AI Security Governance Framework for Financial Services

Financial services organisations face unique challenges in deploying artificial intelligence systems, operating under some of the most stringent regulatory frameworks globally while simultaneously pursuing AI-driven competitive advantage. This paper presents a comprehensive AI security governance framework specifically designed for the banking and financial services sector, integrating requirements from the Financial Conduct Authority, Prudential Regulation Authority, European Central Bank, and emerging international standards.

The framework builds on established model risk management practices (SS1/23, SR 11-7) and extends them to address the novel risks introduced by generative AI, large language models, and automated decision systems. It provides a structured approach to AI risk assessment that considers not only traditional model risks such as accuracy and bias, but also security-specific concerns including data poisoning, adversarial attacks, prompt manipulation, and intellectual property leakage through model interactions.

Practical implementation guidance covers the establishment of AI governance committees, the definition of risk appetite for AI-driven decisions, integration with existing three-lines-of-defence models, and the creation of AI-specific incident response procedures. The framework also addresses the growing regulatory expectation for explainability in AI-driven financial decisions, providing technical approaches that balance model performance with interpretability requirements.

Drawing on two decades of experience securing financial services environments and managing assets exceeding five hundred billion pounds without a single breach, the paper provides battle-tested recommendations for organisations at various stages of AI maturity — from those conducting initial pilots to institutions with extensive production AI deployments.