The impact of credit risk on profitability in commercial banks in Vietnam Luận văn thạc sĩ

Master’s thesis Supervisor : Dr Pham Huu Hong Thai The IMPACT of CREDIT RISK on PROFITABILITY IN cOMMERCIAL BANKS in vietnam By Trong Quoc Tran Email : trong906@gmail.com Tel : 0907003639 HOCHIMINH CITY-2010 Master’s thesis Supervisor : Dr Pham Huu Hong Thai ACKNOWLEDGEMENT I would like to express my thankfulness to all those who gave me the possibility to complete this research project I am grateful all authors who have given me a source of referential documents in the process of writing my thesis Especially, I am deeply indebted to my supervisor Dr Pham Huu Hong Thai, whose support, interest, encouragement and suggestion supported me during the research and writing process of this research project I also send to my gratitude to all teachers Financial and banking department has encouraged and help me this completes my thesis I would like to thank the library staff of the University of Economics Ho Chi Minh City for their relentless effort in making access to research data and literature possible Abstract By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai Nowadays, Credit risk management in banks has become more important because of the financial crisis that the world is experiencing Since granting credit is one of the main sources of income in commercial banks, the management of the risk related to that credit affects the profitability of the banks The study evaluates the impact of credit risk on profitability in Commercial Banks in Vietnam for the period of 2005-2009 Using financial ratios such as Return on Asset (ROA), Return on Equity (ROE), Nonperforming loan (NPL) analyze In the study try to find out how the credit risk management affects the profitability in banks The study is limited to identifying the relationship of credit risk management on profitability of twenty commercial banks in Viet Nam The results of the study are limited to banks in the sample and are not generalized for the all the commercial banks in Viet Nam Furthermore, as the study only uses the quantitative approach and focuses on the description of the outputs from SPSS, the reasons behind will not be discussed and explained The quantitative method is used in order to fulfill the main purpose of the study The study have used regression model to the empirical analysis In the model the study have defined ROE as profitability indicator while NPLR and CAR as credit risk management indicators The data is collected from the sample banks annual reports (20052009) and capital adequacy and risk management on financial reports (20052009) in twenty commercial banks The findings and analysis reveal that credit risk has effect on profitability in all twenty banks Keywords: credit risk management, profitability, banks By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai List of Acronyms Adj R2 Adjusted R-squared BCBS Basel Committee on Banking Supervision CAR Capital Adequacy Ratio CCF Credit Conversion Factors Coef Coefficient CRD Capital Requirements Directives FIRB Foundation Internal Rating-based FSA Financial Supervisory Authority ICAAP Internal Capital Adequacy Assessment Process IFRS International Financial Reporting Standards IRB Internal Rating-based LGD Loss Given Default N Number (of Observations) NI Net Income NPL Non-performing Loan NPLR Non-performing Loan Ratio PD Probability of DefaultP-value Probability Value R2 R-squared ROA Return on Assets ROE Return on Equity RORAC Return on Risk Adjusted Capital RWA Risk Weighted Asset SFSA Swedish Financial Supervisory Authority Signif Significance TL Total Loan TSE Total Shareholders’ Equity By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai TABLE OF CONTENT TITLE PAGES PAGES ACKNOWLEDGEMENT (2) Abstract (3) List of Acronyms (4) CHAPTER ONE 1.Introduction (8) 1.1 Statement of problems (8) 1.2 Problem Discussion (10) 1.3 Research question (10) 1.4 Objective of the study (11) 1.5 Scope of the study (12) 1.6 Layout of the study (12) CHAPTER TWO LITERATURE REVIEW 2.1 The relationship between profitability and capital (13-14) 2.2 The relationship between capital and risk (14-15) 2.3 The relationship between risk and profitability (15-16) 2.4 Previous Studies 2.4.1 ROE – profitability indicator (17-18) 2.4.2 Credit risk management indicators (18-19) 2.4.3.Capital and profitability : (19-20-21-22) 2.5 Theories 2.5.1 Risks in banks (23) 2.5.2 Credit risk management in banks (24) 2.5.3 Bank Profitability 2.6 Regulations 2.6.1 The Basel Accords (24-25-26) (28) (28-29-30) CHAPTER THREE METHODOLOGY By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai 3.1 Research approach (31) 3.2 Hypothesis (31) 3.3 Sampling (32) 3.4 Data Collection (32) 3.5 Data analyzing instruments (32-33) 3.6 Applied regression model (33) 3.6.1 Dependent variable (33) 3.6.2 Independent variables (33) 3.6.3 Regression analysis explained 3.7.Reliability and validity (34-35-36-37) (37-38) CHAPTER FOUR : OVERVIEW OF THE COMMERCIAL BANKING SYSTEM IN VIETNAM 4.1.The commercial banking system of Vietnam was the process of transition from mono-banking system to commercial banking system (39) 4.2 Role of commercial banks in the economy (39-40) 4.3 Banking system of the role of trade in Vietnam after 20 years (40-42) 4.4.Opportunities for Vietnam's commercial banking system (42-43) 4.5 The difficulties and challenges for Vietnam's banking system (44-45) CHAPTER FIVE : EMPIRICAL RESULT AND DISCUSSION 5.1Overview of the banks studied (46-48) 5.2 Return on Equity (ROE) (50-52) 5.3 Non-Performing Loan (NPLR) (54-55) 5.4 Capital Adequate Ratio (CAR) (56-57) 5.6.Basel I and basel II application affect CHAPTER SIX : CONCLUSION AND SUGGESTIONS (60-61) 6.1 Conclusion 6.1 Conclusion By: Tran Quoc Trong (66-67) Master’s thesis Supervisor : Dr Pham Huu Hong Thai CHAPTER ONE INTRODUCTION Introduction In this chapter, we present the background of the thesis followed by the problem statement The discussion also contains the motivation for our thesis Finally, we present the research question, the purpose of this thesis and limit the area of the study 1.1 Statement of problems Credit activities are crucial of Vietnam banking system, They bring 80-90% to income for each bank, but the risks are not less Credit risk will be higher than the enormous influence to business banking Facing the opportunities and challenges of the process of international economic integration, the issue of raising the competitiveness of the domestic commercial banks with foreign commercial banks, in particular improving the quality of credit, risk reduction has become urgent Besides, the world economic situation is complicated and the risk of increasing the credit crisis Vietnam is a country with open economy should not avoid the effects of the world economy Facing this situation, requires commercial banks of Vietnam must improve the management of credit risk, limited to the minimum possible risks, causing potential risks Managing credit risk in financial institutions is critical for the survival and growth of the financial institutions In the case of banks, the issue of credit risk is even of greater concern because of the higher levels of perceived risks resulting from some of the characteristics of clients and business conditions that they find themselves in Credit risk refers to the risk of loss because of debtor’s non-payment of a loan or other forms of credit As they default, delay By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai in repayments, restructuring of borrower repayments and bankruptcy are also considered as additional risks When it comes