AI Consultancy for UK Financial Services Firms
Financial services has the clearest AI opportunity of any sector and the least room to get the governance wrong, which is why so many programmes stall between a promising pilot and anything a risk committee will approve. We work with mid-sized UK firms on the version of AI strategy that survives contact with a regulator, and our founder spent 30 years leading technology in regulated sectors, including CTO and CIO roles in finance and insurance, before starting this consultancy.
Built for mid-sized firms rather than scaled down from a bank programme
The large consultancies build their financial services methodology around tier-one banks and then offer a smaller version of it to everyone else, which is why a firm of 300 people ends up paying for a governance framework designed for an organisation of 30,000. The framework is not wrong, it is simply built for a scale of risk function you do not have and a budget you would not sign off.
We work the other way round, starting from the risk appetite, the data and the people you actually have. That usually means fewer controls carrying more weight, a shorter path from use case to approval, and a plan your existing second line can operate without hiring a team to run it.
We are paid by the client, and only by the client. We take no commission, referral fee or resale margin from any vendor, we have no implementation arm that needs feeding, and we are not tied to a single platform. That matters more in this sector than most, because when the answer is that your current stack is adequate and the problem is process, we can say so.
The questions a financial services board actually asks
The same four questions come up in this sector, usually in the same order. Can we evidence how this decision was reached, and to whom. What happens when the model drifts and who notices. Where does accountability sit under the Senior Managers Regime when a system rather than a person made the call. And what does this cost over three years once you include the people, the assurance and the second line, not just the licences.
Those are governance questions rather than technology questions, and they are the reason pilots stall. The technology in most mid-market financial services use cases is settled and unremarkable, covering document handling, customer correspondence, case triage, fraud signals and internal knowledge retrieval. What is unsettled is who signs it off and on what evidence.
We design that evidence in from the start, because retrofitting it to a working pilot is where the cost and the delay come from. That includes Consumer Duty outcomes where AI touches a customer journey, and the model risk documentation your auditors will ask for before your regulator does.
How we work with financial services firms
Breathe is our 5 to 10 day discovery sprint. We assess AI readiness, map your technology and data capability against your governance appetite, score the opportunities and give you a costed roadmap with a three-year view of the total spend. For a regulated firm it also establishes which use cases are genuinely low risk, which is usually the difference between a programme that starts and one that keeps getting deferred.
Flow is implementation. Over 4 to 8 weeks we take one real problem and build a working capability with the controls, the audit trail and the measurement designed in, so what you end up with can go to a risk committee rather than only to a demo.
Grow is a fractional Chief AI Officer. We hold strategy, governance, vendor oversight and board reporting together for firms that need senior AI accountability without carrying a full-time executive, which is the position most mid-sized financial services firms are in.
We work with insurers through our insurance page and with law firms through our legal page, and we work across the UK from a base in Leeds.
Related reading
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AI in Financial Services: A Practical Guide for Mid-Market Firms
AI can automate KYC, detect fraud and speed up reporting. But regulators demand explainability. Here's how to move forward without getting stuck.
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AI Governance in Financial Services: What Good Looks Like
Governance is not the opposite of innovation. The firms moving fastest with AI in financial services are the ones that invested early in getting their governance right.
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How AI Can Help You Evidence Consumer Duty Outcomes Without Creating New Risk
Consumer Duty has moved from implementation to impact. AI can help you evidence good customer outcomes at scale, but only if the governance is right from the start.
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Tell us where your AI programme is stuck, whether that is a pilot nobody will approve or a board asking for a plan you have not had time to write, and we'll reply within one working day.
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