Assessing the Effects of Credit Risk Identification on Lending Performance of Commercial Banks in Kenya

Abstract

Credit risk presents a significant threat to commercial banks, a situation that is particularly evident in Kenya. Given the banking sector's critical role in any economy, effective credit risk identification is essential. Credit risk accounts for more than 50 per cent of the total risk faced by commercial banks. Over the years, banks in Kenya have encountered various challenges related to credit risk, which have impacted their lending performance. Therefore, it is crucial to identify credit risk effectively to ensure that lending performance remains stable. Using multiple regression and primary data collected from 42 commercial banks in Kenya in 2019, the study evaluates how credit risk identification affects commercial banks' lending. The results showed that credit risk identification has a significant effect on the lending performance of commercial banks in Kenya. Specifically, having systems that support risk identification was found to be essential. Additionally, the banks' ability to analyse borrowers' sources of funds to assess their loan repayment capacity is vital. Furthermore, having internal guidelines for conducting credit risk identification also significantly influences lending performance. Based on these findings, the study recommends that commercial banks implement a robust technology system that could incorporate Artificial Intelligence (AI) tools to support effective credit risk identification. In addition, full implementation of credit standards could further enhance the various methods in evaluating borrowers' repayment ability when extending loans. This approach could enhance the existing credit risk identification tools and reduce the risk of loan defaults.