to banking, credit risk is apparent on lending services to clients There is the need for an effective employment of credit scorecard for the purpose of ranking potential and existing customers according to risk In this will be based the appropriate measures to be applied by the banks Nevertheless, banks charge higher price for higher risk customers Credit limits and faced by lenders to consumers, lenders to business, businesses and even individuals Credit risks, nevertheless, are most encountered in the financial sector particularly by the institutions such as banks Credit risk management therefore is both a solution and a necessity in the banking setting The global financial crisis also requires the banks to regain enough confidence by the public not only for the financial institutions but also the financial system in general and to not just rely on the financial aid by the governments and central banks It is critical for the banks to engage in better credit risk management practices Banks are not an exemption The banks of Vietnam as well as the other over all the World are required to follow Basel II capital adequacy framework from 2007 Basel II aims to build on a solid foundation of prudent capital regulation, supervision, and market discipline, and to enhance further risk management and financial stability However, it is worth mentioning that regulatory and deregulatory transitions usually end up with the same result The exposed risk – the main and most difficult one to identify – is the credit risk in the particular current case The importance of this risk is increased by the fact that it is linked to the problem of collateral Therefore, it is in need of being deliberately examined and studied For this reason, Basel II considers varieties of credit risk measurement techniques, wider than Basel I did The goal is to improve the credit risk By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai management quality without constraining banks’competitiveness Regulations should be interactive or flexible to be successful because of rapidly changing technological, political, and economical circumstances Credit risk measurement tools presented in Basel II intended to be flexible The banks can either choose from the proposed options or employ their own as long as it gives sound and fair results The importance of the credit risk management and its impact on profitability has motivated us to pursue this study We assume that if the credit risk management is sound, the profit level will be satisfactory The other way around, if the credit risk management is poor, the profit level will be relatively lower Because the less the banks loss from credits, the more the banks gain.The profitability is the indicator of credit risk management The central question is how significant is the impact of credit risk management on profitability 1.2 Problem Discussion The importance of the credit risk and its impact on profitability has motivated us to pursue this study We assume that if the credit risk management is sound, the profit level will be satisfactory The other way around, if the credit risk management is poor, the profit level will be relatively lower Because the less the banks loss from credits, the more the banks gain Profitability is the indicator of credit risk management The central question is how significant is the impact of credit risk management on profitability This thesis is an endeavor to find the answer 1.3 Research question The discussed background and problem formulation make us to have the following research question: How does credit risk affect the profitability in commercial banks in Vietnam ? 