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Non-Performing Loans (NPLs) in Islamic Banks of Bangladesh: An Empirical Study

Benazir Rahman
By Benazir Rahman
1 week ago
Non-Performing Loans (NPLs) in Islamic Banks of Bangladesh: An Empirical Study

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  1. World Review of Business Research Vol . 8. No. 3. September 2018 Issue. Pp.12-23 Non-Performing Loans (NPLs) in Islamic Banks of Bangladesh: An Empirical Study Benazir Rahman1and Nusrat Jahan2 The word banking is a buzz word in this modern era. Our financial system largely depends on this sector. The concept of Non-Performing Loans (NPLs) or classified loans is one of the major barriers in the way of sustainability and growth of banking industry. The study basically focuses on the recent scenario of Non-Performing Investments (NPIs) in Islamic commercial banks of our country. The paper has shown the impact of credit worthiness of customers, bureaucratic issues, ethical perspective of employees, credit analysis process and so on over the trend of NPLs or NPIs. For the study a field survey has done for primary data collection. All of the 8 Islamic banks are in the sample frame. Principal Component Analysis has been used to analyze primary data. The regression and trend between NPIs and profit after tax has shown to reveal the real picture. 5 years secondary data has been used (20112015). Different statistical tools like as mean values, standard deviation, F-test, regression analysis and so on have been used. The paper reveals some variables have highest influence over the NPIs of Islamic banks while others have least impact. The paper will be useful material for the finance scholars and bankers. Keywords: Non-performing Investments (NPIs), Islamic commercial banks, growth, Bangladesh. 1. Introduction A prerequisite for the economic development of a country is smooth and efficient flow of saving-investment process. The economy of Bangladesh basically depends on the intermediary role of commercial banks for mobilizing internal saving and providing capital to the investors. While taking credit, we basically think of banks rather than NBFIs. For this reason, Banks are becoming more exposed to credit risk and NonPerforming Loan is becoming a burning issue for our banking industry as well as for our economy. Non-performing loan or asset or investment (in case of Islamic Banks) refers to those assets from which banks no longer receive installments. NPI is categorized into four criterions. The worst scenario is Bad/Loss account. Banks are now fighting hard to handle NPI. To find out this, we have used some statistical tools. Our study focuses on the causes of NPI of Islamic banks prevailing in our country. NPL is considered as NPI in case of Islamic Banks, as Islamic Banks use the term Investment in place of loan, that is, they contemplate loan as their investment. Operational function of Islamic Banks _____________________________________ 1 Benazir Rahman, Sr. Lecturer in Finance, Department of Business Administration, Northern University Bangladesh, Email: safa.bnkng.du@gmail.com 2 Nusrat Jahan, Sr. lecturer, Department of Business Administration, Uttara University Bangladesh, Email: jn.nusrat@gmail.com 12
  2. Rahman & Jahan differs than that of conventional banks. While conventional banks are more concerned about assessing the creditworthiness of the borrowers while providing loans, Islamic banks gives emphasis on the profitability of the project, as they do focus on doing transaction on P/L sharing basis, and as partners, they have to share the loss (if any occurs). This statement justifies that Islamic Bank consider loan as their Investment, so, in our study the term NPI (Non Performing Investment) is going to be used instead of NPL (Non-Performing Loan). There are eight Islamic banks in our country. This study reflects the true scenario regarding NPIs in Bangladesh and also how adversely it can affect the function of a bank. Some recommendations are made based on the findings, which we have got after conducting some analysis. The major objectives of the study are to find out the root of NPI of Islamic banks in Bangladesh, make a comparison between NPI and ROE and reveal whether there is significant relationship between selected variables and NPI of Islamic Banks. The next section of the paper will focus on literature review; the third section focuses on the methodology followed by the fourth session that is analysis and findings part. The last section includes conclusion and recommendations. 