The Influence Of Technology Adoption, Income Expenditure Disparity, Client Characteristics And Interest Rates On The Uptake Of Mobile Based Lending By Commercial Banks In Kenya: A Case Of Ken

ABSTRACT

The development of mobile technology has increased, causing effects in the banking sector on a global scale. Moreover, there has been an increase in the rapid technological surroundings around the world in the banking industry and the expansion of distribution channels for financial services. The study’s purpose was to investigate the influence of technology adoption, income-expenditure disparity, client characteristics and interest rates on the uptake of mobile-based lending by commercial banks in Kenya, a case of Kenya Commercial Bank. The specific objectives were to establish how technology adoption influences mobile-based lending by commercial banks in Kenya, income-expenditure disparity influences mobile-based lending by commercial banks in Kenya, client characteristic influences mobile-based lending by commercial banks in Kenya, and how interest rates influence mobile-based lending by commercial banks in Kenya. The study was grounded on the diffusion innovation theory, financial intermediation theory and the technology acceptance model. The study was conducted in Nairobi in Kencom house whose target population was 200 respondents. This study employed a stratified sampling of the population, of which a sample size of 133 was selected. Furthermore, a descriptive research design was utilized. Questionnaires were used in gather primary data, and a pilot test of the inquiry carried out to test the validity and reliability of the data. Statistical Package for Social Sciences (SPSS) Version 24 was used to analyse the primary data collected through editing involved checks for incorrectly filled questionnaires, coding by involving groupings of values from the survey. The study applied descriptive statistics as well as regression analysis. Presentation of results was done using figures, tables and charts. From the regression model, the study established the four independent variable’s technology adoption β = 1.551, client characteristic β = 1.485, interest rates β = 1.442 and income-expenditure disparity β = 0.504, where p