The Relationship Between Fintech Adoption and Performance of Commercial Banks in Kenya

Abstract

This research investigates the dynamic relationship between Financial Technology (Fintech) adoption and the performance of commercial banks in Kenya. Fintech, characterized by disruptive innovations in the financial sector, has become integral to global financial institutions' evolution. In Kenya, Fintech adoption is driven by widespread mobile phone usage and an increasingly financially literate population, leading to collaborations between banks and fintech firms. The study explores Fintech adoption comprehensively, considering innovations like cloud services, APIs, mobile applications, artificial intelligence, digital ID, and machine learning. It analyzes Fintech's impact on financial markets, emphasizing its role in bridging gaps left by traditional financial institutions and expanding access to financial products. Financial performance, crucial for commercial banks, is assessed through Return on Capital (ROE) and Earnings Ratio (ROA). The study establishes that up to 83.9% of commercial banks' financial performance in Kenya can be attributed to registered mobile banking users, mobile payments, risk and financial inclusion, and amounts invested. Positive correlations are found between financial performance and these factors, highlighting their significance. The conclusions reveal that a rise in registered mobile banking users leads to a 0.72 drop in financial performance, while mobile payments contribute to a 0.67 increase. Risk and financial inclusion positively impact financial performance by 0.634 percentage points, and amounts invested increase financial performance by 0.549 for each additional unit. Policy recommendations include reviewing mobile transaction security policies, fostering collaborations with fintech firms, and continuous credit policy review. The study acknowledges limitations, such as the reliance on a ten-year data span and the exclusion of certain variables. Suggestions for further research propose a more extensive investigation into all facets of fintech, extending the study duration, and exploring correlations across various sectors within East African commercial banks using longitudinal data over twenty years. The subsequent chapters detail the research methodology, data analysis, and findings. The research design utilizes descriptive methods, employing a census approach involving all management employees of the 38 commercial banks in Kenya. Secondary data from the Central Bank of Kenya and the Kenya National Bureau of Statistics is analyzed using SPSS version 23, employing regression models. The findings, presented in Chapter Four, indicate a positive correlation between fintech factors and financial performance. The study recommends longer time frames and broader variables for future research. Chapter Five provides a comprehensive summary, emphasizing the model's significance, concluding findings, and policy recommendations. It recognizes limitations and suggests avenues for further research, contributing valuable insights for industry stakeholders and policymakers