The Relationship Between Core Capital And Financial Performance Of Commercial Banks In Kenya

Abstract

This research was undertaken to determine the relationship between core capital and financial performance of commercial banks in Kenya. So far, the studies available have arrived at different findings. This study will be aimed at contributing to determining what proportion of core capital influences performance of commercial banks in Kenya. The researcher ran an explanatory study on 33 out of the 43 banks in Kenya between January 2011 and December 2015. Data was analysed by SPSS software version 21 and was presented using graphs and frequency tables. Secondary data obtained from the CBK’s Bank Supervision Annual Reports was analysed through multiple linear regressions. Return on assets was used to measure financial performance while shareholders equity and retained earnings, current ratio, log of sales and assets less obligations were used to measure core capital, liquidity, bank size and solvency margin respectively. The results demonstrated that there exists a strong positive linear relationship between return on assets and core capital, a weak positive relationship between liquidity, solvency margin and return on assets and a weak negative relationship between size and return on assets. It also showed that 42.8% of the financial performance is determined by the four independent variables implying that the selected independent variables are important determinants of bank’s financial performance as they explain almost half of its changes. Consistent with previous estimations that inadequate capital in the banks was a cause of less financial performance in the commercial banks this study determined that banks have a responsibility to ensure their capital base is adequate enough to be able to offer loans and other vital financial services to their customers. The study recommended that the banks should ensure their capital base is adequate enough to be in a position to earn higher revenues and make higher profits. Analysis of variance (ANOVA) was used to confirm the findings of regression. The critical F value at 2.74was less than the computed value at 26.196. This confirms that overall the multiple regression model was statistically significant, in that it was a suitable prediction model for explaining how the selected independent variables affects the financial performance of commercial banks.