2. Literature Review A non-performing loan, or NPI, is a loan that is in default or close to being in default (Wikipedia, 2017). A bank loan is considered non-performing when more than 90 days pass without the borrower paying the agreed installments or interest. Non-performing loans are also called “bad debt”. (European Central Bank, 2016). Wangai et al. (2014) have examined the effect of non-performing loans on financial performance of microfinance banks (MFBs) in Kenya. A structured questionnaire was used to collect data from the respondents. The authors assert that credit risk significantly negatively affected financial performance of MFBs in Nakuru town. They have concluded that increase in credit risk would significantly reduce the MFBs’ financial performance. Adebisi and Matthew (2015) have examined the impact of nonperforming loans on firms’ profitability of banks in Nigeria. The secondary data obtained from the Annual Report and Statement of Accounts of the NDIC for a period of seven (7) years (2006- 2012) were analyzed using the regression model. The authors have found significant negative relationship between the Nonperforming Loans (NPI) and Return on Assets (ROA); however, they found a positive but insignificant relationship between the Nonperforming Loan (NPI) and Return on Equity (ROE) of Nigerian Banks. Somoye (2010) explored the variations of credit risk of NPIs on bank performances in Nigeria. The study reviewed performances of banks of Nigeria using banking variables such as total assets, total loans, non-performing loans, equity capital and profit-beforetax etc. Chimkonoet. al.(2016) investigated the effect of non-performing loan ratio and other determinants on the financial performance of commercial banks in the Malawi. The author concluded that non-performing loan ratio, cost efficiency ratios and average lending interest rate had a significant effect on the performance of banks in Malawi. They asserted that cash reserve ratio variable was positively related to bank performance but was not significant. 13
  3. Rahman & Jahan Karim et al. (2010) investigated the relationship between non-performing loans and bank efficiency in Malaysia and Singapore through the Tobit simultaneous equation regression model and found that higher non-performing loan diminishes cost efficiency and also lesser cost efficiency increases non-performing loans. Bhattarai (2016) examined the effect of non-performing loan on the profitability of Nepalese commercial banks using pooled data of fourteen commercial banks with 77 observations during the period of 2010 to 2015. The study concludes that profitability of Nepalese commercial is influenced negatively by non-performing loan ratio and positively by the other covariates like as bank size, cost per loan assets and gross domestic product growth rate. Rajan and Dhal (2003) have examined the Nonperforming Loans and Terms of Credit of state owned banks in India. They found that favorable macroeconomic conditions and financial factors such as banks size, cost of credit, credit maturity, and credit orientation have significant impact on the nonperforming loans of Indian commercial banks. Shrestha (2011) has analyzed trend of NPIs and the effect of NPI on share price of the18 sampled commercial banks of Nepal using the descriptive statistics, trend and one factor econometric model. The stratified sampling method was used in selecting the banks for the study. The author assets that NPI of commercial banks is in decreasing trend, however, the total performing loan to total deposit ratio in the industry is an increasing trend during study period. The author further concludes that the real stock price of the commercial banks has a negative association with the levels of their NPIs. Haneef (2012) established that NPIs are increasing due to lack of risk management which threatens the bank’s profitability. Ekanayake and Azeez (2015) studied the determinant factors of credit risk considering non-performing loans (NPIs) as proxy variable in Sri Lanka’s commercial banking sector considering nine licensed commercial banks as a sample and the data taken from the period starting 1999 to 2012. They showed that the level of NPIs can be attributed to both macroeconomic conditions and banks’ specific factors. It reveals that, NPIs tends to increase with deteriorating bank’s efficiency. There