Effect of Fintech Services on Financial Inclusion in Kenya

Abstract Many research studies have been done to investigate the subject of financial inclusion. However, there has been no recent study on the impact of FinTechs on Financial Inclusion in Kenya. This study investigates how FinTechs have affected Financial Inclusion in Kenya based on FinTech and financial inclusion data from audited individual Company financial statements and the Central Bank of Kenya. The scope of the study was in the realm of the republic of Kenya. The general objective of the study was to investigate the effects of the various FinTech services on financial inclusion in Kenya. The specific objectives of the study are; to determine the impact of credit-oriented, savings-oriented and transactional- oriented FinTechs on financial inclusion in Kenya. The quick acceptance of FinTechs in Kenya, coupled with the mobile banking platforms already in place, has proven the possibility of opening up opportunities for Kenyans, giving them more credit and savings as well as transactional access options with these kinds of technologies. The Innovation Diffusion Theory, Financial Intermediation Theory and the Silber’s Constraint Theory of Innovation were used to explain various concepts of FinTechs and the variables investigated. The study used descriptive design methodology and utilized panel secondary data gathered from annual reports and financial statements of regulated banks and through independent agencies like the Central Bank of Kenya on various financial inclusion parameters. Inferential and descriptive statistics methods were used to interpret and analyze the data and information collected. Descriptive statistics applied trend analysis with mean, maximum, and minimum values being explained over the years for the variables being investigated in the study. Among the inferential statistical techniques applied in the study, included Pearson’s correlation and regression analysis. These techniques were used to demonstrate a causal relationship between FinTechs services and financial inclusion. Data was investigated using a statistical software–IBM SPSS to explore and determine the correlation and regression relationship between the dependent variable (financial inclusion) and each independent variable. Tables and figures were effectively used to present the data. The correlation and regression results showed a positive relationship between the dependent variables (financial inclusion) and the FinTech services. Research findings indicated a regular increase in the number of FinTech accounts since 2007. However, FinTech credit services and savings services picked up in 2011 and there has also been a steady rise till the end of 2021. The findings show that there is a positive link between the FinTech transactional services, FinTech savings services, and the dependent variable (financial inclusion). However, they show a negative correlation between FinTech credit services and financial inclusion. The limitations of the study include the possibility of bias given that it is dependent on information given by FinTech services to the Central Bank of Kenya as well as its own reports. Another limitation of the financial inclusion data is that it is provided on an annual basis thus introducing assumptions that the financial inclusion index has been the same for that year from the months of January to December. In terms of recommendations for further study, there is a need for more research based on other financial innovations like internet banking platforms and agencies, etc., to conclude on whether the findings follow the same trends as the ones in this study. Scoping to the larger East African Region or smaller counties can be done using the same variables to assess whether the different economies influence the findings to make them consistent.