The study sought to evaluate the contribution of Fin-Tech to financial inclusion in Kenya. Descriptive research design was used collect and analyse data. The population of the study was all 25,000,000 adult population in Kenya interacting with Fin-Tech in various degrees. The study collected quarterly secondary data regarding financial inclusion and Fin-Tec from CBK database, Communication Authority database and KNBS. The data extracted was entered on data collection sheets in the form of excel sheets. Data on excel sheet were exported to STATA version 15. Measures of dispersal and central tendency were used including minimum, maximum, mean and standard deviation. OLS regression model helped evaluate the effect of Fin-Tech on financial inclusion in Kenya. The study adopted the models. The study examined whether or not the explanatory have significant effect on the dependent variable by comparing the p-value associated with the parameters with 0.05 level of significance. P-values less than 0.05 levels of significance implies significant effect of the explanatory variable on dependent variable. The study established that financial technology and other covariates have a significant effect on financial inclusion as measured by number of banks accounts, deposits and credit to private sector. Further, mobile money had a direct and significant effect on financial inclusion measured by number of bank accounts, deposits and credit to private sector. Agency banking had a significant effect on financial inclusion through number of bank accounts, deposits and credit to private sector. Point of Sale had a direct and significant effect on financial inclusion through number of banks accounts opened and credit to private sector, however, Point of Sale had negative and insignificant effect on financial inclusion through deposits. Diaspora remittances had a direct but not statistical significant effect on financial inclusion through number of bank accounts, deposits and credit to private sector. However, diaspora remittances had significant effect on financial inclusion measured by credit to private sector. The effect of lending rate on financial inclusion through number of bank accounts, deposits and credit to private sector was inverse and statistically significant. Finally, the effect of mobile phone penetration on financial inclusion through credit to private sector, deposits and number of bank accounts was direct and statistically significant. The study thus concluded that financial technology and other covariates have major effect on financial inclusion via number of banks accounts, deposits and credit to private sector. The study recommends to the Central Bank, Communication Authority of Kenya, communication firms and banking institutions to strengthen and deepen mobile money and agency banking. The CBK should put policies in place for securing transactions carried over the point of sale as well as improved POS technology. The study also recommends to the government to put in place policies and strategies for ease of the remittance money by Kenyans working and doing business abroad. The study also suggests to the Central Bank of Kenya, Sacco Regulatory Authority, commercial banks, deposit-taking MFIs to continue lowering the cost of borrowing.

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