is also a positive correlation between loan to asset ratio and NPIs. Meanwhile, banks with high level of credit growth associated with a reduced level of non- performing loans. Larger banks incur lesser loan defaults compared to smaller banks. With regard to macro-economic variables, NPIs vary negatively with the growth rate of GDP and Inflation and positively with the prime lending rate. Anjom and Karim (2016) examined the affiliation between non-performing loans and macroeconomic factors such as annual growth rate of gross domestic production (GDP), real interest rate, inflation rate, public debt as percentage of gross domestic production etc of SAARC countries. With respect to bank specific factors they focused on how nonperforming loans response with the changes of the bank specific factors such as growth in loan, return on equity, return on assets, loan to asset ratio, loan to deposit ratio, Total capital to total asset ratio, operating expense to operating income ratio, total liabilities to total asset ratio, non-interest income to total income ratio. Lata (2015) showed the overall scenario of NPIs, its growth, effect of excess NPIs on the performance of banks by using some ratios and a linear regression model of econometric technique. She found that NPI as percentage of total loans of state owned 14
  4. Rahman & Jahan commercial banks was very high and they hold more than 50 % of total NPIs of the banking industry from FY2006 to FY2013. She wrapped up the study by saying that it is one of the major factors of influencing banks profitability and it has statistically significant negative impact on Net Interest Income of SCBs for the study periods. Jahan (2016) studied the recent status of NPI over the SME industries of Bangladesh and found some key reasons of it such as improper credit analysis and monitoring of loans, high interest rates, and borrower’s quality and so on. Khanam et. al. (2013) studied the status and management of NPI in the banking sector of Bangladesh. The study revealed that various causes like as political influence, diversion of fund, poor industry analysis etc. increases the volume of NPI and stated that different managerial actions like as proper credit analysis, training for loan officials, weaver on interest, loan restructuring etc. will help to reduce the amount. Rahman (2012) sketched the Basel Capital Accord (Basel-II) is one of the roots of NPI as well as credit crisis. Adhikary (2006) examined the presence and challenges of NPI in our banking sector and suggested that the prevention of the ‘flow problem of bad loans’ accompanied by other resolution measures might help to sort out the nonperforming loan mess in Bangladesh. Ater and Roy (2017) analyzed the impact of non-performing loan (NPI) on profitability considering net interest margin (NIM). They found out that non-performing loan (NPI) as percentage of total loans on listed banks in Dhaka Stock Exchange (DSE) is very high and they holds more than 50 % of total non-performing loans (NPIs) of the listed 30 banks in Dhaka Stock Exchange (DSE) for year 2008 to 2013 and it is one of the major factors of influencing banks profitability and it has statistically significant negative impact on net profit margin (NPM) of listed banks for the study periods. Roy et. al. (2014) analyzed the determinants of macro-economic variables on the nonperforming loan of local private commercial banks of Bangladesh. The data range from year 2004 to 2013 covering 18 scheduled banks. Macro-economic variables i.e. GDP growth, inflation and interest spread are selected as the determinants of non-performing loan. The study summed up that the GDP growth and inflation have negative and positive effect on non-performing loan ratio (NPIR) respectively in case of local private commercial banks. The basic gap between the previous literature discussed earlier and this study is that the study mainly focuses on the overall NPI scenario of Islamic banks of Bangladesh which can be rarely seen.The paper focuses on the reasons behind the increasing trend of NPI in Islamic banks which can be a great threat to economy in future After reviewing the literature the following hypothesizes have been derived; H0: There is no significant relationship between ROE and NPI to total investments of Islamic Banks. H1: There is a significant relationship between ROE and NPI to total investments of Islamic Banks. 15
