THE IMPACT OF NON PERFORMING LOANS ON PROFITABILITY OF VIETNAMESE COMMERCIAL BANKS45469

VIETNAM NATIONAL UNIVERSITY - UNIVERSITY OF ECONOMICS AND BUSINESS THE IMPACT OF NON - PERFORMING LOANS ON PROFITABILITY OF VIETNAMESE COMMERCIAL BANKS Pham Phat Tien*, Nguyen Thi Huyen My College of Economics, Can Tho University ABSTRACT The study was conducted to understand the impact of non - performing loans on profitability of Vietnamese commercial banks Panel data is collected from the published financial statements of 29 commercial banks from 2013 to 2018, and macro variable is collected from the World Bank GMM model is used to process data Research result shows that non - performing loans ratio affects strongly and negatively to bank profits, this result is consistent with the theory of bad management and skimming In addition, internal factors of banks such as total assets, loans on deposits ratio, and loans loss reserves ratio also have the significant impact on profits Beside that, bank profits is also affected by inflation Keywords: Profit, commercial bank, non - performing loan, GMM INTRODUCTION The banking system is considered the channel of capital supply Moreover, the bank, itself is one of the important financial institutions in a country's financial system The bank's contribution develops the economy which is through its special products In Vietnam, credit is the main product when it is not only accounts for the majority of asset items, but it is also the main source of income for banks Recently, commercial banks have become more cautious on their credit operations Because credit is the most activity have non - performing loans (NPL) which lead to credit risk It is considered one of the most serious risks NPL is one of the most influential factors in the performance of commercial banks, as they directly affect the functioning of banks, weakening assets and weakening income when the debt is * Corresponding author Email address: pptien@ctu.edu.vn 449 IN TERNATIONAL CONFERENCE ON - CIFBA 2020 not collected which is growing NPL are not only a factor affecting bank profits, but bank profits are also affected by other variables in the economy and problems within the bank itself Assessing the health of banks, or finding the factors affecting banks' profits is a necessary issue, as well as a study examine the relationship between NPL, other factors with bank’s profit From these reasons, it is necessary to study the non - performing loans affecting the profitability of Vietnamese commercial banks LITERATURE REVIEW AND THEORETICAL FRAMEWORK There has many previous experiment studies examined the determinants of bank profitability in many countries on around the world In this study, authors summarize some studies to make the background for building research model Foremost, in Sub - Saharan countries, according to research by Flamini, et al (2009), high NPL ratio make high credit risk and NPL which is positive relationship with ROA Moreover, inflation also impacts on the profits of banks In Tanzania, Kingu, et al (2018) has make study to finding the relationship between bank’s profit and NPL Our’s result show that the NPL and the debt to deposit ratio were negative relationship with the bank’s profit Research in Greece, Athanasoglou, et al (2011) showed that credit risk provisions and loan ratios are negatively correlated with profitability Banks improve profits by following credit risk which help the bank forecast risk levels in future Next to Nigeria, Osuagwu (2012), the ratio of loans and NPL increases were positive to credit risk and reduces profit, but in Bangladesh, Islam (2018) indicates that NPL and loans loss reserves is negative relationship to the bank's profit In additional, Funso, et al (2012) researched the relationship between credit risk and business performance of the largest banks in Nigeria according to the ratings of Fitch and The Banker The result showed that NPL and credit risk provisioning ratios increase is negative with efficiency of commercial banks, while the increase in loan sales will increase profits With similar results as the study of Million, et al (2015) in Ethiopia, NPL with business performance of commercial banks are negatively correlated Besides, the study shows that commercial banks have a good credit management model, risk management will achieve the better profit Turn back to Vietnam, researched by Minh & Canh (2015), loans on assets, deposit ratio and inflation are positively acssociated with banks profitability Meanwhile, the ratio of NPL, equity on assets, the ratio of operating expenses to income are negatively with profitability Finally, researched by Akhtar, et al (2011) in Pakistan, Irawati & Maksum (2017) in Indonesia have confirmed that NPL is negatively acssociated with commercial