Credit Risk Management and Level of Non-Performing Loans in Commercial Banks in Kenya
Makori, Nyangori Wilfred
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The management of non-performing loan has been a major challenge facing financial institutions especially commercial banks. According to the Central Bank of Kenya Bank Supervision Annual Report 2014, Non-performing loans increased by 32.4 per cent to Kshs. 108.3 billion in December 2014 from Kshs. 81.8 billion in December 2013. However, the ratio of gross NPLs to gross loans increased marginally from 5.2 per cent to 5.6 per cent in December 2014. The ratio for total loans to total assets of the banking sector for the quarter ended 30th September 2015 was 62.68% a slight increase from 61.38% reported in September 2014. Further, the pile of bad bank loans rose from Kshs 47 billion to Kshs 259 billion to December 2017 in the latest credit officer survey report for the quarter ending December 2017 by the Central Bank of Kenya. This resulted in significant annual increase in the ratio of non-performing loans to gross loans rising to 10.56 per cent from the 9.1 per cent for the ending December 2016. This lead to banks giving profit warnings for coming financial years. The objective of this study was to establish the relationship between credit risk management approaches employed by commercial banks in Kenya and the loans performance using credit risk identification, risk assessment and risk monitoring to measure credit risk management. In order to achieve this objective, both primary and secondary data were be used. The data was collected using a questionnaire. The questionnaire had have both closed and open-ended questions. The closed ended questions enabled the collection of quantitative data while open-ended questions enabled collection of qualitative data. The secondary data obtained from the annual reports of the commercial banks for period 2011 to 2016. The data collected include the amount of credit, number of non-performing loans, number and value of total loans. The collected data was analyzed though descriptive and inferential statistics. The Statistical Package for Social Sciences (SPSS) was used to analyze data. The results were presented in tables, charts and bar graphs. The study established that credit risk identification, credit risk assessment and credit risk monitoring influence loan performance positively. The ANOVA analysis was intended to investigate whether the variation in the independent variables explained the observed variance in the outcome, in this study the loan performance in commercial banks in Kenya. ANOVA findings in this study showed that there was correlation between the predictor variables these are the credit risk identification, credit risk assessment and credit risk monitoring and response variable, loan performance since P value was less than 0.05. This indicated that there was a strong relationship between the study variables.