Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Impact of Credit Risk Management on Bank Performance:Empirical Evidence from Bangladesh


Affiliations
1 Institute of Business Administration, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh
     

   Subscribe/Renew Journal


This paper empirically examines the implications of credit risk management of 23 Dhaka Stock Exchange listed conventional commercial banks of Bangladesh over the period 2006- 2015. The study considers five credit risk measures and two control variables to identify their impacts on three different dimensions of bank performance. Upon conducting relevant diagnostic tests, fixed effect model with Driscoll-Kraay standard error has been selected as the most suitable model for all the three performance indicators. The results suggest that Capital Adequacy Ratio (CAR) has a significant positive association with banks’ performances measured by Return on Assets (ROA), Return on Equity (ROE) and Market-to-Book value Ratio (MBR) whereas Non-Performing Loan Ratio (NPLR) shows an inverse association with all the three performance measures. The study demonstrates a positive association of Loan to Deposit Ratio (LTDR) with ROA and ROE. On the contrary, Loan- Loss Provision Ratio (LLPR) has significant negative association with both ROA and ROE, while influencing MBR positively. The study also indicates that Geographic Focus Index (GFI) has a significant positive impact on MBR. Some policy guidelines have been suggested based on the findings of the study.

Keywords

Dhaka Stock Exchange, Fixed Effect, Geographic Focus Index, Performance Measures, Random Effect.
User
Subscription Login to verify subscription
Notifications
Font Size