  5. Rahman & Jahan 3. Research Methodology 3.1 Sample size and Sources of data For the study we have selected all 8 Islamic banks of Bangladesh. Union Bank Ltd. Islami Bank Banglade sh Ltd. EXIM Bank Ltd. Social Islami Bank Ltd. ICB Islami Bank Ltd. Al Ararafh Islami Bank Ltd. First Security Islami Bank Ltd. Shahjalal Islami Bank Ltd. We have collected 5 years data (2011-2015) such as NPI to total investments and Return on Equity(ROE)from the selected Islamic banks to show the significance of their relationship. The study is based on both qualitative and quantitative data which is collected from annual audited financial statements of the sample banks. For the study a structured questionnaire has given among the particular sample to collect data which is considered as a primary source of data. A non-comparative scale questionnaire has created by using a five-degree likert scale consisting of such values; Scale 1 Label Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree Since the study is concerned with the Shariah based banking industry, all the employees of Islamic banks in Bangladesh are potentially constituted the sampling frame as a population. For the survey questionnaire has given to the 120bank personnel of 8 Islamic banks15 respondents from each banks. The survey has done at Dhaka city only. 16
  6. Rahman & Jahan Table1: Demographic Information of the Respondent Gender: Age Male 102 25-34 years Female 18 35-44 years 45-54 years Working experiences 75 Less than 1 year 28 1-3 years 11 4-6 years 11 35 32 55 years and above 6 7-9 10 years & years above 15 28 The secondary data which is used in this research is quantitative in nature. Different articles and websites of the selected sample banks are used as secondary source of data. 3.2 Instrumentation To justify the research following factors has been selected; • Lending rates. • Credit Analysis and loan monitoring. • Nature of Borrowers. • Good governance. • Transparency in relationship with customers. • Bureaucratic impact. • Lending purposes. • Verification of Collateral. • Ethical ground of the bankers. • Intention of taking risks. • Changes in economic and political environment. For the study we use descriptive statistics, ranking factors and factor analysis techniques using varimax rotation. KMO test has been used to verify reliability. For all the analysis SPSS 16.0 has been used. Graphical presentation has also shown to focus on the trend of NPI with other factors. For the analysis regression analysis has also used in analysis. For this following variables are selected; Dependent variable: Return on equity (ROE) Independent variable: NPI to total Investments 4. Analysis and Results The trends of 5-year average data of Islamic banks have shown through graphs are as follows; 17
  7. Rahman & Jahan Figure 1: Comparison between NPI to Investments and ROE of Islamic banks Comparison between NPI to Investments and ROE of Islamic banks 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 2011 2012 2013 NPLR 2014 2015 ROE The figure shows that Npl to loans ratio and ROE increased till 2012. After 2012 ROE started decreasing till 2014 and it increased in 2015. The scenario is inverse in case of NPL to Investments ratio which indicates that these variables are negatively related. By analyzing the primary data using SPSS 16.0 following results have found; Table 2: Descriptive Statistics Std. Analysis Mean Deviation N Lending rates are quite high Credit Analysis and loan monitoring are poor Borrowers are analyzed properly Good governance prevails in the organization and it has a positive impact on NPI Relationship with customers is transparent Bureaucratic impact prevails in credit approval Lending purposes are being analyzed properly Collateral is verified properly Ethical ground of the bankers is questionable Intention of taking risks is very high Changes in economic and political environment have an impact on NPI 2.7583 1.20221 2.4583 1.23599 3.8250 1.13510 120 120 120 3.6250 1.15999 120 3.7833 2.9000 3.7000 3.6417 1.9750 2.9000 1.19652 1.24617 1.12720 1.34599 1.28640 1.11068 120 120 120 120 120 120 3.5833 1.11960 120 Rank of Mean values 8 9 1 5 2 7 3 4 10 7 6 18
