FinregE outlines five-pillar framework for UK AI regulatory adoption

By Milan Rojan

FinregE has unveiled a five-pillar framework to help financial institutions align AI adoption with the UK’s evolving regulatory expectations, following the publication of its analysis of the UK AI Adoption Plan 2026.

Rohini Gupta, CEO of FinregE, said: “The risk for many institutions is treating the regulator’s plan as a checklist rather than a systemic shift in their operating models. For AI to meet regulatory standards, the underlying foundation must be as dynamic as the technology it governs.”

She added that AI adoption in regulated industries required verified sources, documented decisions and continuous regulatory traceability to strengthen governance and oversight.

The RegTech provider has argued that while the regulator’s strategy has outlined a clear direction for AI adoption, many firms have faced challenges in translating those ambitions into operational compliance. It said organisations should move beyond deploying standalone AI tools and adopt a unified regulatory operating model that delivers end-to-end traceability.

The proposed framework has included five pillars: developing a comprehensive inventory of AI use cases, aligning AI deployments with regulatory obligations and customer outcomes, mapping obligations to internal policies, risks and controls, assessing the combined impact of regulatory and technology changes, and embedding governance, auditability and human oversight into workflows from the outset.

FinregE said its Regulatory Operating System (ROS) has integrated regulatory intelligence, obligations, risks, controls, policies, assessments and accountable owners into a single environment, enabling organisations to monitor regulatory developments, assess complex regulatory changes using AI and link internal controls directly to regulatory obligations through machine-readable digital rulebooks.

The company added that its AI Regulatory Insights Generator (RIG) had been designed specifically for regulated environments, allowing compliance teams to analyse regulatory content within governed workflows supported by verified regulatory sources.