG 11,164.0 (16,119.0) 838.0 (2,762.0) Piraeus Bank 16,854.0 (13,738.7) 4,963.0 - Diff (%) Alpha Bank 0.0% -2.0% 0.0% 0.0% Eurobank 22.6% -3.1% 2.0% 0.0% NBG 3578.2% -24.8% 2.8% -6.4% Piraeus Bank 3168.0% -22.5% 12.5% 0.0% Source: Annual Reports (2018) and own calculations

Postgraduate Dissertation 74 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

7.2 Strategies to reduce NPEs

According to the Bank of Greece (2018), non-performing loans in the Greek are gradually declining. At the end of September 2018, NPEs amounted at €84.7 billion, having recorded a decline of €9.7 billion from December 2017 and of €22.5 billion from their March 2016 peak. NPE reduction in 2018 can be attributed to €4.4 billion of loan write- offs and €5.2 billion of loan sales.

Despite the improvement in the broader economic and institutional environment, NPE recovery remains limited. At the end of 2018, non-performing loans amounted to €81.8 billion, down by €12.7 billion compared to the end of 2017 and €25.4 billion compared to March 2016. Of these, 47.2% relate to loan agreements already denounced by banks, 30.6% to "unlikely to pay" loans and 22.2% to loans overdue longer than 90 days, which have not yet been terminated (Naftermporiki, 2019).

Based on the trends observed since 2016, the pace of NPE reduction is not sufficient to lead to a substantial decrease in the stock still outstanding. In order to accelerate the NPE reduction and support growth, the Greek banks have submitted their revised operational targets for NPE reduction ratio below 20% through 2021. It is estimated, that at the end of 2021 NPEs will be below €30.0 billion, down by 12.0% compared to €34.1 billion, which was the end-September 2018 target (Naftermporiki, 2019).

The main idea focuses on the transfer of a significant portfolio of non-performing loans from the systemic balance sheets to one or more Special Purpose Vehicle that could be created for this purpose after the relevant approvals (Ministry of Economy, Supervisory Authorities, European Competition Authority, etc.) (Bank of Greece, 2018a).

In the coming years, NPL sales, collections, and collateral liquidation are expected to play a key role leading to a decrease of NPEs as a percentage of total exposures to 20% or lower by 2021. However, for this target to be achieved, other strategies should be considered so that Greek banks are able to transfer NPEs from their balance sheets to Special Purpose Vehicles while managing fiscal risk and mitigating the impact on their capital base.

A major fiscal strategy is the legislation on the protection of the first residence. This is a very important step towards a complete reform of the legal framework for the overall

Postgraduate Dissertation 75 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” treatment of insolvency of households. The new legislation contains specific eligibility conditions and safety measures designed to protect the most vulnerable social groups while ensuring the avoidance of moral hazard to consistent debtors and the controlled impact on banks' capital base (Tzortzi, 2019).

Another consideration is the conflicts of interest created in the NPL operating model as a result of the ECB’s objective to detach the units responsible for loan origination (households) from those in charge of NPL management (banks). Banks can help to cope with these conflicts to reduce non-performing loans by providing adequate information about their risk management practices and balance sheet data as well as any sanctions in case of unlawful actions. In doing so, they can contribute to accelerating plans to reduce NPEs and to improve the quality of the capital of Greek banks.

According to Karamouzis (2016), the challenge for Greek banks today is not capital adequacy but a strong management tenacity, along with a proper restructuring and bankruptcy framework. These improvements will allow banks to effectively use their stock of provisions and collaterals to clean up NPE portfolios. To that end, the Bank of Greece suggests the transfer of part of the deferred tax assets (DTCs), which is recorded in the bank's balance sheets, to Special Purpose Vehicles, especially for loans that are extremely delayed and deteriorate the banks’ portfolios. This strategy is expected to allow for a substantial reduction of the NPEs without the need for share capital increases. More explicitly, the strategy provides for a reduction of NPEs by 50% while maintaining a double-digit capital adequacy index for all four systemic banks. In any event, the banks that participate in this plan on a voluntary basis will have a better capital quality with a smaller participation of tax arrears following the transfer of loans (To Vima, 2019).

Balance sheet repair is expected to reduce credit risk cost, which has a major impact on banks’ pre-provision income. By mitigating the excessively high credit risk cost, the funding costs will be reduced, thereby increasing loan demand and competitiveness. As seen in Eurobank, National Bank of Greece and Piraeus Bank, loan demand has increased following the IFRS 9 adoption. Further, lower credit risk costs will reinforce net interest income, may reduce the funding costs of banks, thereby improving their asset quality and long-term resilience, and will lower the operating cost for handling NPLs (Stournaras, 2018).

Postgraduate Dissertation 76 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

8.

