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:  

Philip O’Shaughnessy, Head of Architecture, METRO BANK 

Amit Nandi, VP Solutions & Data Architect, BARCLAYS CORPORATE & INVESTMENT BANK 

Eshaan Salwan, Cyber Security Audit Analyst, LLOYDS BANKING GROUP 

Ronan Brennan, Artificial Intelligence Strategist, NATWEST GROUP 

Soung Low, Model Risk Data Scientist, NATWEST GROUP 

Finance teams win when models and tools work with real data context, not guesses.

In this session, you'll explore emerging design patterns at the intersection of finance and data teams. You'll hear Jakub Jurovych, CEO of Deepnote, discuss how institutions like a Norwegian wealth fund, card issuers like Ramp, and insurtechs like Jerry use agentic AI today. Learn how AI agents improve asset allocation, treasury and liquidity management, payments analytics, credit risk evaluation, fraud detection, and claims automation.

Discover practical steps to unify data from disparate sources. Learn how to keep your data fresh and prepared for agents. Explore best practices for building production-ready AI agents capable of multi-step SQL and Python workflows, training ML models, and producing auditable reports. Key use cases covered will include reconciliations, anomaly detection, and customer lifetime value modeling.

Unlock the future of finance, where continuous, auditable AI systems replace static analysis, driving more revenue and cutting costs.

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?

Moderator: Shaina Reid,  Director of Prime Services In-Business Risk, CIBC

Panellists:  

Ankur Agrawal, Director Technical Performance Management, AXA UK 

Linda Su, SVP Data & Analytics, CITI BANK 
Sebastian Obeta, Member of European AI Alliance, EUROPEAN COMISSION 

Arunita Roy, Technical and Data Strategy Lead on the Transforming Data Collections Programme, FCA 

Yohan Lobo, Senior Industry Solution Manager, M-FILES 

This session delves into the evolving landscape of model risk management, illustrated through real-world examples. We will explore how issues in model implementation, drift, and usage can translate into substantial financial and operational losses and highlight effective approaches for managing these risks at scale. Finally, we will look into practical insights into strengthening detection, validation, and governance practices to build resilient, audit-ready model ecosystems. 

Scaling AI beyond pilot projects remains one of the biggest challenges in financial services. This session explores what it really takes to embed AI into production and deliver measurable business impact. 

• Why do so many AI initiatives stall — and how can firms move beyond pilot purgatory? 

• How can organisations balance innovation speed with governance, controls, and risk appetite? 

• What lessons can be learned from firms that have successfully operationalised AI at scale? 

• How do leaders track adoption, outcomes, and ROI once models move into live environments? 

Moderator: Sal Gauri, Director EMEA Value, 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 

Aizaz Hussain, Operations Strategy, HSBC 

Ronan Brennan, Artificial Intelligence Strategist, NATWEST GROUP 

Sabina Kuzina, Data Science Platform Lead & AI Training Lead, DEUTSCHE BANK 

• Why risk assessment and security controls are essential 

• How we curate AI tools using an efficient workflow 

• How this approach has driven AI innovation within Lloyds Banking Group