Title :	Factors affecting credit risk in Nepalese commercial banks
Material Type:	printed text
Authors:	Rakshya Gautam, Author
Publication Date:	2018
Pagination:	107p.
Size:	GRP/Thesis
Accompanying material:	11/B
Languages :	English
Descriptors:	Bank loans
Class number:	332.175
Abstract:	Banks primarily involve in financial intermediation activities in an economy. The bank credit creation is considered as one of the major functions carried out bythe banks where it contributes to the provision of the necessary funding to thehouseholds, businesses and government. By providing loans to borrowers, banks canearn profit from charging interests and services fees. However, this service leads thebanks expose to credit risk when borrowers do not pay back the loan as promised. Credit risk arises from nonperformance by a borrower. According to Ouhibi and Sami (2015), non-performing loans (NPLs) serve as a guide on the quality of the assets, credit risk and efficiency in the allocation of resources to productive sectors. Lopez and Saidenberg (2000) defined credit risk as the degree of value fluctuations in debt instruments and derivatives due to changes in the underlying credit quality of borrowers and counterparties. Ideally, the level of loan loss provisioning, should be able to reflect the beliefs of bank management on the quality of the loan portfolio that they have. In other words, it should indicate that provisions should be able to cover the whole spectrum of expected credit losses if they are to think of provisions as a measure of true credit risk (Dugan, 2009). This study attempts to examine the factors affecting credit risk in the Nepalese commercial banks. The study is based on the secondary data which are gathered for 18 commercial banks in Nepal with 126 observations for the period of 7 years from 2009/10 to 2015/16. The secondary data are collected from the Banking and Financial Statistics and Bank Supervision Report published by Nepal Rastra Bank and annual reports of the selected commercial banks. The research design adopted in this study is descriptive and causal comparative research design. Therefore, regression models are estimated to test the significance and importance of factors affecting credit risks in Nepalese commercial banks. The result shows that average non-performing loan is highest for the SUBL (2.98 percent) and lowest for SCBL (0.56 percent). The average loan loss provision is highest for the HBL (Rs. 821.72 million) and lowest for NBSI (Rs. 89.38 million). The average capital adequacy ratio is highest for SCBL (13.85 percent) and lowest for HBL (11.03 percent). BOK has highest average credit to core capital deposit ratio (84.00 percent) and SCBL has lowest average credit to core capital deposit ratio (153.07 percent). NABIL has highest average return on assets (2.55 percent) and MBL has lowest average return on assets (0.71 percent). The average total loan to total assets ratio is highest for SBL (74.11 percentage) and lowest for SCBL (45.432 percentage). NABIL has the highest average total assets (size) (82.461 billion) and NCC has lowest total assets (size) (22.858 billion). The gross domestic product growth rate is highest in the year 2013/14 (5.99 percent) and lowest for the year 2015/16 (0.77 percent). The inflation rate is highest in the year 2015/16 (9.91 percent) and lowest for the year 2014/15 (7.20 percent). The descriptive analysis shows that the average the average capital adequacy ratio, credit to core capital deposit ratio, return on assets, total loan to total assets ratio, bank size, gross domestic product and inflation are 12.17 percent, 77.47 percent, 1.59 percent, 65.82 percent, 3.81 percent and 9.07 percent for the selected commercial banks. The correlation matrix shows that capital adequacy ratio, return on assets, bank size, and inflation have negative relationship with the non-performing loans whereas credit to core capital deposit ratio, total loan to total assets ratio and gross domestic product have positive relationship with the non-performing loans. The result shows that capital adequacy ratio and return on assets are negatively correlated to loan loss provisions. The credit to core capital deposit ratio, total loan to total assets ratio and bank size are positively correlated to the loan loss provisions. Furthermore, the gross domestic product and inflation is negatively correlated to the loan loss provisions. The regression analysis shows that capital adequacy ratio has a significant and negative impact on non-performing loans indicating that higher the capital adequacy ratio, lower would be the non-performing loans. Likewise, return on assets, total loan to total assets ratio, and inflation have negative impact on non-performing loans which means higher the return on assets, total loan to total assets ratio, and inflation lower would be the non-performing loans. The beta coefficient is positive for gross domestic product growth rate which shows that increase in GDP leads to increase in non-performing loan ratio. Likewise, the positive beta coefficient of capital adequacy ratio concludes that higher the capital adequacy ratio, higher would be the loan loss provisions while the positive beta coefficients of credit to core capital deposit ratio and gross domestic product growth rate. Similarly, the beta coefficients are negative for return on assets showing negative impact of return on assets on loan loss provisions, higher would be the loan loss provisions. Likewise, the beta coefficients are negative for total loan to total assets ratio and inflation. The results show that bigger the bank size higher would be the loan loss provisions.