8.1 General conclusions

The Dissertation sought to investigate the macroeconomic factors behind the NPEs increase considering the characteristics of the Greek banking system and the four systemic banks (Alpha Bank, Eurobank, National bank of Greece, and Piraeus Bank). The rapid growth of NPLs, the maintenance of a high stock of these in the portfolios of the banks, and the inability to quickly impair them are inseparably linked to the deep economic crisis and to the weak recovery that is still low at a European level. A fall in economic activity remains the most significant risk as it weakens the borrowers’ ability to service their debt, ultimately leading to an increase in overdue liabilities and a decline in the quality of banks' assets.

Today, pressure from regulators and shareholders is increasing towards the reduction of NPEs. For this purpose, the annual targets and indicators of Greece’s four systemic banks are being set and monitored. Failure to meet these targets would fuel uncertainty over bank capital strength, sinking market valuations, discouraging investors, forcing the imposition of higher minimum capital ratios and weakening the ability of banks to fund the economy.

In Greece, the instability of the broader macroeconomic environment with sluggish economic growth, high interest rates, capital controls, and limited access to foreign markets, forces Greek banks to implement proper strategies to reduce non-performing loans. The target can be achieved following a substantial improvement in GDP growth and financial market conditions. On the other hand, the key question that arises is how the Greek banks will be able to effectively manage NPLs while restoring investor confidence and credit demand growth as well as their profitability.

Before the crisis, the Greek banks had focused on expanding their business and gaining a comparative advantage over their competitors at the expense of inadequate qualitative risk analysis. As a result of this deficiency, they offered loans to borrowers either with

Postgraduate Dissertation 77 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions” inadequate guarantees or even overly indebted borrowers who would not be able to meet their obligations in adverse economic conditions. Further, the broader banking supervisory framework was not adequately strong and credible and thus insufficient to offset the practices outlined above. Supervision was weak and under no circumstances was able to identify the weaknesses of banks as a result of the accumulation of non-performing loans.

Under IFRS 9, financial assets classification is made according to the business model of the Bank and their cash flow characteristics. For instance, financial assets may include loans, contractual cash flows not for sale or contractual cash flows carrying principal and interest payments at amortized cost. Further, the expected credit losses (ECL) framework implements impairment accounting to effectively manage credit risk and mitigate a substantially higher probability of default.

The adoption of IFRS 9 has had a major impact on the loan loss provisions of the National Bank of Greece and Piraeus Bank, a lower impact on Eurobank and no impact on Alpha Bank’s loan loss provisions. NBG and Piraeus Bank have seen a huge decrease in their total assets following the IFRS 9 implementation (-24.8% and -22.5%, respectively). Further, Piraeus Bank experienced an increase in loans (+12.5%) whereas NBG incurred a decrease in deposits (-6.4%).

The prospects for 2019 are positive. Depositors are returning to the Greek banks, access to the money and capital markets is facilitated and the Greek economy is gradually recovering. The reduction of NPEs can be achieved by transferring these loans from the banks’ balance sheets to Special Purpose Vehicles to improve the banks’ portfolios and maintain double-digit capital adequacy index. On the other hand, NPEs reduction heavily depends on the improvement of the broader macroeconomic environment, including sustainable growth, lower unemployment, mitigated risk, full abolition of capital controls, and full access to financial markets. A high percentage of NPEs distorts credit allocation as non-viable firms are kept technically active so that banks avoid or delay loss recognition on these loans. At the end of the day, competitive firms with better growth prospects cannot get new loans.

Postgraduate Dissertation 78 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

8.2 Suggestions and recommendations

Banks play a key role in economic and social well-being, so they must be able to cope with their obligations. At the same time, non-performing loans can be a major risk factor for banks. Following the global financial crisis, it is evident that a rising NPL stock impedes the growth of the economy and puts the banks’ financial solvency at stake.

Given all the above considerations, it would be interesting to investigate how the Greek banks compare to their European peers regarding NPEs and whether a failure to effectively manage NPLs may even lad to bankruptcy with all the negative consequences such an event may entail for the national economy.

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Impact of IFRS 9 on Alpha Bank

Postgraduate Dissertation 87 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Impact of IFRS 9 on National Bank of Greece

Postgraduate Dissertation 88 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Impact of IFRS 9 on Piraeus Bank

Postgraduate Dissertation 89 Georgios Psimopoulos, “Non-Performing Exposures (NPEs) of the 4 systemic Greek banks: Impact of the IFRS 9 application on the determination of provisions”

Author’s Statement: I hereby declare that, in accordance with article 8 of Law 1599/1986 and article 2.4.6 par. 3 of Law 1256/1982, this dissertation is solely a product of personal work and does not infringe any intellectual property rights of third parties and is not the product of a partial or total plagiarism, and the sources used are strictly limited to the bibliographic references.

Postgraduate Dissertation 90