The rapid digitalisation of financial services has fundamentally transformed the regulatory landscape, compelling regulators and regulated entities to rethink how compliance, supervision, and risk governance are designed and operationalised. Regulatory Technology (RegTech) has emerged at the intersection of law, finance, and data science as a response to mounting regulatory complexity, accelerated innovation, and heightened societal expectations regarding transparency, fairness, and accountability. Drawing exclusively on the provided scholarly and institutional references, this article develops an integrated, theory-driven examination of RegTech as both a technological and normative project. It situates RegTech within broader traditions of principles-based regulation, risk-based supervision, and data-driven governance, while critically analysing the implications of artificial intelligence and machine learning for regulatory compliance, financial stability, and fundamental rights. The article adopts a qualitative doctrinal and conceptual methodology, synthesising insights from legal scholarship, financial regulation, political philosophy, and information systems research. The findings suggest that RegTech is not merely a tool for efficiency gains, but a transformative infrastructure reshaping the epistemic foundations of regulation itself. However, this transformation introduces new challenges, including algorithmic opacity, fairness concerns, data protection tensions under regimes such as the GDPR, and asymmetries between large incumbents and smaller organisations. The discussion highlights the need for a recalibrated regulatory imagination that aligns technological capability with principles-based norms, democratic accountability, and institutional resilience. The article concludes by outlining future research and policy directions aimed at steering RegTech development toward socially legitimate and systemically robust outcomes.

RegTech, financial regulation, artificial intelligence

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