Factors affecting credit risk in Nepalese commercial banks [printed text] / Rakshya Gautam, Author . - 2018 . - 107p. ; GRP/Thesis + 11/B.
Languages : English

Descriptors:	Bank loans
Class number:	332.175
Abstract:	Banks primarily involve in financial intermediation activities in an economy. The bank credit creation is considered as one of the major functions carried out bythe banks where it contributes to the provision of the necessary funding to thehouseholds, businesses and government. By providing loans to borrowers, banks canearn profit from charging interests and services fees. However, this service leads thebanks expose to credit risk when borrowers do not pay back the loan as promised. Credit risk arises from nonperformance by a borrower. According to Ouhibi and Sami (2015), non-performing loans (NPLs) serve as a guide on the quality of the assets, credit risk and efficiency in the allocation of resources to productive sectors. Lopez and Saidenberg (2000) defined credit risk as the degree of value fluctuations in debt instruments and derivatives due to changes in the underlying credit quality of borrowers and counterparties. Ideally, the level of loan loss provisioning, should be able to reflect the beliefs of bank management on the quality of the loan portfolio that they have. In other words, it should indicate that provisions should be able to cover the whole spectrum of expected credit losses if they are to think of provisions as a measure of true credit risk (Dugan, 2009). This study attempts to examine the factors affecting credit risk in the Nepalese commercial banks. The study is based on the secondary data which are gathered for 18 commercial banks in Nepal with 126 observations for the period of 7 years from 2009/10 to 2015/16. The secondary data are collected from the Banking and Financial Statistics and Bank Supervision Report published by Nepal Rastra Bank and annual reports of the selected commercial banks. The research design adopted in this study is descriptive and causal comparative research design. Therefore, regression models are estimated to test the significance and importance of factors affecting credit risks in Nepalese commercial banks. The result shows that average non-performing loan is highest for the SUBL (2.98 percent) and lowest for SCBL (0.56 percent). The average loan loss provision is highest for the HBL (Rs. 821.72 million) and lowest for NBSI (Rs. 89.38 million). The average capital adequacy ratio is highest for SCBL (13.85 percent) and lowest for HBL (11.03 percent). BOK has highest average credit to core capital deposit ratio (84.00 percent) and SCBL has lowest average credit to core capital deposit ratio (153.07 percent). NABIL has highest average return on assets (2.55 percent) and MBL has lowest average return on assets (0.71 percent). The average total loan to total assets ratio is highest for SBL (74.11 percentage) and lowest for SCBL (45.432 percentage). NABIL has the highest average total assets (size) (82.461 billion) and NCC has lowest total assets (size) (22.858 billion). The gross domestic product growth rate is highest in the year 2013/14 (5.99 percent) and lowest for the year 2015/16 (0.77 percent). The inflation rate is highest in the year 2015/16 (9.91 percent) and lowest for the year 2014/15 (7.20 percent). The descriptive analysis shows that the average the average capital adequacy ratio, credit to core capital deposit ratio, return on assets, total loan to total assets ratio, bank size, gross domestic product and inflation are 12.17 percent, 77.47 percent, 1.59 percent, 65.82 percent, 3.81 percent and 9.07 percent for the selected commercial banks. The correlation matrix shows that capital adequacy ratio, return on assets, bank size, and inflation have negative relationship with the non-performing loans whereas credit to core capital deposit ratio, total loan to total assets ratio and gross domestic product have positive relationship with the non-performing loans. The result shows that capital adequacy ratio and return on assets are negatively correlated to loan loss provisions. The credit to core capital deposit ratio, total loan to total assets ratio and bank size are positively correlated to the loan loss provisions. Furthermore, the gross domestic product and inflation is negatively correlated to the loan loss provisions. The regression analysis shows that capital adequacy ratio has a significant and negative impact on non-performing loans indicating that higher the capital adequacy ratio, lower would be the non-performing loans. Likewise, return on assets, total loan to total assets ratio, and inflation have negative impact on non-performing loans which means higher the return on assets, total loan to total assets ratio, and inflation lower would be the non-performing loans. The beta coefficient is positive for gross domestic product growth rate which shows that increase in GDP leads to increase in non-performing loan ratio. Likewise, the positive beta coefficient of capital adequacy ratio concludes that higher the capital adequacy ratio, higher would be the loan loss provisions while the positive beta coefficients of credit to core capital deposit ratio and gross domestic product growth rate. Similarly, the beta coefficients are negative for return on assets showing negative impact of return on assets on loan loss provisions, higher would be the loan loss provisions. Likewise, the beta coefficients are negative for total loan to total assets ratio and inflation. The results show that bigger the bank size higher would be the loan loss provisions.