banks' profits Furthermore, the research results confirm that the profitability of commercial banks is affected by other factors such as lending rates, bank size, employment, and liquidity The theoretical framework for this study follows market power models established under the new empirical industrial economics literature for the analysis of competition and profitability in the banking sector In this study, authors summarize some theories which are involved to explain the results of study Louzis, et al (2011) consider the impact of macro and internal factors on NPLs of banks in Greece The authors gave the results with: Macro variables such as GDP, 450 VIETNAM NATIONAL UNIVERSITY - UNIVERSITY OF ECONOMICS AND BUSINESS unemployment rate and interest rates have different effects on banks' NPLs and for each lending sector Factors inside the bank such as bank size is a positive with the NPLs ratio of the two types of loans, mortgage and business, but it does not affect consumer lending So, Louzis, et al (2011) proposed the theory “Too big to fail” It suggests that the diversification of banks' assets reduces credit risk, NPL, the risk of default and increases bank profits In particular, Memdani (2017), bank size is one of the basis for assessing diversification which is a condition for banks to have more opportunities to diversify Berger & DeYoung (1997) conducted a study in the US banking system, from 1985 to 1994, to examine the impact of NPL on the efficiency of banks They use the study to test hypotheses related to loan quality, cost effectiveness, and bank capital “Bad management”, “Skimming” and “Unlucky” theories were proposed “Bad management” theory is that ineffective management leads to increase NPL Bad managers may be due to bad credit scoring skills, inadequate appraisals, difficulty tracking disbursed loans Therefore, this theory predicts the ability of banks reduce credit management is positive with NPL Memdani (2017), banks exert to maintain the required reserve ratio, loosen checking and supervising loan quality, so, NPL will increase in the long time The “Skimming” theory, which suggests that managers are limited by the allocation of resources to monitor credit quality from customer debt, leads to an increase in NPL The allocation of low resources can help banks gain profits in the short term, and help banks implement high profit growth strategies by saving costs in screening, appraisal, monitoring and evaluating the quality of loans However, in the long time, this action will cause risks and reduce profits The “Unlucky” theory suggests to changes in external conditions such as GDP, inflation, and interest rates which affect banks' NPL Banks must increase operating costs to reduce banks' profits Because the bank follow borrowers operations to ensure the quality of loans is not impaired The research results of Berger & DeYoung (1997) show that the impact of external factors on NPL was not large, so it concluded that the increase of NPL depends on internal factors of bank Increased cost effectiveness of banks was negative impact on NPL Therefore, the results supported the theory of bad management and skimming Credit management is good as well as allocate resources to follow the loans properly, the ratio of NPL tends to decrease in the future Bofondi & Gobbi (2003) has make a study to investigate the relationship between banks' access in the local credit market and the ratio of default on loans From that conclusion, the entry into the credit market is negative with the market share and revenue of banks Expanding loans with a little credit information will lead to the risk of default Banks with a large market share are abundant credit information to assess the business cycle of local borrowers The authors also proposed the information asymmetric theory, that banks with a large market share are the advantageous banks with abundant capital, from which they can choose good borrower Disadvantage selection due to information asymmetry leads to low quality loan when it have to make the bank eliminate good borrowers and grant bad borrowers In the long time, it causes a decline in the overall quality of the bank's asset portfolio which lead to accumulation of NPL and decrease in profits (Bofondi & Gobbi, 2003; Makri, et al 2014) 451 IN TERNATIONAL CONFERENCE ON - CIFBA 2020 METHODOLOGY 3.1 Data The data for this study is obtained from financial statements yearly of 29 Vietnamese commercial banks from 2013 to 2018 for the estimation of bank specific variables The financial statements were provided by the website of Vietstock company where is the very reliable stock figures in Vietnam The data for macroeconomic variables is collected from the website of World Bank Until the data was processed, some banks had not published