Day One | December 1
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
8:00
Breakfast and Networking
8:50
Chair’s Opening Remarks
9:00
THE AI ADOPTION GAP: WHY GOVERNANCE IS THE ANSWER, NOT THE OBSTACLE – PANEL DISCUSSION
Why are organisations investing billions in AI yet struggling to scale adoption? Understanding how governance, risk and organisational readiness are becoming the foundations of successful AI transformation
Key topics
- Understanding why AI investment is failing to convert into measurable business value
- Examining the gap between AI ambition, organisational readiness and governance maturity
- Exploring whether governance is enabling innovation or becoming a barrier to adoption
- Understanding the risks organisations introduce when scaling AI without effective governance frameworks
- Identifying the capabilities required to deploy AI safely, responsibly and at enterprise scale
- Learning how leading financial institutions are aligning AI strategy, governance and risk to accelerate adoption
 | Guillaume Figer,Chief Risk Officer,Societe Generale |
 | Ratul Ahmed,Managing Director Principal Project Manager,Commerzbank AG |
 | Dr Isabela Parisio,Postdoctoral Research Associate,Tech and Policy,King’s College London |
9:50
AI GOVERNANCE OPERATING MODELS IN PRACTICE
Session: Examining how financial institutions are building governance frameworks capable of supporting AI at scale
Key topics
- Translating governance policies into operational processes and controls
- Designing approval, escalation and oversight mechanisms for AI use cases
- Embedding AI governance into model risk, operational risk and enterprise risk frameworks
- Managing governance across multiple business units, jurisdictions and AI platforms
- Understanding where governance frameworks begin to fail as AI adoption scales
- Building governance operating models that support both innovation and control
 | Yingbo Bai,Managing Director, Head of AI Governance and Regulatory Engagement,UBS |
10:25
Morning Refreshment Break and Networking
10:55
AI GOVERNANCE AS A BOARD-LEVEL RESPONSIBILITY – PANEL DISCUSSION
Session: Understanding how AI governance is moving beyond technology oversight and becoming a core board, risk and accountability priority.
Key topics
- Understanding why AI governance is emerging as a strategic leadership and enterprise risk issue rather than solely a technology concern
- Examining what regulators expect from boards and senior management under evolving accountability and governance frameworks
- Defining the board’s role in overseeing AI strategy, risk appetite, governance effectiveness and organisational readiness
- Assessing how AI governance intersects with operational resilience, cyber security, conduct risk and reputational risk
- Establishing meaningful reporting, oversight mechanisms and challenge frameworks to support effective board-level decision-making
 | Sucharita Banerjee,Global Head of Operational Risk, ERM Reporting and Operations,AIG |
 | Cosette Reczek,Managing Director, Global Head of Markets Model Risk,Standard Chartered |
11:45
AI CONCENTRATION RISK AND THE NEW DEPENDENCY LANDSCAPE
Session: Understanding how foundation models, hyperscalers and external providers are reshaping risk.
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
12:20
Lunch Break
1:05
Lunch Break and Networking Roundtables
Roundtable
Challenges Around Responsible AI
 | Suzanne Brink,Head of Responsible AI,Lloyds Banking Group |
1:50
FROM PROMPTING TO AGENTIC VALIDATION
How AI can transform model risk validation beyond prompting: building agentic, scalable and governed workflows
Key topics
- Identifying the validation activities where generative AI creates the highest impact. Initial exploration with IFRS9 provisioning models.
- Building structured, reusable prompt frameworks to standardize validation activities
- Enhancing AI quality through controlled workflows and continuous improvement
- Scaling the approach across IRB, Credit Decisioning and ESG risk models
- Migrating to GCP and Gemini to deploy agents and workflows
- Orchestrating AI capabilities across validation and monitoring processes
- Embedding AI as a decision support tool, with validators retaining full accountability for assessments and regulatory sign-off
- Extending the approach beyond credit risk model validation
- What the rise of agentic AI means for the future role of model risk and validation teams
 | Alvaro J. Fernandez,Lead Validator – Wholesale Banking & Bankwide Chapter, Credit Risk Model Validation – Model Risk Management,ING |
2:25
AI READINESS STARTS WITH DATA
Session: Why data architecture, governance and quality are becoming the biggest barriers to AI adoption.
Key topics
- Understanding why AI maturity is increasingly determined by data maturity
- Assessing the impact of fragmented legacy infrastructure on AI deployment
- Revisiting BCBS239 and enterprise data governance through the lens of AI
- Establishing accountability for data quality, ownership and lineage
- Building AI-ready data environments
- Understanding why many firms require data transformation before AI transformation
 | Gagan Singh,Group Head of Data Governance,Legal and General |
3:00
RESPONSIBLE AI STARTS WITH TRUST: EMBEDDING PRIVACY, ACCOUNTABILITY AND TRUST BY DESIGN
Session: Building governance frameworks that embed Responsible AI principles into the design, development and deployment of AI systems.
Key topics
- Understanding how Responsible AI can be embedded into enterprise governance frameworks
- Implementing privacy-by-design and accountability-by-design across the AI lifecycle
- Balancing innovation with customer trust, regulatory expectations and business objectives
- Establishing clear ownership and accountability across legal, risk, privacy and technology functions
- Operationalising Responsible AI through governance, controls and oversight mechanisms
- Building trust in AI systems through transparency, accountability and responsible deployment
 | Angela Isom,Global Chief Privacy and Responsible AI Officer,Gallagher tbc |
3:35
Afternoon Coffee Break and Networking
4:10
AGENTIC AI AND AUTONOMOUS DECISION-MAKING
Session: Preparing governance frameworks for systems capable of acting independently.
Key topics
- Understanding the rise of agentic AI across financial services
- Examining how autonomous systems differ from traditional AI deployments
- Managing AI systems capable of taking actions rather than simply generating outputs
- Understanding emerging customer-facing and internal use cases
- Establishing controls for increasingly autonomous workflows
- Defining accountability when decisions become machine-led
 | Phani Ravindra Kaligotla,Vice President, Global AI and Data Strategy,Mastercard |
4:45
AI GOVERNANCE AND FINANCIAL STABILITY
Session: Assessing how AI failures could evolve from firm-level incidents into systemic financial risks.
Key topics
- Understanding the systemic implications of AI adoption across financial services
- Exploring how AI could amplify market, operational and conduct failures
- Examining the risks of correlated decision-making and model convergence
- Assessing whether AI should be considered critical financial infrastructure
- Understanding the lessons from previous systemic failures
- Identifying emerging risks regulators are increasingly focused on
5:20
Chair’s Closing Remarks
5:30
End of Day One of AI Governance in Financial Services