Credit risk management on financial performance of commercial banks in Nepal
Date
2024
Authors
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Journal ISSN
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Publisher
Shanker Dev Campus
Abstract
The relationship between credit risk and commercial banks performance has been the concern of emerging studies both in developed and developing countries. The overall purpose of this research is to examine and analyze how the selected commercial banks have managed mainly credit risk in this competitive Nepalese banking industry. The specific objective are; to analyze the credit risk position of Nepalese commercial banks, to analyze the indicators of credit risk management of Nepalese commercial banks, and to minimize the credit risks management present in the commercial banks on the basis of NRB guidelines. To fulfil objective of the study, among the 21 commercial banks, only 3 (Kumari Bank Ltd., Machhapuchhre Bank Ltd. and NIC Asia Bank Ltd.) commercial banks have been selected. The study is based on secondary sources of data from 2013/14 to 2022/23.
The study found that MBL has higher concentration risk than KBL and NIC Asia as MBL has extended more loans in few sectors than KBL and NIC Asia. KBL, MBL and NIC Asia has highest ratio in Metal and Electric Products and construction sector, which is 203.76%, 192.83% and 201.75% respectively. In this sector also, the ratio of KBL is higher than that of MBL and NIC Asia. There is wide range of differences in the ratio of different loan sectors of MBL than that of KBL and NIC Asia. Therefore, it is concluded that NIC Asia has higher credit risk or default risk than that of KBL and MBL in terms of its interest on loan. The study found that Total Capital fund to Risk Weighted Asset (RWA) of KBL, MBL and NIC Asia for 10 years. Sample banks have capital adequacy ratio higher than the statutory requirement in all 10 years. The average ratio of KBL, MBL and NIC Asia is 14.94%, 15.72% and 12.04 % respectively. This shows that MBL has slightly higher Capital Adequacy Ratio than KBL and NIC Asia, which signals that MBL is in a bit better position than KBL and NIC Asia. Correlation coefficient regarding PLL with ROA and ROE indicates that there is positive relationship between them but the result is not too sufficient that’s why it is considered as significant. Regression coefficient of PLL is positive but the value is not significant at 5 percent level of significance. The value of multiple coefficient of determination (R2) is 0.829 in NIC Asia bank indicated that 82.9% of total variation in ROA of this bank is explained by independent variables and only 17.1% is explained by other variables. The t value of coefficient of CAR, LLPR, NPLR and CRR are statistically significant given model at 5% level of significance; therefore the regression equation could provide statistically significant explanation of variation in the ROA due to CAR, LLPR, NPLR and CRR.