Effects of Liquidity Risk on Financial Performance of Commercial Banks in Kenya

Abstract

Today’s business environment is extremely volatile. Interference of business norms is not only subjected to externalities but also to internal perspectives. Yes, competition is a major source of change and success in many areas but internal self-sufficiency and management has also proved to be an unavoidable stakeholder. In the banking industry, which is the focus of this research project, internal soundness contributes a great deal on market sustainability. Otherwise shortcomings prevail and failure becomes difficult to manage. Liquidity risk remains to be among major exposures, to an extent that it hold the highest factor rate. Banks must then ensure that they hold high liquidity levels. However, there also exists a divergent school of thought arguing that too much and too low liquidity imparts negatively on profits. Therefore raising two question on how to establish an optimum level of liquidity and its effects on financial performance. This research project focuses on the effects of liquidity risk on financial performance of banks by narrowing down to commercial banks in Kenya. To establish literature base, related scholarly writing have been analysed against the shiftability theory, finance distress theory and commercial loan theory. This study uses liquidity coverage ratio and net loans issued to measure liquidity risk while bank size and capital adequacy are used as control variables. Financial performance has also been depicted using return on equity. The study utilizes descriptive research design and a census banks population. The population include all 41 commercial banks in Kenya. Collection of quantitative data on the key parameters was done by use of a study guide. Data analysis was then carried out by use SPSS Version 21.0 and emulated through use of correlation and regression. Validity of the regression model was also established by use various diagnostic tests that include normality, homoscedasticity and multicollinearity. A response rate of 85% was attained as data from 7 banks was not adequately established. Diagnostic tests were performed accordingly on the analysis model. The coefficient of determinant (R2) indicated a statistical value at 38.3 %, depicting that the model explains only 38.3% of the return on assets which in this case denotes financial performance. This shows that there are other factors that affect return on equity apart from liquidity coverage ratio and loans issued and the control variables (bank size and capital adequacy). Correlation analysis shows a positive correlation between return on assets and Liquidity coverage ratio at 0.0016, net loans issued at 0.567 and bank size at 0.597. Capital adequacy was found to have a negative effect at -0.07. From regression it was established that liquidity coverage ratio, had a positive significant effect on financial performance of commercial banks in Kenya.