Islamic vs. Conventional Banking in the Age of FinTech and AI: Evolving Business Models, Efficiency, and Stability (2020–2024)

This study investigates the differential impacts of FinTech and Artificial Intelligence (AI) adoption on the business models, operational efficiency, and financial stability of Islamic versus conventional banks. Utilizing a balanced panel dataset of 26 banks across 11 countries from 2020 to 2024, the research employs an empirically derived 7-point FinTech Index and fixed-effects panel regression models to rigorously assess these relationships. Our findings reveal a significant and persistent lag in FinTech adoption by Islamic banks compared to their conventional counterparts, despite both exhibiting consistent upward trends in digital integration. Crucially, the empirical results demonstrate that higher FinTech adoption universally enhances bank efficiency (evidenced by reduced cost-to-income ratios and increased return on assets) and bolsters financial stability (measured by the Z-score) for both Islamic and conventional banking models. Contrary to some initial hypotheses, the study finds no statistically significant evidence of a differen-tial impact of FinTech on either efficiency or stability between the two bank types; both benefit comparably from digital transformation. Furthermore, while Islamic banks exhibit a higher baseline level of efficiency and stability, FinTech adoption does not appear to in-duce a unique efficiency-stability trade-off for them. These findings challenge assump-tions regarding divergent FinTech impacts based on banking models, highlighting the universal role of digital transformation in fostering financial system resilience and opera-tional sustainability. The study provides critical policy implications for regulators to foster enabling environments and support Islamic banks in closing their adoption gap, along-side strategic insights for banks to leverage FinTech for sustained performance in the evolving financial landscape