  • Abbas, A., Zaidi, S. A. H., Ahmad, W., & Ashraf, R. U. (2014). Credit risk exposure and performance of banking sector of Pakistan. Journal of Basic and Applied Scientific Research, 4(3), 240-245.
  • Acharya, V. V., Hasan, I., & Saunders, A. (2006). Should banks be diversified? Evidence from individual bank loan portfolios. The Journal of Business, 79(3), 1355-1412.
  • Ahmad, N. H., & Ariff, M. (2007). Multi-country study of credit risk determinants. International Journal of Banking and Finance, 5(1), 135-152.
  • Alkhatib, A., & Harasheh, M. (2012). Financial performance of Palestinian commercial banks. International Journal of Business and Social Science, 3(3), 175-184.
  • Alshatti, A. S. (2015). The effect of credit risk management on financial performance of the Jordanian commercial banks. Investment Management and Financial Innovations, 12(1), 338-345.
  • Baltagi, B. H. (2005). Econometric Analysis of Panel Data (3rd ed.). New York, NY: Wiley.
  • Bangladesh Bank. (2010-15). Financial stability report. Dhaka, Bangladesh: Author. Retrieved August 10, 2016, from https://www.bb.org.bd/openpdf.php
  • Bangladesh Bank. (2016). Guidelines on credit risk management (CRM) for banks. Dhaka, Bangladesh: Author. Retrieved September 7, 2016, from https:// www.bb.org.bd/openpdf.php
  • Basel Committee on Banking Supervision (1988). International convergence of capital measurement and capital standards. Basel, Switzerland: Author. Retrieved September 3, 2016, from https://www.bis.org/publ/bcbs04a.htm
  • Basel Committee on Banking Supervision. (1991). Measuring and Controlling Large Credit Exposures. Basel, Switzerland: Author. Retrieved September 3, 2016, from https://www.bis.org/publ/bcbsc121.pdf
  • Basel Committee on Banking Supervision. (1999). A new capital adequacy framework. Basel, Switzerland: Author. Retrieved September 3, 2016, from https:/ /www.bis.org/publ/bcbs50.htm
  • Basel Committee on Banking Supervision. (2010). Basel ²²²: A global regulatory framework for more resilient banks and banking system. Basel, Switzerland: Author. Retrieved September 3, 2016, from https://www.bis.org/publ/bcbs189_dec2010.htm
  • Baum, C. F. (2001). Residual diagnostics for cross-section time series regression models. The Stata Journal, 1(1), 101-104.
  • Berger, A. N., Hasan, I., & Zhou, M. (2010). The effects of focus versus diversification on bank performance: Evidence from Chinese banks. Journal of Banking & Finance, 34(7), 1417-1435.
  • Boahene, S. H., Dasah, J., & Agyei, S. K. (2012). Credit risk and profitability of selected banks in Ghana. Research Journal of finance and accounting, 3(7), 6-14.
  • Boffey, R., & Robson, G. N. (1995). Bank credit risk management. Managerial Finance, 21(1), 66-78.
  • Breusch, T. S., & Pagan, A. R. (1980). The Lagrange multiplier test and its applications to model specification in econometrics. The Review of Economic Studies, 47(1), 239-253.
  • Brooks, C. (2014). Introductory econometrics for finance (3rd ed.). New York, NY: Cambridge University Press.
  • Caprio, G., Laeven, L., & Levine, R. (2007). Governance and bank valuation. Journal of Financial Intermediation, 16(4), 584-617.
  • Diamond, D. W. (1984). Financial intermediation and delegated monitoring. The Review of Economic Studies, 51(3), 393-414.
  • Dietrich, A., & Wanzenried, G. (2011). Determinants of bank profitability before and during the crisis: Evidence from Switzerland. Journal of International Financial Markets, Institutions and Money, 21(3), 307-327.
  • DeYoung, R., & Rice, T. (2004). Noninterest income and financial performance at US commercial banks. Financial Review, 39(1), 101-127.
  • Driscoll, J. C., & Kraay, A. C. (1998). Consistent covariance matrix estimation with spatially dependent panel data. The Review of Economics and Statistics, 80(4), 549-560.
  • Drukker, D. M. (2003). Testing for serial correlation in linear panel-data models. The Stata Journal, 3(2), 168-177.
  • Gizaw, M., 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.
  • Greene, W. H. (2003). Econometric analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Grippa, P., & Gornicka, L. (2016). Measuring concentration risk- A partial portfolio approach (IMF Working Paper No. 16/158). Washington, DC: International Monetary Fund. Retrieved September 10, 2016, from https://www.imf.org/external/pubs/ft/wp/2016/wp16158.pdf
  • Haselmann, R., & Wachtel, P. (2007). Risk taking by banks in the transition countries. Comparative Economic Studies, 49(3), 411-429.
  • Hair, J.F., Jr., Anderson, R. E., Tatham, R.L., & Black, W.C. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Hill, R. C., Griffiths, W. E., & Lim G. C. (2011). Principles of econometrics (4th ed.). River Street, NJ: John Wiley & Sons.
  • Hoyos, R. E. D., & Sarafidis, V. (2006). Testing for cross-sectional dependence in panel-data models. The Stata Journal, 6(4), 482-496.
  • International Monetary Fund. (IMF) (2011-2015). Global Financial Stability Report. Bank Non-performing Loans to Total Loans. IMF, Washington, DC: Author. Retrieved September 10, 2016 from https://data.imf.org/regular.aspx?key=61404592
  • Kmenta, J. (1986). Elements of econometrics (2nd ed.). New York, NY: Macmillan Publishing Co.
  • Lütkebohmert, E. (2008). Concentration risk in credit portfolios. Berlin Germany: Springer Science & Business Media.
  • Kolapo, T. F., Ayeni, R. K., & Oke, M. O. (2012). Credit risk and commercial banks’ performance in Nigeria: A panel model approach. Australian Journal of Business and Management Research, 2(2), 31-38.
  • Kosmidou, K. (2008). The determinants of banks’ profits in Greece during the period of EU financial integration. Managerial Finance, 34(3), 146-159.
  • Kurawa, J. M., & Garba, S. (2014). An evaluation of the effect of credit risk management on the profitability of Nigerian Banks. Journal of Modern Accounting and Auditing, 10(1), 104-115.
  • Lewis-Beck, M. S. (1980). Applied regression: An introduction. Newbury Park, CA: Sage Publications Inc.
  • Mahmud, K., Mallik, A., Imtiaz, F. M., & Tabassum, N. (2016). The bank-specific factors affecting the profitability of commercial banks in Bangladesh: A panel data analysis. International Journal of Managerial Studies and Research, 4(7), 67-74.
  • Meyer, A. P., & Yeager, T. J. (2001). Are small rural banks vulnerable to local economic downturns? Federal Reserve Bank of St. Louis Review, 83(2), 25-38.
  • Noman, A. H. M., Pervin, S., Chowdhury, M. M., & Banna, H. (2015). The effect of credit risk on the banking profitability: A case on Bangladesh. Global Journal of Management and Business Research, 15(3), 40-48.
  • Ongore, V. O., & Kusa, G. B. (2013). Determinants of financial performance of commercial banks in Kenya. International Journal of Economics and Financial Issues, 3(1), 237-252.
  • Park, H. M. (2011). Practical guides to panel data modeling: A step by step analysis using stata (Tutorial Working Paper). Minamiuonuma, Japan: Graduate School of International Relations, International University of Japan. Retrieved September, 2, 2016, from http:// www. iuj.ac.jp/faculty/kucc625
  • Park, R. W. (1967). Efficient estimation of a system of regression equations when disturbances are both serially and contemporaneously correlated. Journal of the American Statistical Association, 62(318), 500-509.
  • Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels (IZA Discussion Paper No. 1240). Bonn, Germany: Forschungsinstitut zur Zukunft der Arbeit [Institute for the Study of Labor] (IZA). Retrieved from ftp.iza.org/dp1240.pdf
  • Poudel, R. P. S. (2012). The impact of credit risk management on financial performance of commercial banks in Nepal. International Journal of Arts and Commerce, 1(5), 9-15.
  • Samad, A. (2015). Determinants of bank profitability: Evidence from Bangladesh commercial banks. International Journal of Financial Research, 6(3), 173-179.
  • Salas, V., & Saurina, J. (2002). Credit risk in two institutional regimes: Spanish commercial and savings banks. Journal of Financial Services Research, 22(3), 203-224.
  • Sufian, F., & Habibullah, M. S. (2009). Determinants of bank profitability in a developing economy: Empirical evidence from Bangladesh. Journal of Business Economics and Management, 10(3), 207-217.
  • Sufian, F., & Kamarudin, F. (2012). Bank-specific and macroeconomic determinants of profitability of Bangladesh’s commercial banks. Bangladesh Development Studies, 35(4), 1-29.
  • Tabak, B. M., Fazio, D. M., & Cajueiro, D. O. (2011). The effects of loan portfolio concentration on Brazilian banks’ return and risk. Journal of Banking & Finance, 35(11), 3065-3076.
  • Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data (2nd ed.). Cambridge, MA: MIT Press.

