Day Two | December 2
Here is the latest edition of the agenda. As we approach the event, we will be adding speakers and sessions to enhance your experience. To stay informed, please register your interest
 | Lisa Kalscheur,Chief Marketing Officer,Weave.AI |
Key topics
- How AI is reshaping accountability across the three lines of defence
- The evolution of compliance, risk and audit in AI-enabled organisations
- Moving from periodic reviews to continuous monitoring and assurance
- Maintaining effective independent challenge in increasingly automated environments
- Balancing human judgement, accountability and AI-enabled oversight
- Preparing governance functions for agentic and autonomous AI systems
 | Lucy da Piedade,Managing Director, Head of Group Controls Office,Deutsche Bank |
 | Marili Anderson,Head of UK Compliance,Rabobank London Branch |
 | Dimitrios Asvestis,Head of Traded Risk Model Validation and Model Risk Measurement,Barclays |
 | Claus murmann,Senior Staff Solutions Engineer, Financial Services,Domino.ai |
Key topics
- PRA’s technology‑agnostic approach to AI regulation in UK financial services
- How AI risks extend beyond model risk, including cyber and third‑party dependencies
- Using existing expectations to support responsible AI adoption
- Applying SS1/23 model risk management principles to AI use cases
- Strengthening governance, oversight, accountability, policies and risk appetite
- Managing the AI lifecycle through use‑case definition, risk tiering, validation, monitoring and controls
 | Jonathan Taylor,Head of Quantative Analysis, and Model Risk Management,Bank of England |
 | Diederick Potgieter,Risk Specialist,Bank of England |
Key topics
- Auto-register agents, tools, and prompts from build/deploy metadata hooks, with gatekeeping that blocks unregistered agents
- Linked inventories for Agents, Capabilities, Skills, and Tools as a live dependency graph
- Static risk-tiering plus central audit of the runtime control plane’s configs and thresholds
- Modular components governed once and propagated to all dependent agents; inherited platform governance for fast-track reviews
- Telemetry mapping, retrospective trajectory audits, and a Stability Score to flag drift
- Programmatic kill-switch for gateway-level credential revocation on critical findings.
 | Efrem Bonfiglioli,AI Risk Management Expert,Yields |
Key topics
- Understanding adversarial AI, prompt injection and model manipulation
- Assessing how AI is changing the cyber threat landscape
- Using AI to strengthen defensive capabilities
- Managing vulnerabilities within AI systems and models
- Understanding the implications of AI-enabled fraud and financial crime
- Aligning cyber security and AI governance strategies
 | Suresh Sankaran,Prudential Regulation Lead,NatWest |
 | Pallavi Kapale,Senior Financial Crime Officer,Bank of China |
Key topics
- Assessing how AI can strengthen resilience while creating new operational, cyber and concentration risks
- Mapping AI models, cloud providers, software suppliers and other dependencies to important business services
- Governing AI use across critical third parties, including accountability, assurance and human oversight
- Scenario-testing AI failures, supplier disruption, compromised models and AI-enabled cyber threats
- Ensuring incident response, remediation and recovery processes can operate at AI-enabled speed and scale
- Preparing resilience and third-party governance frameworks for DORA, FCA PS26/2 and evolving supervisory expectations
 | Andrew Pym,, Head of Operational Resilience,Monzo |
 | Magdalena Watson,Head of Operational Risk and Resilience,Renaissance Re |
 | Rosalyn Aryee,Global Head of CIB Business Resilience & Business Continuity,Santander CIB |
Key topics
- Assessing concentration risk across AI providers and infrastructure platforms
- Understanding the systemic implications of shared dependencies
- Examining resilience risks associated with foundation models
- Managing exposure to external AI ecosystems
- Exploring future regulatory expectations around concentration risk
- Developing strategies to reduce dependency risk
Key topics
- Identifying operational, financial, strategic and reputational AI risks
- Mapping AI risks into existing enterprise risk taxonomies
- Understanding the implications of stacked and interconnected AI risks
- Integrating AI into enterprise risk reporting and risk appetite frameworks
- Establishing ownership across multiple risk domains
- Avoiding fragmented approaches to AI risk management
Key topics
- How AI may reshape employment, productivity and financial services operating models
- The future relationship between humans and autonomous systems
- How AI could transform customer behaviour and financial decision-making
- The long-term implications of AI for markets, competition and financial stability
- Preparing governance frameworks for a radically different economic environment
 | Suzanne Brink,Group Head of Responsible AI and Bank of England AI Consortium, Lloyds Banking Group |
 | Tanveer Bhatti,Independent Member,Bank of England AI Consortium |
 | Guillaume Figer,Chief Risk Officer,Societe Generale |
 | Joe Breeden,Chair,Model Risk Managers International Association (MRMIA) |