Relationship Between Credit Risk Management and Financial Performance of Grain Milling Firms in Mombasa County

Abstract

The study aimed to determine how credit risk management affects financial performance of grain milling firms in Mombasa County and was directed by the following three theories; Moral Hazard Theory, Credit Risk Theory and Liquidity Preference Theory. The study used a descriptive research design that granted the researcher to explain the characteristics of the research variables. The research focused on all the 8 grain milling firms in Mombasa County. Secondary data was collected from annual financial statements obtained from the finance and accounts managers and was recorded on a data collection sheet. The collected data was analyzed using the help of SPSS version 20. Descriptive statistics was used to describe the variables using: mean, standard deviation, skewness and kurtosis. Correlation analysis was used to determine the association of the variables in form of a correlation matrix. Multiple regressions was used to analyze the quantitative data. The descriptive statistics revealed that most grain milling firms were giving credit of more than 30 days that is considered the usual credit terms of most firms. The overdue accounts that was measured by percentage of bad debts indicated a highly skewed distribution curve. Liquidity as measured by quick ratio had an average figure of 1.2 which was higher than the ideal acid test of 1.1 while the liquidity of the firms followed a symmetrical distribution. The skewness results indicated that the firm sizes followed a symmetrical distribution. Kurtosis for all the variables followed a normal distribution. It was observed that there was a significant positive association between credit period and ROA. The relationship between credit period and ROE followed a weak positive correlation. Secondly, a significant positive correlation existed between ROE and liquidity as measured by the quick ratio. Liquidity and ROA also portrayed a significant positive correlation. Thirdly, there was a significant negative correlation between overdue accounts and ROA. This also corresponded to a significant negative correlation between overdue accounts and ROE. Lastly, we observed an insignificant positive correlation between size and ROA. This also corresponded to a significant positive correlation between overdue accounts and ROE. The regression coefficients indicated a positive significant relationship between ROA and credit period with a beta of 0.001. Overdue accounts, liquidity and size did not have a significant impact with ROA. The regression coefficients also postulated a positive significant impact between ROE and credit period with a beta of 0.001. There is also a significant negative relationship between ROE and overdue accounts. Size and liquidity did not have any significant relationship with ROE. The study concluded that having overdue accounts negatively impacts on the ROA and ROE of a company hence recommending managers to strive to enforce prompt payment of company debtors. The study also concluded that credit period as measured by average collection period significantly affected financial performance of grain milling firms in Mombasa County depicted by significant positive correlation between credit period and ROA therefore recommending that credit should be cautiously extended to its customers so as to increase its financial performance.