  8. Rahman & Jahan It can be said from the table 3, nature of borrowers has got the uppermost influence with the highest mean and credit analysis is considered as less important factor with the lowest mean. The ranking based on importance of rest of the factors have also shown. Table 3: KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. Bartlett's Test of Approx. Chi-Square Sphericity df Sig. .849 479.137 55 .000 Sufficient correlation has shown among the variables as the statistic of Kaiser-MeyerOlkin measure of sample adequacy for individual variance is found 0.849 which shows data set is appropriate for further analysis. Bartlett's test for sphericity has also shown that the overall significance of the correlation matrices is acceptable as α is nearly zero. Table 4: Communalities Initial Lending rates are quite high Credit Analysis and loan monitoring are poor Borrowers are analyzed properly Good governance prevails in the organization and it has a positive impact on NPI Relationship with customers is transparent Bureaucratic impact prevails in credit approval Lending purposes are being analyzed properly Collateral is verified properly Ethical ground of the bankers is questionable Intention of taking risks is very high Changes in economic and political environment have an impact on NPI Extraction 1.000 1.000 1.000 .329 .607 .699 1.000 .622 1.000 1.000 1.000 1.000 1.000 1.000 1.000 .666 .485 .605 .573 .603 .467 .278 Extraction Method: Principal Component Analysis. Source: Field survey, 2017 The table 4 shows that after 2 factors are extracted and retained in rotated component matrix the community is 0.329 for 1st variable, 0.607 for 2nd variable and so on. It is considered that extracted values of communalities need to be more than 0.5 for the accuracy of the data analysis. Most of the extracted values are more than 0.5 except the lending rate and the last one which is good for the study. 19
  9. Rahman & Jahan Table 5: Rotated Component Matrixa Component 1 Lending rates are quite high Credit Analysis and loan monitoring are poor Borrowers are analyzed properly Good governance prevails in the organization and it has a positive impact on NPI Relationship with customers is transparent Bureaucratic impact prevails in credit approval Lending purposes are being analyzed properly Collateral is verified properly Ethical ground of the bankers is questionable Intention of taking risks is very high Changes in economic and political environment have an impact on NPI Eigen Value 2 .031 .229 .822 .788 .026 .716 .695 .752 .721 .521 .748 .683 .078 4.096 1.839 Variance explained (%) 37.240 16.718 Cumulative variance explained (%) 37.240 53.958 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 3 iterations. Source: Field survey, 2017 Table 5 shows the first includes 6 sub-factors and it can be seen that among these borrower’s credit worthiness has got the highest importance and Changes in economic and political environment has got the lowest importance. The second factor includes 7 sub-factors and it is found that Ethical ground of the bankers has got the highest importance and Good governance has got the lowest importance. The regression analysis has given following results; Table 6: Results of Regression Analysis and Others Type of bank Dependent Variable Independent variable N R2 D-test t-test Sig. F-test Sig. Beta Relationship Islamic banks ROE NPI to Total Investments 5 0.067 2.545 -0.465 .674 0.216 .674 -0.259 Negative The regression analysis reveals that in case of Islamic banks the relationship between ROE and NPI to total investments is insignificant which means null hypothesis is accepted. 20
  10. Rahman & Jahan 5. Concluding Remarks The study focuses on the reasons behind NPI and the relationship between profitability and NPIs of Islamic banks. Previous literature focused on the relationship between NPL and profitability of conventional banks (Bhattarai 2016; Haneef 2012). Previous studies also focused on NPLs of conventional banks which are driven or caused by interest rate risks but our research endeavored to examine how NPLs have been impacted by interest-free banking. We studied 8 Islamic banks in Bangladesh which do not charge interest rates (that take interest risks out of the NPL as one of the causative factors) and found that NPLs at the Bangladeshi Islamic banks are relatively compared to conventional banks and this finding go unreported in the previous studies (Adebisi and Matthew 2015; Chimkono et al. 2016;Rahman 2012;Roy et. al. 2014; Ekanayake and Azeez 2015).The indispensable gap between the previous literature and this study is that the study mainly focuses on the overall NPI scenario of Islamic banks of Bangladesh which is almost untouched in previous researches. The study reveals that the overall relationship