Microfinance services and financial performance of small and medium enterprises of youth SMEs in Kisumu County, Kenya

Abstract

Small and Medium Enterprises (SMEs) is an important sub sector for the Kenyan economy like many other developing countries since it employs about 85% of the Kenyan workforce (about 7.5million Kenyans of the current total employment). The current constitutional framework and the new Micro and Small Enterprise Act 2012 provide a new window of opportunity through which the evolution of SMEs can be realized through the devolution framework. However, the impact of devolution on SMEs development depends on the architecture of the regulatory and institutional framework inclined to support SMEs in an economy. Lack of access to credit is a major constraint inhibiting the growth of SMEs sector. The issues and problems limiting SMEs acquisition of financial services include lack of tangible security coupled with inappropriate legal and regulatory framework that does not recognize innovative strategies for lending to SMEs. The study sought to establish the influence of microfinance services on the financial performance of SMEs in Kisumu County, Kenya. The specific objectives were to determine the effect of access to credit, savings mobilization, financial skills training and role modeling on performance of SMEs in Kisumu county.The study was anchored on the following five theories which include women empowerment theory, game theory of microfinance, uniting theory of microfinance, financial sustainability theory and poverty alleviation theory. Empirical literature reviewed scholarly studies on access to credit, savings mobilization, financial skills training and role modeling and their influence on financial performance of SMEs. The study used a descriptive research design. The population of study were the youth owned enterprises in the 7 sub-counties in Kisumu County that were operational. This consisted of 448 respondents who were the proprietors of the enterprises. A sample of 135 respondents was taken which formed 30% of the target population. The primary data was collected by use of self-administered semi-structured questionnaire. Data analysis was done by use of descriptive statistics such as frequencies, percentages, mean scores and standard deviation with the aid of SPSS and presented through tables, charts, graphs, frequencies and percentages.