Evaluating Fintech Adoption in Kenya's M-Pesa Ecosystem: An Economic Analysis

Thesis Abstract

The rapid expansion of mobile money platforms in Kenya, led by M-Pesa, has transformed financial inclusion and intermediation, yet the precise economic mechanisms through which fintech adoption shapes household welfare, firm productivity, and regional growth remain insufficiently understood. This study addresses the problem of limited empirical insight into how Fintech adoption within the M-Pesa ecosystem influences monetary efficiency, credit access, savings behavior, and transaction costs across urban and rural contexts in Kenya. The aim is to quantify the economic impact of M-Pesa-enabled Fintech adoption and identify the channels through which these effects operate. Specific objectives are (1) to assess the relationship between Fintech adoption intensity and household consumption volatility; (2) to evaluate the impact on small and micro enterprises’ revenue growth and financial resilience; (3) to examine how adoption affects access to formal credit and interest rates for borrowers; (4) to analyze regional disparities in adoption and economic outcomes; and (5) to formulate policy implications for financial inclusion and digital infrastructure investment. The theoretical framework integrates the Technology Acceptance Model (TAM) and the Theory of Financial Intermediation, complemented by the Innovation Diffusion Theory to capture social contagion effects and the Endogenous Growth perspective to link fintech adoption to productivity and growth. A mixed-methods design combines a quantitative cross-sectional survey with qualitative interviews to triangulate findings. The population comprises Kenyan households and micro enterprises in four counties (Nairobi, Kisumu, Mombasa, and Kakamega) selected to represent urban-rural diversity. A stratified random sample of 1,200 households and 400 micro enterprises will be surveyed, while 40 in-depth interviews will be conducted with financial service providers, mobile network operators, and policymakers. Data collection will employ structured questionnaires capturing Fintech usage, transaction costs, income, expenditure, savings, credit access, and business performance, complemented by semi-structured interviews to elicit contextual factors and perceived barriers. Validity and reliability will be ensured through pre-testing, Cronbach’s alpha checks for multi-item scales, and triangulation across data sources. Quantitative analysis will utilize multivariate regression methods to estimate the impact of Fintech adoption intensity on household welfare indicators and firm performance, propensity score matching to address endogeneity between adoption and economic outcomes, and heterogeneity analysis across urban and rural strata. The qualitative component will undergo thematic analysis to identify mechanisms, facilitators, and constraints driving observed quantitative relationships. Robustness checks will include alternative model specifications and sensitivity analyses on key variables such as income level, education, and mobile network quality. The study anticipates finding that higher Fintech adoption within M-Pesa correlates with reduced transaction costs, improved liquidity, and greater financial inclusion, with larger effects for households engaging in savings and remittance activities and for micro firms accessing formal credit channels. Expected results also include evidence of urban–rural disparities, where urban areas exhibit stronger productivity gains while rural areas show incremental improvements primarily in payment efficiency and risk-sharing. The contribution to knowledge lies in providing causal insights into the economic channels through which M-Pesa-based Fintech adoption affects welfare, enterprise performance, and financial access, and in offering context-specific policy guidance for digital infrastructure investment, consumer protection, and inclusive credit policies. The study concludes that targeted interventions—such as interoperable payment standards, affordable credit schemes, and digital literacy initiatives—can amplify the welfare and growth benefits of Fintech adoption in Kenya, while recommendations emphasize strengthening data-driven regulatory oversight, expanding network coverage, and fostering public–private collaboration to sustain inclusive digital finance development.