Event roundup: Tech and the City – AI in Financial Services – techUK and TheCityUK Half-Day Summit

On Tuesday 18th November 2025 techUK hosted leading industry figures across the AI, financial services and fintech sectors for Tech and the City – AI in Financial Services, a half-day summit run in partnership with TheCityUK.

This summit was convened for industry to share best practice on AI use in financial services, for the Financial Conduct Authority (FCA) to outline what practical support they are offering to innovators in this space, and for regulators/government to deepen their understanding of what innovation is happening in the market.

The summit was opened by James Challinor, Head of Financial Services at techUK, who emphasised the generational opportunity the UK has for AI to power growth across the financial services sector. This opportunity aligns closely with government’s Financial Services Growth & Competitiveness Strategy, which aims to make the UK the world’s most technologically advanced global financial centre by 2035.

Opening keynote – Edmund (Ed) Towers, Head of Advanced Analytics & Data Science Units, FCA

Ed began his keynote by outlining the FCA’s history as an innovation leader and its long history of enterprise support, notably with the world’s first regulatory sandbox in 2016. He outlined the FCA’s two current AI-focused services which innovators can utilise:

Supercharged Sandbox: for early-stage experimentation and proof-of-concept development
AI Live Testing: for firms ready to deploy and test their AI solutions with real users in a live market environment

Both sit within the FCA’s AI lab, where businesses can engage directly to develop their AI products. The FCA have experienced strong engagement in the first cohort, with 50+ firms engaging. Most of the first cohort’s use cases involve generative AI, with some combining classic machine learning and newer agentic systems. The FCA are currently taking applications for the next cohort of firms to engage with these services.

On regulation, Ed reiterated that the current UK regulatory regime of principles-based, outcome-focused regulation for AI in financial services will remain. This approach forms a core part of the FCA’s long-term strategy. In addition to this various UK frameworks all continue to apply to AI, including Consumer Duty, Senior Managers and Certification Regime, alongside operational resilience and cyber requirements. The message from Ed/FCA was clear, the UK can lead globally in AI-enabled financial services. The core challenge remains in ensuring firms have confidence that deployment is safe and reliable.

Second keynote – Alexon Bell, Co-Founder & Chief Product Officer, Quantexa

Alexon opened his address by outlining what a transformational moment this is for the financial technology sector, with the coming years promising huge change across the eco-system. He detailed that collaboration across regulators, financial services and technology is key to success.

Alexon outlined that AI is a broad area and most innovation fails. This is normal and to be expected. 80% of AI use in financial services is still traditional machine learning despite the recent focus on generative AI and agentic AI. He noted only 4% of generative AI proof-of-concepts (PoCs) reach production, so pursuing usable AI systems can be a significant resource drain if firms do not approach AI strategically. AI use cases often fail as firms do not think deeply about using the correct type of AI to solve the appropriate problem. Models must be designed from the outset with explainability and the end use case in mind. Success requires trust, and companies must have trust in their AI systems through deep understanding and extensive testing.

The other key focus of Alexon’s keynote was data. Successful AI use cases need the right type of data. Like oil, data needs to be highly refined before it’s useful. AI models also need diverse training outcomes to generalise successfully. A famous example given was relating to self-driving vehicles. The AI models for these were trained in Europe on European data, but when exported to the Australian market they kept crashing into kangaroos as the self-driving AI models were not familiar with or trained on data replicating the animal’s movements. Organising the data in human-like structures also makes the AI outputs more intuitive, and whilst synthetic data is helpful early on, real world data is messy and AI models must be able to navigate that. Firms need clear selection criteria for PoCs based on data constraints, model limitations and the wider business use cases. The message was clear, investing significant time in cleaning and structuring data pays dividends in the long run.

Alexon concluded that building a successful, collaborative ecosystem across financial services, technology and the regulators is key to accelerating success. For firms at the beginning of their AI journey, focus and strategy are key. From picking the right use cases, to careful and extensive testing, to learning lessons fast and failing forwards. If a technology firm can use AI to solve one problem, for one financial institution, they can then provide this solution to firms across the eco system and start to build market share.

Panel discussion – the challenges and opportunities for AI and financial services

Following the keynotes, industry leaders joined the stage for a discussion on the challenges and opportunities for AI in financial services. The panellists were:

Sushil Saluja, Technology & Innovation Lead, City of London Corporation (Panel Chair)
Jeremy Donaldson, Managing Director – Head of Financial Services, DXC Technology (techUK Financial Services Council Chair)
Suchitra Nair, Head of EMEA Regulatory Strategy, Deloitte (TheCityUK Technology and Innovation Group Chair)
Chris Knox, Global Financial Services Regulatory Director, Microsoft
Sarah Self, AI Director, Aviva

The first question focused on key trends seen in the market currently. It came through that AI deployment is being deployed across organisations, with business leaders believing every business process could be improved. Although there is a high degree of nervousness if something goes wrong with an AI system, as it could negatively impact a business from a reputational, operational and financial viewpoint.

There was also agreement the UK is on the right track regarding AI adoption in financial services, but several AI ‘growing pains’ persist. First and foremost is data, as in line with the former keynote. Messy and unkept data is slowing AI roll out and stopping firms from scaling AI solutions. There are also bright spots for adoption, with strong adoption taking place in payments and significant opportunities emerging around code modernisation to transform legacy mainframe software.

Adoption rates vary globally. The US is leading the pack, owing to its deep pools of capital, competitive pressure and high pilot tolerance. China is also doing well, releasing AI models at a rapid pace. In European jurisdictions, the innovation is more measured with the focus being on regulation and guardrails. Singapore mirrors this measured approach.

The second panel question focused on regulation. The panellists thought the UK regulatory approach was the correct one, but with some caveats. Firstly, clearer guidance may be needed on agentic AI and how it fits into model risk management. Secondly, there are still some broader spots of regulatory friction. One example being that financial services companies are responsible for validating entire AI systems but are unable to independently validate LLMs as they don’t have access to the underlying components, training data, or full model architecture. This pushes companies towards traditional machine learning rather than newer types of AI. There was overarching agreement that the UK should stay on its current regulatory trajectory, and that the key challenges to AI adoption lie in data, operating models and governance.

The final question focused on how firms operationalise AI. Many AI programmes have failed as they were spread across different teams, frameworks and data sets. Organisations increasingly recognise the need for frameworks, governance and clear objectives. A company must articulate the business problem they are trying to solve before pursuing a use case. The focus should be on selecting a small number of high-value use cases only. Challenges persist around data quality and breaking down organisational silos, but these are surmountable with focus and a well-thought through strategy.

In conclusion

The event was concluded by techUK’s Head of FS James Challinor. James reiterated the opportunity at hand for the technology sector to support the financial services sector in its growth mission through the provision of cutting-edge technologies. This summit focused on AI, an area techUK continues to explore in detail through both the Financial Services Programme and techUK’s dedicated AI Programme. But there are several innovative technologies which have the potential to transform financial services including distributed ledger technology and quantum computing. These are all themes techUK’s Financial Services Programme will look at across 2026. If you have views on this or would like to learn more about techUK’s areas of work, please contact to [email protected].

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