yet the financial statements, this lead to the number of variables' observations of bank specific variables are not the same The observation of inflation variable in each year is consistencies for all banks, so the inflation variable crossed 29 Vietnamese commercial banks with 174 observations for years (Table 4.1) 3.2 Governing Equations Based on the literature reviews and the data collection capacity, authors set up the linear multivariate regression model to estimate the relationship between bank profitability and bank specific variables and macroeconomic variable, where applicable as stated in Athanasoglou, et al (2006) and Minh & Canh (2015): ROA = f(NPL, LDR, LLR, LNSIZE, INF) Detailed definitions of all the variables and their sources are provided in the table: Variable Name of Variale ROA Return on assets NPL Non - performing loans ratio (-) LDR Loans on deposit ratio (+) LLR Loans loss reserves ratio (-) Bank size (+) Inflation rate (+)/(-) LNSIZE INF Expected sign Measure Logarithm of total assets Inflation growth rate according to CPI Source: Financial statements of Vietnamese commercial banks and World Bank There are some indicators to measure the probability of the bank as net interest margin (NIM), return on equity (ROE) and return on assets (ROA) This study, authors use return on assets (ROA) as the key proxy for bank profitability, instead of the alternative return on equity (ROE) and net interest margin (NIM), the same as Flamini, et al (2009) Flamini, et al (2009) found that an analysis of ROE, NIM disregard the impact of financial leverage from the use of banks' assets to make profits and the problem that banks maybe encounter when using financial leverage such as credit 452 VIETNAM NATIONAL UNIVERSITY - UNIVERSITY OF ECONOMICS AND BUSINESS risk, liquidity issue, But these problem still exist which is a threat to banks in the information asymmetric business environment So, ROA the most important indicator of performance and measures how the banks are profitable relative to assets, meaning how management is efficient in utilizing the assets to generate profit, while, ROE and NIM focused on the profitability from equity and interest rate 3.3 Numerical Method Multicollinearity test by covariance matrix between pairs of variables in the model After that, the Hausman test is used to select one of the two regression models, with fixed effect (FE) and random effect (RE) From the selected model, the study performed tests assumptions of the regression model, in order to detect heteroscedasticity, autocorrelation Finally, we use the GMM estimates to process data with eliminate model defects and confirm the validity of the estimates in the research model Stata software 14.0 is used to process the data RESULTS AND DISCUSSION 4.1 Results Table 4.1 Descriptive statistics Variable Unit Obs Mean Std.Dev Max Min ROA (%) 165 0.82 0.69 3.61 -0.03 NPL (%) 162 2.01 1.04 6.81 0.34 LDR (%) 165 64.28 13.16 97.61 25.40 LLR (%) 166 4.12 8.93 67.66 -2.06 SIZE Milion of VND 167 206,204 258,977 1,313,078 14,685 (%) 174 3.74 1.72 6.59 0.88 INF Source: Financial statements of Vietnamese commercial banks and World Bank Because authors want that the variables in model not multicollinearity, so we performed the correlation test through covariance matrix of pair variables If the correlation coefficient between pairs of explanatory variables are high (exceeding 0.8), there is a possibility of multi - collinear (Nam, 2008) From the results of correlation analysis, there is no multi - collinear between the variables Therefore, all of variables are eligible to be included in the regression analysis model Table 4.2 Covariance matrix of variables ROA NPL LLR LDR LNSIZE ROA 1.0000 NPL -0.1437 1.0000 LLR -0.4274 0.1823 1.0000 LDR 0.2687 -0.1008 -0.1298 1.0000 LNSIZE 0.2717 -0.1453 -0.0885 0.1262 1.0000 INF 0.0593 0.3227 0.0066 -0.1775 -0.1049 INF 1.0000 Source: Financial statements of Vietnamese commercial banks and World Bank 453 IN TERNATIONAL CONFERENCE ON - CIFBA 2020 The results of estimating regression models by both FE and RE are statistically significant at 1% and all variables in the model affect the profitability of commercial banks at 5% and 1% R - square values of both FE and RE models are 0.3186 and 0.3019, respectively, which means that the independent variables included in the model explain over 30% of the fluctuations of ROA Table 4.3 Fixed - effect regression and Random - effect regression Variable NPL LDR LLR LNSIZE INF Cons FE Coef -0.129** 0.023*** -0.013** 0.330** 0.105*** -4.642*** Obs R - square F Prob > F t -2.63 4.43 -2.59 2.26 4.59 -2.77 161 0.3186 11.88 0.0000 P > │t│ 0.01 0.000 0.011 0.026 0.000 0.006 Coef -0.109** 0.018*** -0.017*** 0.182*** 0.083*** -2.54*** Obs R - square Chi - square Prob > chi2 RE z -2.37 4.43 -3.52 2.64 3.70 -3.01 P > │z│ 0.018 0.000 0.000 0.008 0.000 0.003 161 0.3019 61.03 0.0000 Note: *, ** and *** represent significance levels of 10%, 5%, and 1% respectively Source: Financial statements of Vietnamese commercial banks and World Bank Moreover, we want to get the best regression results used to explain the impact of change factors of ROA, so we conducted Hausman test to choose either FE or RE models The result of Hausman test shows that the estimation result by using the FE model explains the impact of the independent variables on the dependent variable is better than the estimation result by using the RE model at 1% significance level Table 4.4 Results of Wald test and Wooldridge test H0: No variance changes H0: No autocorrelation Chi - square 4.5e + 32 F Prob > chi2 0.0000 Prob > F Source: Financial statements of Vietnamese commercial banks and World Bank 23.441 0.0001 However, the estimation results using the FE model can still have defects The Wald test and the Wooldridge test show that the FE model has a heteroscedasticity and an autocorrelation at a significant level of 1% Table 4.5 GMM estimates P > │t│ 0.030 0.009 0.037 0.005 0.001 F 9.18 AR(2) 0.873 Hansen test 0.283 Prob > F 0.0000 Note: *, ** and *** represent significance levels of 10%, 5%, and 1% respectively Source: Financial statements of Vietnamese commercial banks and World Bank NPL LDR LLR LNSIZE INF 454 Variable Coef -0.1172** 0.015*** -0.004** 0.489*** 0.059*** t -2.29 2.79 -2.18 3.06 3.58 VIETNAM NATIONAL UNIVERSITY - UNIVERSITY OF ECONOMICS AND BUSINESS Based on the literature review and empirical studies, GMM regression analysis method must be implemented to fix the heteroscedasticity change and the autocorrelation The estimation result by using GMM method is considered to be the best and this estimation result is used to explain the impact of independent variables on the dependent variable in the model The Arellano - Bond (AR2) value for correlation in the residuals of the model is not statistically significant (p - value equals 87.3% > 10%), proving that the model has no correlation in remainder The Hansen test is not statistically significant (p - value equals 28.3% > 10%) proving that the tool variables in the model are reasonable and not correlated with the residuals 4.2 Discussion Consistent with the studies of Funso, et al (2012), Minh & Canh (2015), Islam (2018), Akhtar, et al (2011), Million, et al (2015), NPL is negative with profit of commercial banks “Bad management” theory and “Skimming” theory suggest that banks perform the supervision of borrowers, ineffective initial credit assessment, the weakness in professional skills of administrators or employees credit and banks want to save costs, thereby increasing NPL This is entirely consistent with the situation of credit operations of commercial banks during the study period because the borrower's inability to repay debt will lead to difficult debts to recover, thereby increasing the cost of deduction provisioning, reducing interest income from lending activities and affecting the profitability of the bank Different from the results of Kingu, et al (2018), this study finds a positive relationship between the ratio of loans on deposits to profitability, this expresses that banks face liquidity issue in the near future because excessive lending and financial recession when banks use higher - cost sources of capital The research results show that loans loss reserves ratio is negatively associated the profitability of the bank This result also coincides with the research results of Islam (2018), Athanasoglou, et al (2011) The bad management theory and skimming theory said that the loans loss reserves ratio adversely impacts bank profits, banks are making efforts to supervise borrowers and credit scores effectively Thereby, the bank reduce NPL and loans loss reserves that banks have to set up will increasing bank profits The bank size is positively acssociated with ROA, the more profit will be generated for the bank, this coincides with the research results of Irawati & Maksum (2017) The “Too big to fall” and the information asymmetry theories suggest that banks are big, more profitable because of the diversified asset portfolio, from which the types of risks that banks likely to encounter also be varied In addition, large banks have more opportunities to access the amount of credit information available in the market which assess the performance of borrowers Thereby reducing NPL and increasing bank profits The effect of inflation rate is positive with the profitability of banks and has expected sign This may explain that bank executives are adjusting interest rates accordingly to expected inflation rates to ensure bank profitability The research results are also consistent with the