Digital Credit Borrowing And The Financial Risk Exposure Of Micro And Small Enterprises In Nairobi City County, Kenya

ABSTRACT

Micro and Small Enterprises have specific funding needs in terms of their business growth. Financial institutions that lend MSE’s generally tend to develop long-term relationships, which may further expose lenders to environmental and social issues associated with the enterprise posing financial risks. Digital credit has currently developed as an alternative instrument for providing short-term loans to uninformed borrowers. In free or loosely regulated markets, the use of digital credit may pose serious menaces to consumers, including manipulation, accidental leakages over-indebtedness, identity theft, and fraud. Driven by this knowledge gap, this study sought to investigate the financial risk exposure and the use of the Digital credit borrowing on the Micro and Small Enterprises in Nairobi City County in Kenya. The objectives of this study were to find out through research the Design & Delivery of Digital Credit Loans, Cost of Borrowing the loans, Literacy Levels of the Borrowers, and Credit Risk Management. The information that provided by this research was benefit digital credit lenders, the borrowers, academicians and policy makers. The study adopted the theory of Micro-Loan borrowing Rates, Credit risk Theory, Liquidity Preference Theory and Loanable Funds Theory. A sample of 385 respondents drawn from a population of 21,100-registered Micro and Small enterprises registered in Nairobi City County was used to arrive at the conclusion. Primary data was collected from sample population using open and closed ended questionnaires. The questionnaires were self-administered. The study used descriptive design. The reliability of the questionnaires was determined by Cronbach’s Alpha. The variables were considered reliable because their reliability values exceeded the prescribed threshold of 0.7. The study adopted descriptive research design. Data was coded and sorted by use of SPSS. Descriptive statistics such as percentages, frequencies, mean and standard deviation was used. Afterwards the research findings were presented using pie charts, frequency tables and bar graphs. A multiple linear regression was used to analyze the relationship and draw inferences from research data. The study found out that Digital Credit borrowing and financial risk exposure was predominant because the respondents appreciated the convenience and disbursement speed. Due to the nature of the digital loans, most defaults and late repayments resulted to negative listing at CRB’s. The study indicated that the Design and Delivery, Cost of borrowing the digital loans, Financially Literacy Levels, Credit Risk Management, were statistically significant in the financial risk exposure. The moderating variable of income levels was found to be insignificant. The study recommends transparency and consumer protection, Digital sensitizations and campaigns and regulation of the digital lenders.