SVP, AI Risk: Data and AI Risk, Risk Management Group

Business Function

Risk Management Group (RMG) is responsible for the development and maintenance of risk management and internal control frameworks. It provides independent review and challenge to ensure appropriate balance in risk/return decisions, and monitors key risk issues across the Bank.

The role sits within the Data & AI Risk (DAR) team and is focused on the development and ongoing refinement of the Group’s AI risk framework, ensuring it is practical, aligned to regulatory expectations, and applied consistently across the organisation.

Responsibilities:

• Lead the development and continuous evolution of the Group’s AI risk framework (policy, taxonomy, and control expectations)
• Ensure the AI risk framework reflects real use cases, emerging risks, and regulatory direction
• Define clear risk guardrails for AI use cases aligned to Group risk appetite
• Maintain a clear view of AI use cases, platforms, and developments across the business
• Engage with business and technology teams to ensure risk considerations are incorporated early
• Translate policy into practical, implementable requirements across teams
• Work with standard and control owners to align implementation with risk expectations
• Ensure consistent interpretation and application of AI risk requirements across the Group
• Provide clear, pragmatic risk views on complex or ambiguous AI risk matters
• Support issue and incident articulation and guide resolution of control gaps
• Bring external perspectives by keeping across industry developments and regulatory trends in AI risk
• Translate external developments into actionable updates to internal frameworks and guidance
• Contribute to building a cohesive and credible AI risk capability within the team
• Support consistency and clarity in how AI risks are articulated and managed across the Group

Requirements:

• Experience (8+ years) in risk management, with grounding in at least one established risk discipline (e.g. model risk, cyber risk, data risk), and experience applying that discipline to AI or advanced analytics use cases, including translating policy into practical implementation
• Experience developing and implementing risk frameworks or policies, with a focus on real-world application
• Good understanding of AI-related risks or adjacent domains; experience in AI risk, regulated environments, or advisory roles is advantageous
• Strong judgement and ability to operate effectively in ambiguous, evolving areas
• Strong knowledge of relevant regulations and industry practices in Data and AI risk, including model risk management frameworks
• Strong analytical and problem-solving skills, with the ability to assess risks and identify practical solutions
• Excellent communication skills, with the ability to engage effectively with both technical and non-technical stakeholders
• Bachelor’s degree in a relevant field (e.g. Accounting, Banking, Computer Science, Engineering, Mathematics, Statistics); relevant certifications (e.g. CRISC, CISM) are advantageous

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