Abstract

This study examined some factors that affect Small and Medium Enterprises (SMEs) access to finance. It was done in order to further understand the constraints facing SMEs in accessing finance in Lusaka. The study intended to achieve the following objectives: to examine the extent to which collateral requirements affect SMEs access to finance, to examine the extent to which interest rates affect SMEs access to finance and to examine the extent to which other factors affect SMEs access to finance. The study research questions were formulated to find out the extent to which collateral and interest rates affect access to finance and what other factors do SMEs consider as affecting their access to finance. The study used a mixed method approach (Qualitative and Quantitative research methods) in order to come up with the study findings. The study shows a positive correlation between lack of collateral assets and rejection of credit (r = 0.727) and interest rates (r = 0.202) variables. In view of the study findings, the study recommends that SMEs make use of practical and unconventional means of alternative sources of finance, given the challenges faced with traditional sources of finance. Crowd funding has been recommended as it comes in many forms. Specifically, a form of crowd funding called “Village Banking” can be leveraged on by SMEs. The study also recommends group partnering of SMEs in order for them to create a critical mass for their operations and in order for them to enjoy economies of scale for their businesses. In addition to the above, SMEs are encouraged to improve on their business record keeping such as cash flows and income statements in order for them to attract potential sources of finance such as venture capital investors and/or angel investors. Further research should focus on strategies of how SMEs can finance their operations without entirely depending on borrowing from financial institutions. The study would combine both qualitative and qualitative methods in measuring causality of the associated factors and how they influence SMEs performance by carrying out more sophisticated analysis using statistical software.

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