Capco’s UK AI Lab

Our work through 2025 confirmed a simple truth: AI creates value only when it starts with the business problem. Across our projects, a few lessons stood out that will prove valuable over the next year:

• The thinking behind Smart Suite – our new collection of AI solutions – resonated with clients because it offered a clear, needs-driven way to show how AI solves real challenges in financial services.
• Agentic AI works when anchored to real workflows, not abstract automation.
• Structure matters more than volume in compliance, and graph-based reasoning unlocks context that LLMs miss.
• Hybrid AI is now the default, with agents, graphs, classical machine learning and LLMs each solving different parts of each challenge.

Our focus over the last year

2025 marked a decisive shift beyond proofs of concept. The Capco UK AI Lab designed, built and deployed AI solutions inside live client environments, delivering measurable outcomes while navigating a rapidly evolving model landscape. With nearly 95% of GenAI initiatives still failing to generate significant returns, the Lab deliberately reversed the pattern: starting with business pain points rather than technical capability.¹ That business-first mindset shaped everything we delivered.

A year defined by business-first AI

Across financial services, we saw a clear disconnect between how AI products are marketed and how clients describe their challenges. Clients spoke about regulatory pressure, legacy complexity, operational friction and cost – not about ‘using AI’. The Smart Suite concept emerged directly from this gap. Instead of leading with tools, we organized solutions around common financial services problems, showing clearly how AI could reduce risk, time and effort in familiar workflows.

What this looked like in practice

The most valuable opportunities for applying AI rarely appeared in formal requirements documents. They surfaced in everyday work: broken handoffs, slow reviews and hidden dependencies. Once those pain points were identified, the right type of AI to apply became obvious, and the Lab turned those insights into a set of practical tools built to address them: 

• Agentic data management. Data quality issues, for example, were often not about ‘bad data’ but about constant small inconsistencies. The Lab built an agentic approach that deployed specialized agents to handle lineage, quality checks, policy enforcement and knowledge capture. Working quietly in the background, the agents stabilized processes and freed teams to focus on analysis rather than fixes.
• Compliance. In compliance, the challenge is structural rather than textual. Regulations are interconnected, not linear. The Lab addressed this by building regulatory knowledge graphs, enabling LLMs to navigate compliance obligations as a network. This reduced blind spots, cut manual cross-checking and aligned outputs with how compliance professionals actually reason.
• Liquidity forecasting. Liquidity forecasting teams face volatility, not language problems. Our approach unraveled that problem by combining long short-term memory networks (LSTMs), transformers and neural networks into a single pipeline. It tracked short-term settlement fluctuations and long-term patterns, giving teams clearer scenarios and more time to act.
• Legacy modernization. In the case of legacy estates, the first problem is to create visibility and clarity before applying automated solutions. The Lab built knowledge graphs to map systems and dependencies, and then applied LLMs to generate accurate documentation and guide refactoring – creating a safer path to modernization.

Across every use case, the Lab translated complex AI into practical improvements: calmer processes, faster decisions, reduced risk and tangible operational gains. The focus was never experimentation for its own sake, but to deliver progress that teams could feel day to day.

Looking forward to 2026

Whether financial institutions are struggling with compliance complexity, data friction, forecasting uncertainty or legacy transformation, the Capco UK AI Lab can help. We partner with you to make sure you focus on your most important business challenges and apply the right mix of AI to solve them – at scale and in the environments that matter most.

References
¹ https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/