results of Minh & Canh (2015), Athanasoglou, et al (2011) 455 IN TERNATIONAL CONFERENCE ON - CIFBA 2020 CONCLUSIONS The study partly shows the factors that affect bank profits, but must attention to the effects of NPL NPL is not only one of the legacy lending in previous years of Vietnamese commercial banks, but also it is a signal of ineffective credit management, accuracy lack of supervision of loans before, during and after disbursement Since then, the quality of bank assets has decreased, leading to an increase in provision expenses and a decrease in profits Another conspicuous risk when excessive NPL increase will lead to the increase of operation cost and pull profits down Loans on deposits ratio which is positive relationship with profit, this means the banks are facing the hidden risks, such as the liquidity issue in the near future Although the higher the ratio of debt to total deposits, the banks can earn more profits, the higher the ratio of debt to total deposits requires a balance between capital and capital usage Besides the factors within the banks, such as: the ratio of loans on deposits, the loans loss reserves and the bank size all have a significant impact on the profitability of banks In addition, macro factors such as inflation also significantly affect the profitability of commercial banks REFERENCES [1] Akhtar, M F., Ali, K., & Sadaqat, S (2011) Factors Influencing the Profitability of Islamic Banks of Pakistan The International Research Journal of Finance and Economics, (66), 125 - 132 [2] Athanasoglou, P.P., Brissimis, S.N., & Delis, M.D (2008) Bank - specific, Industry specific and Macroeconomic determinants of Bank profitability Journal of International Financial Markets, Institutions and Money, 18(2), 121-136 [3] Berger, A N., & De Young, R (1997) Problem Loans and Cost Efficiency in Commercial Banks Journal of Banking and Finance, 21(6), 849-870 [4] Bofondi, M., & Gobbi, G (2003) Bad Loans and Entry in Local Credit Markets Bank of Italy Research Department, Rome [5] Kingu, P S., Macha, S., & Gwahula, R (2017) Bank specific determinants of Non - performing loans: Empirical evidence from commercial banks in Tanzania The international journal of Business & Management, 5(12), 18-28 [6] Louzis, D., Vouldis, A., & Metaxas, V.L (2012) Macroeconomic and Bank-specific Determinants of Non - performing Loans in Greece: A comparative study of mortgage, business and consumer loan portfolios The Journal of Banking and Finance, 36 (4), 1012-1027 [7] Minh, H T H & Canh, N T (2015) Diversify income and the factors affect to the profitability of commercial banks in Vietnam Banking technology review, 106-107, 13-25 [8] Irawati, N., & Maksum, A (2017) The Impact of Risk Management and Bank Size on Profitability of Commercial Banking in Indonesia The Advances in Economics, Business and Management Research, 46, 38-41 [9] Islam, F T (2018) Evaluating Loan Loss Provisioning for Non - Performing Loans and Its Impact on the Profitability of Commercial Banks in Bangladesh The Asian Finance& Banking Review, 2(2), 33-41 456 VIETNAM NATIONAL UNIVERSITY - UNIVERSITY OF ECONOMICS AND BUSINESS [10] Makri, V., Tsagkanos, A., & Bellas, A (2014) Determinants of Non - Performing Loans: The Case of Eurozone The Panoeconomicus, 2, 193 - 206 [11] Nam, M V (2008) Econometric Culture-Information Publishing [12] Memdani, L (2017) Macroeconomic and Bank Specific Determinants of Non Performing Loans, Npls in The Indian Banking Sector The Studies in Business and Economics, 12(2), 125-135 [13] Million, G., Kebede, M., & Selvaraj, S (2015), The impact of credit risk on profitability performance of commercial banks in Ethiopia African Journal of Business Management, 9(2), 59-66 [14] Osuagwu, E S (2014) Determinants of Bank Profitability in Nigeria International Journal of Economics and Finance, 6(12), 46-63 [15] Funso, K T., Kolade, A R., & Ojo, O.M (2012) Credit Risk and Commercial Banks Performance in Nigeria: A Panel Model Approach Australian Journal of Business and Management Research, 2(2), 31-38 [16] Flamini, V., McDonald, C., & Schumacher, L (2009) The Determinants of Commercial Bank Profitability in Sub - Saharan Africa IMF Working Paper 457 ... bank’s profit From these reasons, it is necessary to study the non - performing loans affecting the profitability of Vietnamese commercial banks LITERATURE REVIEW AND THEORETICAL FRAMEWORK There... 2020 CONCLUSIONS The study partly shows the factors that affect bank profits, but must attention to the effects of NPL NPL is not only one of the legacy lending in previous years of Vietnamese commercial. .. reserves and the bank size all have a significant impact on the profitability of banks In addition, macro factors such as inflation also significantly affect the profitability of commercial banks