Abstract Views: 208

PDF Views: 0




  • Impact of Credit Risk Management on Bank Performance:Empirical Evidence from Bangladesh

Abstract Views: 208  |  PDF Views: 0

Authors

K. M. Zahidul Islam
Institute of Business Administration, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh
Md Badrul Alam
Institute of Business Administration, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh
Md Motaher Hossain
Institute of Business Administration, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh

Abstract


This paper empirically examines the implications of credit risk management of 23 Dhaka Stock Exchange listed conventional commercial banks of Bangladesh over the period 2006- 2015. The study considers five credit risk measures and two control variables to identify their impacts on three different dimensions of bank performance. Upon conducting relevant diagnostic tests, fixed effect model with Driscoll-Kraay standard error has been selected as the most suitable model for all the three performance indicators. The results suggest that Capital Adequacy Ratio (CAR) has a significant positive association with banks’ performances measured by Return on Assets (ROA), Return on Equity (ROE) and Market-to-Book value Ratio (MBR) whereas Non-Performing Loan Ratio (NPLR) shows an inverse association with all the three performance measures. The study demonstrates a positive association of Loan to Deposit Ratio (LTDR) with ROA and ROE. On the contrary, Loan- Loss Provision Ratio (LLPR) has significant negative association with both ROA and ROE, while influencing MBR positively. The study also indicates that Geographic Focus Index (GFI) has a significant positive impact on MBR. Some policy guidelines have been suggested based on the findings of the study.

Keywords


Dhaka Stock Exchange, Fixed Effect, Geographic Focus Index, Performance Measures, Random Effect.

References