1.4 Objective of the study By: Tran Quoc Trong Master’s thesis Supervisor : Dr Pham Huu Hong Thai The purpose of the research is to describe the impact level of credit risk on profitability in twenty commercial banks in Vietnam The study is to test the following hypothesis by econometric model : H1: Banks with higher profitability (ROE, ROA) have lower loan losses (NonPerforming Loans/ Total Loans) H2: Banks with higher interest income (net interest/Average total assets, interest net /total income) also have lower bad loans (NPL) H3: The growth of ROE/ ROA may also depend on the capitalization of the banks and operating profit margin If a bank is highly capitalized through the risk-weighted capital adequacy ratio (RWCAR) or Tier capital adequacy ratio (CAR), the expansion of ROE will be retarded we test the hypothesis using the following regression model: P(ROA/ROE)= + 1NPLR+ 2CAR+ Using data on 20 commercial banks in Vietnam and our results show no rejection by ourhypothesis 1.5 Scope of the study The research is limited on evaluate the impact of credit risk on profitability in the twenty Banks in Vietnam Thus, the other risks mentioned in Basel Accords are not discussed Due to the unavailability of information in annual reports, our sample only contains twenty largest commercial banks and their years’ annual reports from 2005 to 2009 respectively Since the banks in sample rejected to participate in our internet based survey, the primary data was not possible to obtain Considering the above mentioned circumstances, the results of the study are limited to twenty commercial banks in the sample and are not generalized for all the banks in Vietnam Finally, as the study only uses the quantitative approach and focus on the description of the outputs from By: Tran Quoc Trong 10 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Coefficients Standardized Unstandardized Coefficients Model B 20,906 -1,761 CAR_BASEL_II -,593 -1,064 -2,282 Collinearity Statistics ,000 -,346 ,260 Sig -,161 1,656 t 3,598 NPLR_BASEL_II Correlations 5,811 Std Error (Constant) Coefficients Beta Zero-order Partial Part Tolerance VIF ,294 -,193 -,172 -,161 ,992 1,008 ,028 -,361 -,351 -,345 ,992 1,008 a Dependent Variable: ROE_BASEL_II Collinearity Diagnosticsa Variance Proportions Dimensi Model on Eigenvalue Condition Index (Constant) 1 2,736 1,000 ,01 ,04 ,01 ,234 3,417 ,03 ,95 ,04 ,030 9,570 ,96 ,01 ,95 NPLR_BASEL_II CAR_BASEL_II a Dependent Variable: ROE_BASEL_II Residuals Statisticsa Minimum Maximum Mean Std Deviation N Predicted Value 7,3585 14,9869 11,8705 2,24422 40 Residual -1,03707E1 14,85267 ,00000 5,22062 40 Std Predicted Value -2,011 1,389 ,000 1,000 40 By: Tran Quoc Trong 82 Master’s thesis Std Residual Supervisor : Dr Pham Huu Hong Thai -1,935 2,771 ,000 ,974 40 a Dependent Variable: ROE_BASEL_II Regression [DataSet1] C:\Users\LENOVO\Documents\ABC.sav Descriptive Statistics Mean Std Deviation N ROA 1,5940 ,80887 100 NPLR ,7481 ,49928 100 CAR 12,8013 3,04983 100 Correlations ROA 1,000 -,166 ,389 -,166 1,000 ,102 ,389 ,102 1,000 ROA ,050 ,000 NPLR ,050 ,157 CAR N ROA CAR Sig (1-tailed) CAR NPLR Pearson Correlation NPLR ,000 ,157 ROA 100 100 100 By: Tran Quoc Trong 83 Master’s thesis Supervisor : Dr Pham Huu Hong Thai NPLR 100 100 100 CAR 100 100 100 Variables Entered/Removedb Variables Model Variables Entered Removed Method CAR, NPLRa Enter a All requested variables entered b Dependent Variable: ROA Model Summaryb Change Statistics Std Error of the Model R R Square Adjusted R Square Estimate R Square Change F Change df1 df2 Sig F Change Durbin-Watson ,440a ,194 ,177 ,73374 ,194 11,656 97 ,00002906 1,316 a Predictors: (Constant), CAR, NPLR b Dependent Variable: ROA ANOVAb Model df Mean Square F Sig Regression 12,551 6,275 11,656 ,00002906 Residual Sum of Squares 52,222 97 ,538 By: Tran Quoc Trong 84 Master’s thesis Total Supervisor : Dr Pham Huu Hong Thai 64,772 99 a Predictors: (Constant), CAR, NPLR b Dependent Variable: ROA