Does Cybersecurity Influence the Impact of AI on Bank Risk-Taking? Evidence from Dual-Banking Countries - Hasanul Banna; Masagus M. Ridhwan; Rudy Marhastari (Journal of Islamic Monetary Economics and Finance, 2026)
Using 5,806 bank–year observations from 17 Asian and African economies over the years 2012–2022, we examine how artificial intelligence (AI) adoption influences bank risk-taking and whether cybersecurity capacity moderates this relationship. We find that AI intensity is associated with higher risk-taking at prevailing adoption levels. We also note that their relationship is concave, suggesting a shift from “risk-ramping” during early deployment to “discipline” as model governance and monitoring mature. We also find that stronger cybersecurity attenuates AI’s marginal risk effect. Heterogeneity is evident: conventional banks exhibit higher turning points, reflecting a longer risk ramp, whereas Islamic banks peak earlier, consistent with stricter governance structures and more risk-averse practices. Results are robust in various sensitivity analyses. The findings suggest that AI scaling in banking requires synchronized advancement in cybersecurity and a model-risk management framework, aligned with evolving supervisory doctrine on digital resilience and AI governance.