AI in Finance Summit schedule

As AI capabilities advance, financial institutions are moving beyond predictive models into agentic systems—autonomous agents that can interact, decide, and act. From intelligent copilots supporting analysts to AI agents executing operational tasks in the background, this shift is reshaping efficiency, compliance, and customer engagement. 

• Early use cases of agentic AI in operations, customer service, etc. 

• Risk boundaries and governance frameworks for autonomous systems 

• The role of human oversight, explainability, and accountability in agentic design 

• How teams are integrating these tools with existing workflows 

Moderator: Megan Harrison, GTM EMEA, GLEAN 

Panellists:  

Indhira Mani, Chief Data Officer, RSA 

Philip O’Shaughnessy, Head of Architecture, METRO BANK 

Niresh Rajah, International Group Chief Data & AI Officer, DLA PIPER/ DANSKE BANK (former)

• How can we move from vanity metrics to true business value? 

• What ROI frameworks are helping teams justify spend across AI use cases? 

• A practical toolkit for focusing your AI efforts where they count most. 

As financial institutions race to innovate with AI, they face a delicate dance: how to stay bold without overstepping the line. With regulators like the FCA, PRA, and the EU sharpening their focus, 2025 will demand a new level of accountability, agility, and alignment.  

• What do regulators really expect from AI leaders — and where’s the line between risk and reward? 

• How can firms scale AI innovation without getting tangled in governance gridlock? 

• Strategies for embedding explainability, fairness, and resilience into AI systems from day one 
• Why robust content management frameworks are critical to AI success — and how poor data governance can undermine trust, compliance, and performance
• Can trust become your competitive edge in a market defined by scrutiny?

Panellists:  

Ankur Agrawal, Director Technical Performance Management, AXA UK 

Linda Su, SVP Data & Analytics, CITI BANK 

Yohan Lobo, Senior Industry Solution Manager, M-FILES  

• Which monitoring and validation tools deliver compliance confidence? 

• How do risk, compliance, and data science collaborate in practice? 

• Takeaways on building audit-ready AI systems that evolve over time. 

• What causes AI initiatives to stall — and how can teams move beyond pilot purgatory? 

• How do successful firms balance innovation speed with risk appetite? 

• Get first-hand insights on navigating the production journey with confidence. 

Moderator: Senior representative, ELASTIC 

Panellists: 

Previn Singh, Founder & Managing Director, KALEIDOSCOPE TRANSFORMATION 

Manuj Sarpal, CTO, GRANITE SHARES ETFS 

Arshad Ahmed, Head of Product, AI Platform, LLOYDS BANKING GROUP 

Pilar Roig, VP Real-Time Payments Data Product, MASTERCARD  

• How can adaptive AI models stay ahead of evolving fraud patterns? 

• What trade-offs exist between detection speed and explainability? 

• Actionable approaches to AI model governance in transaction monitoring.

• How can adaptive AI models stay ahead of evolving fraud patterns? 

• What trade-offs exist between detection speed and explainability? 

• Actionable approaches to AI model governance in transaction monitoring. 

Since synthetic data is no longer a workaround and it is becoming a strategic asset, financial firms are using it to overcome privacy barriers, reduce bias, and boost model resilience.  

• When synthetic data outperforms real data — and why it matters.  

• Use cases in fraud detection, compliance, and fairness testing. 

• How to deploy synthetic data at scale without compromising trust?