between profitability and NPIs are not significant. The SLR requirements for the Islamic banks are lower than that of conventional banks which is 11.5%. It may be one of the reasons behind the insignificance. The study also focuses on that the banks should be concerned about handling classified investments. The study has faced some limitations like lack of availability of data, lack of transparency in secondary data, time constraint etc. The paper is useful for bankers and academicians especially those who are dealing with Islamic banking. Further research can be done by focusing on the insignificant relationship between NPIs and profitability in Islamic banks. After this study it is recommended that Islamic banks should concentrate on decreasing NPIs otherwise it will affect their growth in the long run. References Adebisi, J.F. & Matthew, O.B. 2015, ‘The Impact of Non-Performing Loans on Firm Profitability: A Focus on the Nigerian Banking Industry’, American Research Journal of Business and Management, Vol. 1, No. 4, Pp.1-7. Adhikary, B.K. 2006, ‘Nonperforming loans in the banking sector of Bangladesh: realities and challenges’, Bangladesh Institute of Bank Management, Pp. 75-95. Akter, R., & Roy, J.K. 2017,‘The Impacts of Non-Performing Loan on Profitability: An Empirical Study on Banking Sector of Dhaka Stock Exchange’, International Journal of Economics and Finance, Vol. 9, No. 3, Pp.126-132. Anjom, W. and Karim, A.M., 2016, ‘Relationship between non-performing loans and macroeconomic factors with bank specific factors: a case study on loan portfolios–SAARC countries perspective’, Elk Asia Pacific Journal Of Finance And Risk Management, Vol. 7, No. 2, Pp.1-29. Bhattarai, Y.R. 2016,‘Effect of Credit Risk on the Performance of Nepalese Commercial Banks’, NRB Economic Review, Pp. 41-64. Chimkono, E.E., Muturi, W.& Njeru, A. 2016, ‘Effect of Non-performing Loans and other Factors on Performance of Commercial Banks in Malawi’, International Journal of Economics, Commerce and Management, United Kingdom, Vol. 4, No. 2, Pp. 549-563. 21
  11. Rahman & Jahan Ekanayake, E.M.N.N., & Azeez, A.A. 2015, ‘Determinants of non-performing loans in licensed commercial banks: evidence from Sri Lanka’, Asian Economic and Financial Review, Vol. 5, No. 6, Pp. 868-882. Haneef, S., Riaz, T., Ramzan, M., Rana, M.A., Hafiz, M.I. and Karim, Y. 2012,‘Impact of risk management on non-performing loans and profitability of banking sector of Pakistan’, International Journal of Business and Social Science, Vol. 3, No. 7, Pp. 307-315. Karim, M.Z.A., Chan S.G.& Hassan S. 2010,‘Bank efficiency and non-performing loans: Evidence from Malaysia and Singapore’, Prague Economic Papers, Vol. 19, No. 2, Pp. 118-132. Khanam, F.A., Hasan, K., Mawla, A.M.H.R. and Khan, R.S. 2013,‘Management of NonPerforming Loans (NPIs) of Banks in Bangladesh -An Evaluative study’. International Academic Research Journal of Economics and Finance, Vol.1, No.3, Pp.1-15. Lata, R.S. 2015, ‘Non-Performing Loan and Profitability: The Case of State Owned Commercial Banks in Bangladesh’, World Review of Business Research, Vol. 5, No. 3,Pp. 171 – 182. Rahman, Q.M. 2012, ‘All about non-performing loan: The Bangladesh scenario’. Financial Express, Vol. 20, No.157. Rajan, R.& Dhal, S.C. 2003,‘Non-performing Loans and Terms of Credit of Public Sector Banks in India: An Empirical Assessment’, Occasional Papers Reserve Bank of India, Vol. 24, No. 3, Pp. 81-121. Roy, S.C., Dey, P.K., & Bhowmik, P.K. 2014,‘Non-performing loans in private commercial banks of Bangladesh: Macro-economic determinants and impacts’, The Jahangirnagar Journal of Business Studies, Vol. 4, No. 1, Pp. 47-57. Shrestha, N.R. 2011, ‘Non-Performing Loans and Stock Prices: A Case of Nepali Commercial Banks’, PYC Nepal Journal of Management, Vol. 4, No.1, Pp. 92-101. Somoye, R.O.C. 2010, ‘The variation of risks on non-performing loans on bank performances in Nigeria’, Journal of Economics and Business Audience, Vol. 9, No.1, Pp. 87-99. Wangai, D.K., Bosire, N. & Gathogo, G. 2014, ‘Impact of Non-Performing Loans on Financial Performance of Microfinance Banks in Kenya: A Survey of Microfinance Banks in Nakuru Town’, International Journal of Science and Research, Vol. 3, No. 10, Pp. 2073- 2078. 22
  12. Rahman & Jahan Annexure I: 5 Years Average Data Used In Regression Analysis Year 2011 2012 2013 2014 2015 NPI to Investments 8.46 9.52 11.57 13.15 12.89 ROE 8.15 9.19 8.26 7.62 8.91 23 View publication stats