Credit Risk Management and Performance of Mortgage Lending Commercial Banks in Kenya Ngigi Samuel Mwirikia
Mwirikia, Ngigi Samuel
MetadataAfficher la notice complète
In spite of Kenya‘s mortgage market having grown substantially, it is dominated by large mortgage lending commercial banks pointing to possible restrictions to entry or a likelihood of high risk for tier II as well as III lending commercial banks in Kenya. In 2017, Kenyan mortgage lending commercial banks recorded an average gross non-performing loan ratio of 10.3 percent against the industry recommended Central Bank of Kenya average of 4 percent. In 2018, Kenyan mortgage industry assets was approximated to be 2.5 percent relative to the country‘s gross domestic product with about 24,458 mortgage accounts in the industry. The mortgage sector has in the recent past experienced increased bad mortgage loans. It is thus, from the foregoing statistics the study sought to evaluate credit risk management influence on Kenya‘s mortgage lending commercial banks performance with the objective of establishing the influence of delinquency rates, value at risk, distance to default and bank size on credit risk management of Kenya‘s mortgage lending commercial banks. The study employed credit history score to act as the moderating variable. Merton‘s Default Theory, Portfolio Theory, Theory of Information Asymmetry and Credit Risk Theory guided this study. A census survey on all of Kenya‘s 34 mortgage lending commercial banks in Kenya was utilized. Further, both explanatory and descriptive research designs with positivism as the research philosophy were adopted. The researcher used secondary panel data covering the period 2012 to 2018 with a record survey sheet as the data collection tool. Published audited reports of mortgage lending commercial banks submitted to Central Bank, publications such as such as Banking Supervision Report, and Economic Review Reports by CBK provided data required. Analysis of the data gathered was carried out using STATA after being subjected to the following diagnostic tests, for purpose of addressing any violation of ordinary least squares assumptions; multicollinearity, Hausman, normality, stationarity heteroscedasticity and autocorrelation tests. Panel regression of coefficients results displayed that there was a positive as well as substantial correlation between delinquency rate and mortgage lending commercial banks performance, negative as well as substantial correlation between value at risk and mortgage lending commercial banks performance, positive and substantial association between distance to default and performance of mortgage lending commercial banks and a negative and statistically significant correlation between size of bank and performance of mortgage lending commercial banks. Credit history score has a substantial moderating impact on the affiliation between credit risk management and mortgage lending commercial banks performance in Kenya since coefficient of determination rose after moderation. These findings suggest that mortgage lending commercial banks might require to improve their credit risk monitoring strategies by using more precise tools like credit scoring to reduce high non-performing loans levels in the mortgage sector, and that regulatory authorities should regularly assess the mortgage industry's lending behavior. By retrieving and analytically assessing client background information, credit scoring can estimate the likelihood of loan default. Even for consumers with the best credit scores, loan defaults occur despite effective credit risk management. More research into the demographic characteristics that lead to mortgage loan default could be done.