Credit risk management processes and the operational performance of agricultural cooperatives in Nairobi Metropolitan area: moderated by firm size

Abstract

The access to finance for agricultural activities remains a major challenge for farmers, particularly small-scale farmers. Despite agriculture's substantial contribution to Kenya's GDP, lending to the sector remains disproportionately low. Therefore, the study sought to examine the effect of credit risk management processes and the performance of agricultural cooperatives in Nairobi Metropolitan area; moderated by firm size. The specific objectives were: to establish the effect of credit risk assessment, credit risk monitoring, credit risk identification and credit risk control on the performance of agricultural cooperatives in Nairobi Metropolitan area. The study is anchored on Credit Risk Theory, Credit Rationing Theory, and Information Asymmetry Theory. The study adopted a positivist research philosophy; the correlational research design was also used. The population of interest in this study was 40 agricultural cooperatives registered and active in the Nairobi Metropolitan Area that features Nairobi, Kiambu, Machakos, Kajiado and Murang’a counties. Primary data was collected from 120 Credit Officers (3 individuals per cooperative). Descriptive statistics was used to examine the quantitative data and provide percentage ratings and frequencies. Credit risk assessment was found to be positively and significantly correlated with performance. The study found that credit risk monitoring was positively and significantly correlated with performance; credit risk identification was positively and significantly correlated with performance; and firm size has a positive and significant moderating effect on the relationship between credit risk management processes and the performance of agricultural cooperatives in Kenya. Since the Odds Ratios for credit assessment and credit risk monitoring are both < 1, this indicates lower odds of these variables falling into a higher category; whereas given that the ORs for credit risk identification and credit risk control are > 1, this indicates higher odds of these variables falling into higher category. The p-values for these variables indicated that Credit Risk Assessment and Credit Risk Identification have a significant impact on the likelihood of belonging to a higher category of Performance; whereas Credit Risk Monitoring and Credit Risk Control do not have a significant impact on the likelihood of belonging to a higher category of Performance. The study recommended that the Government should reinforce its credit information sharing policies by involving key stakeholders such as Credit Reference Bureaus as well as all financial institutions including agricultural cooperatives so as to promote more responsible lending. The management of the cooperative should establish robust internal policies and procedures to act as a first line of debt recovery including strict appraisal of loan applications on the basis of the borrower’s ability to repay, and having a first lien over a member’s shares or deposits that the cooperative can use to recover debts as a way of enhancing credit monitoring and control.