Coefficientsa Standardized Unstandardized Coefficients Model Coefficients 95% Confidence Interval for B ,453 -,336 ,148 CAR ,109 ,024 Upper Bound ,170 -,197 -2,262 ,026 -,630 4,473 ,00000294 ,060 Collinearity Statistics 1,104 ,328 NPLR Lower Bound ,410 (Constant) Sig -,207 Std Error t 1,383 B Correlations Beta Zero-order Partial Part Tolerance VIF -,041 -,166 -,224 -,206 ,990 1,010 ,157 ,389 ,414 ,408 ,990 1,010 a Dependent Variable: ROA Coefficient Correlationsa Model Covariances CAR 1,000 -,102 -,102 1,000 CAR ,001 ,000 NPLR Correlations NPLR NPLR CAR ,000 ,022 a Dependent Variable: ROA By: Tran Quoc Trong 85 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Collinearity Diagnosticsa Variance Proportions Dimensi Model on Eigenvalue Condition Index (Constant) NPLR CAR 1 2,755 1,000 ,01 ,03 ,01 ,218 3,553 ,03 ,96 ,04 ,027 10,140 ,96 ,01 ,95 a Dependent Variable: ROA Residuals Statisticsa Minimum Maximum Mean Std Deviation N Predicted Value ,6750 2,5193 1,5940 ,35605 100 Residual -1,15144 3,31219 ,00000 ,72629 100 Std Predicted Value -2,581 2,599 ,000 1,000 100 Std Residual -1,569 4,514 ,000 ,990 100 a Dependent Variable: ROA Regression [DataSet1] C:\Users\LENOVO\Documents\ABC.sav By: Tran Quoc Trong 86 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Descriptive Statistics Mean Std Deviation N ROA_BASEL_I 1,5932 ,75905 57 NPLR_BASEL_I ,7374 ,50092 57 CAR_BASEL_I 12,6205 3,00051 57 Correlations ROA_BASEL_I 1,000 -,260 ,407 -,260 1,000 ,074 ,407 ,074 1,000 ROA_BASEL_I ,025 ,001 NPLR_BASEL_I ,025 ,291 CAR_BASEL_I ,001 ,291 ROA_BASEL_I 57 57 57 NPLR_BASEL_I 57 57 57 CAR_BASEL_I N ROA_BASEL_I CAR_BASEL_I Sig (1-tailed) CAR_BASEL_I NPLR_BASEL_I Pearson Correlation NPLR_BASEL_I 57 57 57 Variables Entered/Removedb Variables Model Variables Entered Removed By: Tran Quoc Trong Method 87 Master’s thesis Supervisor : Dr Pham Huu Hong Thai CAR_BASEL_I, NPLR_BASEL_Ia Enter a All requested variables entered b Dependent Variable: ROA_BASEL_I Model Summaryb Change Statistics Std Error of the Model R R Square Adjusted R Square Estimate R Square Change F Change df1 df2 Sig F Change Durbin-Watson ,501a ,251 ,223 ,66914 ,251 9,030 54 ,0004-4 1,445 a Predictors: (Constant), CAR_BASEL_I, NPLR_BASEL_I b Dependent Variable: ROA_BASEL_I ANOVAb Model df Mean Square F Sig Regression 8,086 4,043 9,030 ,00004-4 Residual 24,178 54 ,448 Total Sum of Squares 32,265 56 a Predictors: (Constant), CAR_BASEL_I, NPLR_BASEL_I b Dependent Variable: ROA_BASEL_I Coefficientsa By: Tran Quoc Trong 88 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Standardized Unstandardized Coefficients Model ,549 -,442 ,179 CAR_BASEL_I ,109 ,030 Upper Bound ,176 -,253 -2,470 ,017 -,801 3,633 ,001 ,049 Correlations Collinearity Statistics 1,351 ,400 NPLR_BASEL_I Lower Bound ,429 (Constant) Sig -,292 Std Error t 1,372 B 95% Confidence Interval for B Coefficients Beta Zero-order Partial Part Tolerance VIF -,083 -,260 -,319 -,291 ,994 1,006 ,168 ,407 ,443 ,428 ,994 1,006 a Dependent Variable: ROA_BASEL_I Coefficient Correlationsa Model Covariances CAR_BASEL_I 1,000 -,074 -,074 1,000 CAR_BASEL_I ,001 ,000 NPLR_BASEL_I Correlations NPLR_BASEL_I NPLR_BASEL_I CAR_BASEL_I ,000 ,032 a Dependent Variable: ROA_BASEL_I By: Tran Quoc Trong 89 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Collinearity Diagnosticsa Variance Proportions Dimensi Model on Eigenvalue Condition Index (Constant) NPLR_BASEL_I CAR_BASEL_I 1 2,748 1,000 ,01 ,03 ,01 ,225 3,494 ,03 ,95 ,04 ,026 10,208 ,96 ,01 ,95 a Dependent Variable: ROA_BASEL_I Residuals Statisticsa Minimum Maximum Mean Std Deviation N Predicted Value ,5268 2,2929 1,5932 ,38000 57 Residual -,97070 2,71450 ,00000 ,65708 57 Std Predicted Value -2,806 1,841 ,000 1,000 57 Std Residual -1,451 4,057 ,000 ,982 57 a Dependent Variable: ROA_BASEL_I Regression [DataSet1] C:\Users\LENOVO\Documents\ABC.sav Descriptive Statistics Mean By: Tran Quoc Trong Std Deviation N 90 Master’s thesis Supervisor : Dr Pham Huu Hong Thai ROA_BASEL_II 1,4022 ,53997 40 NPLR_BASEL_II ,7400 ,52042 40 CAR_BASEL_II 13,0305 3,31482 40 Correlations ROA_BASEL_II NPLR_BASEL_II CAR_BASEL_II Pearson Correlation -,122 ,250 -,122 1,000 ,091 CAR_BASEL_II ,250 ,091 1,000 ROA_BASEL_II ,226 ,060 NPLR_BASEL_II ,226 ,288 CAR_BASEL_II ,060 ,288 ROA_BASEL_II 40 40 40 NPLR_BASEL_II 40 40 40 CAR_BASEL_II N 1,000 NPLR_BASEL_II Sig (1-tailed) ROA_BASEL_II 40 40 40 Variables Entered/Removedb Variables Model Variables Entered Removed Method CAR_BASEL_II, Enter NPLR_BASEL_II a By: Tran Quoc Trong 91 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Variables Entered/Removedb Variables Model Removed Variables Entered Method Enter CAR_BASEL_II, NPLR_BASEL_II a a All requested variables entered b Dependent Variable: ROA_BASEL_II Model Summaryb Change Statistics Std Error of the Model R R Square Adjusted R Square Estimate R Square Change F Change df1 df2 Sig F Change Durbin-Watson ,289a ,084 ,034 ,53072 ,084 1,686 37 ,199 1,397 a Predictors: (Constant), CAR_BASEL_II, NPLR_BASEL_II b Dependent Variable: ROA_BASEL_II ANOVAb Model df Mean Square F Sig Regression ,950 ,475 1,686 ,199a Residual 10,422 37 ,282 Total Sum of Squares 11,371 39 a Predictors: (Constant), CAR_BASEL_II, NPLR_BASEL_II By: Tran Quoc Trong 92 Master’s thesis Supervisor : Dr Pham Huu Hong Thai ANOVAb Model df Mean Square F Sig Regression ,950 ,475 1,686 ,199a Residual 10,422 37 ,282 Total Sum of Squares 11,371 39 b Dependent Variable: ROA_BASEL_II Coefficientsa Standardized Unstandardized Coefficients Model Coefficients 95% Confidence Interval for B ,957 -,152 ,164 CAR_BASEL_II ,043 ,026 Upper Bound ,011 ,235 -,926 ,360 -,484 1,663 ,105 -,009 Collinearity Statistics 1,679 ,356 NPLR_BASEL_II Lower Bound ,263 (Constant) Sig -,146 Std Error t 2,686 B Correlations Beta Zero-order Partial Part Tolerance VIF ,180 -,122 -,151 -,146 ,992 1,008 ,095 ,250 ,264 ,262 ,992 1,008 a Dependent Variable: ROA_BASEL_II Coefficient Correlationsa Model Correlations CAR_BASEL_II NPLR_BASEL_II 1,000 -,091 NPLR_BASEL_II -,091 1,000 CAR_BASEL_II ,001 ,000 NPLR_BASEL_II Covariances CAR_BASEL_II ,000 ,027 By: Tran Quoc Trong 93 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Coefficient Correlationsa Model CAR_BASEL_II NPLR_BASEL_II Correlations CAR_BASEL_II 1,000 -,091 NPLR_BASEL_II -,091 1,000 CAR_BASEL_II ,001 ,000 NPLR_BASEL_II ,000 ,027 Covariances a Dependent Variable: ROA_BASEL_II Collinearity Diagnosticsa Variance Proportions Dimensi Model on Eigenvalue Condition Index (Constant) 1 2,736 1,000 ,01 ,04 ,01 ,234 3,417 ,03 ,95 ,04 ,030 9,570 ,96 ,01 ,95 NPLR_BASEL_II CAR_BASEL_II a Dependent Variable: ROA_BASEL_II Residuals Statisticsa Minimum By: Tran Quoc Trong Maximum Mean Std Deviation N 94 Master’s thesis Supervisor : Dr Pham Huu Hong Thai Predicted Value 1,1521 1,7616 1,4022 ,15605 40 Residual -,81766 1,52347 ,00000 ,51693 40 Std Predicted Value -1,603 2,303 ,000 1,000 40 Std Residual -1,541 2,871 ,000 ,974 40 a Dependent Variable: ROA_BASEL_II By: Tran Quoc Trong 95 Master’s thesis Supervisor : Dr Pham Huu Hong Thai ... sources of income in commercial banks, the management of the risk related to that credit affects the profitability of the banks The study evaluates the impact of credit risk on profitability in Commercial. .. rejection by ourhypothesis 1.5 Scope of the study The research is limited on evaluate the impact of credit risk on profitability in the twenty Banks in Vietnam Thus, the other risks mentioned in. .. the less the banks loss from credits, the more the banks gain .The profitability is the indicator of credit risk management The central question is how significant is the impact of credit risk management