AI Governance for Financial Services Firms Report
AI Governance and Oversight Guidance for Financial Services Firms
A practical, board-ready report for UK financial services firms preparing for accountable, resilient and consumer-focused AI adoption.
Artificial intelligence is moving from experimentation to operational reality across banking, wealth management, insurance, payments and market infrastructure. This report ‘AI Governance for Financial Services Firms’ gives senior leaders, risk teams, compliance officers and technology owners a practical framework for governing AI systems in line with the FCA’s outcomes-focused approach, Consumer Duty, SMCR accountability, operational resilience expectations and emerging UK and EU AI regulation.
Download this report if you need to:
- Map AI accountability to named Senior Management Function holders.
- Classify AI use cases by risk level and apply proportionate controls.
- Prepare for FCA expectations on audit trails, governance evidence and consumer outcomes.
- Assess third-party AI providers, model risk, operational resilience and kill-switch arrangements.
- Build a governance framework that enables safe innovation rather than slowing it down.
Why this AI governance for Financial Services report matters now
UK financial services firms are adopting AI at pace, while regulators continue to apply existing governance, conduct, operational resilience and accountability frameworks to new technology. The challenge for firms is not simply whether AI can improve efficiency. It is whether each AI system can be explained, monitored, challenged, switched off and owned by the right senior manager when it affects customers, markets or important business services.
This guidance translates that challenge into eight practical principles for AI governance and oversight. It is designed for Boards, CEOs, COOs, CROs, Compliance Oversight, MLROs, internal audit teams, legal teams, risk committees and technology leaders who need a clear operating model for AI in regulated financial services.
What you will learn
· How to create a firm-wide AI inventory covering approved tools, third-party platforms and shadow AI.
· How to assess high, medium and low risk AI use cases in financial services.
· How Board accountability and AI strategy should align with risk appetite and governance reporting.
· How SMCR responsibilities can be mapped to AI outcomes, model risk, compliance and operational integrity.
· What due diligence, validation and audit trail evidence firms should maintain before and after deployment.
· How Consumer Duty, market integrity, vulnerability, financial crime and regulated advice boundaries apply to AI systems.
Who should read this report?
This report is written for UK financial services firms deploying or considering AI, including banks, asset managers, wealth managers, insurers, fintechs, payments firms, market participants and FCA solo-regulated firms. It is particularly relevant for firms using AI in customer communications, credit decisioning, financial crime monitoring, transaction reporting, compliance monitoring, investment suitability, advice support, operational processes or third-party technology platforms.
About the Authors
Katharine set-up Leaman Crellin to offer expert, tailored solutions to help clients navigate complex regulatory landscapes and achieve compliance with ease. Providing practical and expert service from in-depth consultancy to training and ready to purchase products, Leaman Crellin clients range from SME’s to FTSE 100’s. Katharine supports c-suite clients and front office trading teams around the world, as well as offering strategic support to clients and the Leaman Crellin team through her CEO role. One of her passions is supporting smaller financial services firms who need to be across a broad range of regulations to a technical depth but often lack the time and resourcing to implement.
Ian has over 30 years Securities Industry experience, often applied through delivering Impact Assessments (regulatory / business strategy / business operating models). These leverage lots of aspects of his experience including a detailed understanding of client value propositions, front to back processes in both buy and sell side firms, risk management frameworks and processes, common data challenges, reconciliations, common issues causing fails, meaningful and effective controls and MI, and ways to minimise system implementation cost, complexity and risk.
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