Volume 6 • Issue 1 • PP: 09–17 • 2026
Digital Financial Technology in Egypt: Determinants, Barriers, and Machine Learning Evidence on FinTech Adoption and Financial Inclusion
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© 2026 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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Despite the rapid growth of financial technology in Egypt, the socioeconomic factors influencing the adoption of digital financial services at the household level are still not fully understood. This paper presents an Adoption Prediction Model (APM) of Hybrid FinTech (Hybrid-FinTech) model using binary logistic regression together with ensemble classifiers, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), which is validated using stratified cross validation. The framework introduces a cross-paradigm agreement criterion that ensures that the rankings obtained by the coefficient and machine learning feature importance are compatible, yielding a dual assessment that didn’t exist in either paradigm alone. Empirical analysis finds that internet access and own mobile phone are the most common structural enablers of FinTech adoption with odds ratios that significantly outperform any of the demographic and income variables. The rate of formal bank account ownership has a strong independent positive impact, which suggests complementarity between digital and traditional financial services. The income, educational and urban-rural gaps are striking, and suggest a deep FinTech divide that cannot be bridged entirely by infrastructure. The strong generalisation that is seen in cross-validation is true for all population subgroups. The findings have direct implications for the National Financial Inclusion Strategy, designed by Egypt, and proportionate FinTech regulation.
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