We are currently building out the Financial Services and AI Working Group, chaired by Niresh Rajah. If you would like to get involved, please reach out to discuss participation and fit.
Why This Group Exists
AI is reshaping credit and pricing, claims, trading workflows, fraud and financial crime controls, and customer journeys. When applied well, it can improve performance, resilience, and decision making across financial services.
The challenge is moving from experimentation to reliable, repeatable deployment. Firms are navigating complex governance requirements, senior management accountability, third party dependencies, and evolving expectations across risk, compliance, and data management. Boards want confidence that AI is being applied responsibly and consistently, without slowing innovation. This group exists to help members work through these challenges together, sharing practical experience, testing approaches in live environments, and developing applied best practice that supports confident, scalable adoption.
Who’s Involved
The group is convened for senior leaders with direct accountability for how AI is designed, governed, and deployed within financial services organisations. Members span established institutions and high growth firms who are already applying AI in live environments and are focused on moving from experimentation to dependable delivery.
Participation is intentionally selective to ensure informed discussion, shared credibility, and practical collaboration between peers. The group operates as a trusted space for leaders who want to compare approaches, pressure test decisions, and shape applied best practice together as AI becomes embedded across core financial services functions.
Niresh Rajah
Niresh is a senior financial services executive with over 20 years of experience leading large scale data, AI and transformation programmes in highly regulated environments. He has held Group level leadership roles across banking and professional services, including at Barclays, Lloyds Banking Group, Danske Bank, DLA Piper and Grant Thornton, with direct responsibility for enterprise AI, data and analytics strategy and delivery. His work has focused on embedding AI into core financial services operations in a way that supports performance, resilience and accountability, while remaining commercially grounded.
Alongside executive roles, Niresh holds board advisory and non executive positions and contributes to academic and industry communities through his work with Oxford University and Imperial College Business School. As Chair of the Financial Services and AI Working Group, he brings a pragmatic, delivery led perspective shaped by real world implementation at scale.
Participation is by invitation and designed to ensure a mix of in-house, private practice, and sectoral experience. This is a practitioner-led group, built for relevance, trust, and action.
What the Group Delivers
This is a forum for leaders who are already carrying real accountability for AI and want a sharper edge as adoption accelerates.
Members use the group to think clearly under pressure. It provides a trusted space to challenge assumptions, test decisions, and refine how AI is being embedded into core financial services operations, with input from peers who understand both the opportunity and the risk.
Members use the group to:
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Compare how leading organisations are structuring AI ownership, decision rights and accountability at enterprise level
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Sense check scaling strategies across high impact workflows where failure has material consequences
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Work through data, model and third party dependencies that shape resilience, cost and execution speed
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Align AI ambition with delivery reality across technology, risk, compliance and product
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Build confidence that decisions will hold at executive and board level as AI becomes business critical
The value is practical and cumulative. Members leave with clearer judgement, fewer blind spots, and greater confidence in how they move from AI ambition to dependable delivery.
How the Group Works
The group operates as a high trust, peer led forum and a central stream of activity within UKAI. Members work alongside it, help shape its direction, and draw on it for practical insight and outputs that support real world AI delivery.
Engagement is built around the issues members are actively dealing with, from scaling and governance to operational decision making. Sessions are deliberately closed and discussion led, allowing for candid exchange, challenge and shared learning between peers with comparable accountability.
Meeting quarterly, the group provides a consistent rhythm of engagement without unnecessary overhead. Between sessions, UKAI drives momentum by curating follow up, connecting members where there is clear value, and turning discussion into practical outputs that members can use internally as AI becomes embedded into business critical operations.
Roundtables
Closed door discussions for senior leaders dealing with live AI deployment. Sessions focus on real decisions around scale, accountability, governance and resilience, grounded in operational reality.
Fireside Conversations
Intimate settings with senior leaders applying AI in live environments, focused on decision making, trade offs and real delivery constraints.
Collaborative Outputs
Practical outputs built from member experience, translating discussion into governance, operating models and delivery tools that can be used internally.
Policy and Regulator Engagement
Insight from the group feeds into UKAI’s wider engagement with government and regulators, keeping members connected to how priorities and expectations are evolving.
Strategic Collaboration with Other UKAI Groups
This work does not sit in isolation. Members connect into other UKAI groups where useful, sharing insight and aligning approaches as challenges and priorities overlap.
What’s Coming Up
The group is shaping a programme focused on the most consequential decisions facing senior leaders as AI becomes embedded into core financial services operations.
Areas currently being explored include:
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How organisations are determining which AI use cases are appropriate for deployment in core workflows
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How accountability and decision making are structured as AI systems span multiple teams, models and third party providers
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How firms are designing internal challenge, approval and escalation processes for AI that affects customer outcomes or financial risk
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How executive teams and boards are gaining confidence in AI driven decisions through clearer assurance and reporting
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How performance, explainability and monitoring are being managed once systems are live and business critical
All outputs are member-led and will feed into UKAI’s wider content and national engagement work.
How to Get Involved
Participation is designed for senior leaders with direct responsibility for how AI is designed, governed and deployed within financial services organisations.
The group is being built deliberately, with membership kept focused to support high quality discussion and meaningful collaboration between peers. It is designed for senior leaders who are responsible for how AI is delivered, governed and scaled within financial services organisations.
Members contribute to core quarterly meetings, themed sessions, and outputs throughout the year. Additional working sessions or deep-dives take place as needed based on member priorities.
If these challenges resonate and you want to be part of a peer group working through them in practice, please get in touch with Stephen Moore.