RegTech Enabled Automation Transforming Regulatory Compliance and Supervision in Fintech Ecosystems

Abstract

We examine how RegTech-enabled automation transforms regulatory compliance and supervision effectiveness across global fintech ecosystems. We apply the AutoReg Compliance Model to integrate automated reporting systems, real-time risk monitoring, and compliance data integration with supervisory Capacity as a conditioning factor. We analyze a cross-country sample of 34 leading fintech fi rms drawn from the CB Insights Fintech 100 using standardized indices and moderated regression analysis. We find that automated reporting systems improve compliance accuracy and regulatory transparency, while real-time risk monitoring shortens supervisory response cycles and strengthens enforcement consistency. Compliance data integration enhances visibility but yields uneven enforcement gains unless supervisory Capacity is strong. The central contribution lies in identifying an absorption mechanism through which supervisory skills, resources, and digital readiness convert automated compliance outputs into effective regulatory action. This refines regulatory governance theory by demonstrating that automation delivers differentiated, stage-specific effects rather than uniform improvements. The findings explain why similar RegTech investments generate uneven outcomes across jurisdictions and offer globally relevant guidance for regulators and fintech firms seeking scalable, evidence-driven supervision and policy design.