Assistant Vice President – Model Risk and AI Governance in London

The Risk Management department is responsible for developing, maintaining and promoting the Bank’s Enterprise Risk Management Framework (ERMF) and its activities, and for providing independent second line of defence (2LoD) oversight for Traded Market Risk, IRRBB & FX Risk, Operational Risk and Model Risk, Climate Risk and Strategic Risk management activities in the Bank. As an Assistant Vice President – Model Risk and AI Governance, you will be responsible for leading the Bank’s 2LoD coverage of Model Risk Management and for developing and implementing an AI governance framework. You will also support the End User Computing (EUC) requirements on behalf of the 2LoD for Information Technology Risk within the Non-Financial Risk & Enterprise Risk Management team. This is a full time permanent position.

Key responsibilities:

• Communicate and maintain the Model Risk Management Policy; track first line of defence (1LoD) implementation of the policy; provide independent assurance to the Chief Risk Officer over 1LoD compliance with the policy.
• Provide guidance, support and training to 1LoD for owning and managing model risk, which includes engaging with 1LoD Risk Owners and Control Owners for designing and implementing appropriate 1LoD controls; provide review and challenge of 1LoD controls design and operating effectiveness.
• Engage with Model Validators and administer the Bank’s independent model validation programme.
• Opine and report on the 2LoD view of the Bank’s risk profile for model risk to UK executive risk and UK board risk committees; review and challenge the 1LOD view of its risk profile; identify and assess the Bank’s top and emerging risks for model risk.
• Collaborate across the 1LoD and 2LoD to design, develop and maintain the Bank’s AI Governance framework to ensure that AI is deployed and used safely, ethically and transparently, and in compliance with existing risk management policies; drive enhancement of existing risk management policies to ensure and guide their application to AI use cases; establish supporting governance processes, standards and guard rails.
• Design, develop and maintain the Bank’s EUC procedures to support the implementation of the Bank’s Information Technology Risk Management Policy; provide guidance and support to 1LoD for understanding and applying the procedures.
• Act as a senior Subject Matter Expert, representing the Risk department in various committees, forums and projects relating to Non-Financial Risk and provide input in relation to the subject matter under the Non-Financial Risk coverage.
• Develop and enforce AI, EUC and model inventory management requirements, inventory completeness processes, and tiering processes.
• Develop management information and reporting for Model Risk, EUC and AI Governance activities and present to Senior Management and to risk oversight committees and forums.

Requirements:

• Degree educated in Finance, Economics, Business or relevant discipline.
• Solid 2LoD experience in model risk management within the Banking sector, including developing and maintaining model risk management policies, assessing model risk management controls, designing model risk management metrics, and providing independent review and challenge of 1LoD model management activities.
• Prior experience in AI governance would be beneficial, but not mandatory.
• Experience as Model Owner, Model Developer or Model Validator would be beneficial, but not mandatory.
• Experience in risk governance, risk management regulatory deliverables and project management.
• Good understanding of enterprise risk management principles and practice including risk governance, the three lines of defence approach, risk appetite and stress testing.
• Good understanding of PRA SS 1/23 and SS 3/18.
• Good understanding of and curiosity over the use of AI and the risks posed by using AI in a banking context.
• Reasonable understanding of core banking models, for example credit risk default and recovery model, market risk VaR, pricing models and forecasting models.
• Excellent communication and interpersonal skills with the ability to form effective relationships and to engage, collaborate and influence stakeholders.
• Adaptable and willing to learn and develop.
• Attention to details.
• Good analytical and problem solving skills.
• Excellent organisational skills.