The PRA holds model risk management roundtable on artificial intelligence and machine learning technologies
Executive Summary
The Prudential Regulation Authority (PRA) held roundtable sessions on 20 and 22 October 2025 with 21 regulated firms to discuss AI and machine learning (AI/ML) adoption under Supervisory Statement SS1/23 on model risk management (MRM) principles for banks. This matters because it highlights PRA's strategic supervisory focus on AI/ML model risks, urging firms to enhance governance, risk appetite, monitoring, and validation to mitigate opacity, overfitting, and rapid performance degradation in these models. https://www.bankofengland.co.uk/prudential-regulation/publication/2025/november/pra-holds-model-risk-management-roundtable-on-ai | https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/2025/november/ai-roundtable-oct-2025.pdf #
What Changed
This is not a formal rule change but supervisory guidance via roundtable insights reinforcing SS1/23 principles (effective since 2023). Key emphases include: - Risk appetite: Boards must articulate AI/ML-specific model risk appetite pre-deployment to avoid exceeding tolerances, given higher uncertainty from opacity. - Model inventories and tiering: Address inaccurate/incomplete inventories and aggregate risks from deploying similar AI/ML across portfolios/jurisdictions; challenge tiering for complexity. - Model development: Assess trade-offs in performance vs. explainability/reliability; prefer simpler models where AI/ML gains are marginal; mitigate overfitting via representative datasets. - Ongoing monitoring: Increase frequency beyond tier-dependent intervals (e.g., six months may suffic
What You Need To Do
- Review and strengthen board-level model risk appetite statements to explicitly cover AI/ML opacity and uncertainty; integrate into governance triggers like re-validation
- Enhance model inventories for completeness, aggregate risk assessment, and cross-jurisdictional tiering challenges
- Update model development policies to evaluate AI/ML trade-offs (e
- Revise ongoing monitoring policies for more frequent, quantitative checks on AI/ML (e
- Participate in PRA initiatives like MRM roundtables or AI Consortium for dialogue; align first/second-line defenses per SS1/23
Key Dates
Compliance Impact
Urgency: Medium - Not critical as no new rules or deadlines, but high relevance for AI/ML users amid PRA's strategic MRM focus; non-compliance risks supervisory actions, given observations of gaps in monitoring and governance. Matters for banks scaling AI (rising adoption per industry views), as unaddressed risks like rapid degradation could amplify losses (e.g., historical model failures cost bil
Who is Affected
Summary
The PRA held roundtable meetings on artificial intelligence and machine learning (AI and ML) in the context of Supervisory Statement (SS)1/23 ‘Model risk management principles for banks’