AI in banking is maturing fast, and with it comes something unavoidable: regulation. But unlike capital rules or stress tests, this time there’s no unified path.
The U.K. and EU are plotting separate maps for AI. Banks must follow both.
For institutions operating in multiple jurisdictions, the regulatory thread now forks. The challenge is to keep operations intact—traceable, auditable, and operational—across two very different regimes.
The UK: Principles first, innovation forward
In Westminster, the regulatory tone is clear: support innovation and avoid overreach. The U.K.’s AI regulation framework is light on mandates and heavy on five key principles:
- Safety
- Transparency
- Fairness
- Accountability
- Contestability
The approach empowers regulators, such as the Financial Conduct Authority (FCA) and Prudential Regulation Authority (PRA), to interpret and enforce these in context—and gives firms room to experiment and deploy at pace, provided they can prove responsible governance.
While this approach encourages innovation, it also demands internal maturity. You won’t be handed a checklist. You’ll be expected to follow your own thread of logic, governance, and control—and be ready to show it.
The EU: The world’s first comprehensive AI law
Meanwhile, Brussels is taking no chances. The AI Act is sweeping, prescriptive, and already triggering widespread concern among financial institutions.
It introduces:
- Risk-based classification of AI use cases
- Strict rules on data quality and provenance
- Documentation and traceability mandates
- Fines of up to €35 million or 7% of global turnover, whichever is larger
The response has been one of unease across the board. One major insurance lobbyist recently admitted, “We have no clue how to implement the AI Act.”1
For banks, particularly those with legacy infrastructure and siloed data systems, the AI Act makes data lineage and explainability non-negotiable.
Dual compliance—not dual standards
For banks straddling both jurisdictions, this isn’t a debate. It’s a design brief.
You can’t afford to build AI capabilities optimised only for innovation or oversight. You’ll need:
- Dual governance
- Universal data traceability
- Auditable model performance and decision logic
- Embedded controls aligned to both principles and prescriptions
In short, you’ll need to follow the thread—from raw data to AI-driven decisions—no matter which regulator is asking questions.
The thread must cross borders
The differences between U.K. and EU AI regulation aren’t going away—if anything, they’ll deepen. But banks that treat this as an either/or problem will find themselves outpaced or out of bounds.
To scale AI responsibly across both regions, you need to:
- Build for adaptability
- Prove control without sacrificing innovation
- Weave governance and experimentation into a single, auditable thread
Teradata works with many of the world’s leading banks on precisely these sorts of problems.
Get your regulation-ready AI blueprint, built for both innovation and accountability.