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Fredrick Gitahi Gichuki - PhD Candidate, Doctoral School of Entrepreneurship and Business, Faculty of Finance and Accountancy, Budapest Business School, Hungary. Part Time Lecturer, Karatina University, Kenya. County Credit Officer, Youth Enterprise Development Fund, Nyandarua County, Kenya


The World Council of Credit Unions recently highlighted the Kenyan Savings and Credit Cooperative Societies’ sub sector as the fastest growing in the world. The growing popularity and landmark growth of the sub sector is driven by the ability of the entities to meet clients credit needs on better and easier terms than other players in the financial sector. Scholars are in consensus that credit management is the foundation for stability and growth of modern-day enterprises. The research therefore sought to establish the influence of collections policy on the financial performance of the Savings and Credit Cooperative Societies in Nyeri Central Sub County of Kenya. The study was particularly interested with the financial aspects of firm performance and specifically exploited profitability ratio aspects measured through Return on Investment. The study also considered Credit Risk Exposure measures namely Portfolio at Risk and Write off Ratio The study was anchored on the Information Asymmetry Theory, Agency theory as well as the Transaction Cost Theory as the key guiding theoretical models. The study adopted a census study of all the 15 active Savings and Credit Cooperative Societies in Nyeri Central Sub County. The study used both primary and secondary data pieces. Questionnaires were the choice tools for collecting primary data. The questionnaire was dropped in person and then picked at a later date. The questionnaire was tested for validity and reliability using a pilot study, seeking expert opinion and Cronbach’s Alpha Reliability Analysis. Financial performance was considered for 5 financial years 2012-2016 for better understanding of performance over time. Secondary resources from the SACCO societies Regulatory Authority publications and reports were also useful. The study used the Statistical Package for Social Sciences to generate both descriptive and inferential statistics. The results of the multiple regression analysis established that collections policy (β=1.425, p=0.05) was a statistically significant predictor of financial performance. Pearson correlation analysis results indicated that collections policy (r=0.721, p=0.030) has a very strong and statistically significant relationship with financial performance. A recommendation was made on need to tighten the collections policy and embrace a stringent as opposed to lenient collections framework in the tune of the agency theorists.

Full Length Research (PDF Format)