Hiring in financial services is tilting towards higher-skilled, better-qualified people, and that tells us something about how the work is changing. In the sector, recruitment was generally for roles at Regulatory Qualification Framework (RQF) level 6 and above, rather than the RQF 3 to 5 band GOV.UK - Temporary Shortage List: Stage 2 report. In plain terms, RQF 6 sits at degree level, so firms are reaching for people who can reason through complex, judgement-heavy work.
That demand is landing at the same time as a national push on AI capability. During London Tech Week 2025, the UK government announced a partnership to upskill 7.5 million UK workers in essential AI skills by 2030, equivalent to around 20% of the UK workforce techUK. Banks sit right in the path of that shift, because so much of their decision-making now runs through models.
Put the two together and the picture is clear. The people banks want can hold their own on regulated, degree-level work, and they increasingly need to understand what AI is doing underneath that work. Model oversight is where those two threads meet.
Model oversight is not one job title. It is a skill showing up across credit risk, compliance, model risk management, data teams and front-line banking roles. The common thread is a person who can look at an AI model's output and ask the sharp questions: is this fair, is it explainable, and can we defend it to a regulator?
How firms build these skills is also changing. Apprenticeships have risen from 3% of AI hires in 2020 to 19% in 2025 GOV.UK / DSIT – AI Labour Market Survey 2025 report. That matters for banking, because apprenticeships let firms grow oversight skills in-house and attach them to the people who already understand the regulated context.
So the dynamic is twofold. Firms hire experienced, qualified specialists at RQF 6 and above for the hardest oversight work, and they grow a wider base of AI-literate people through upskilling and apprenticeships. Both routes point to the same outcome: oversight becoming an everyday expectation, not a rare specialism.
Start by writing the skill into the role, not bolting it on. Describe the judgement you actually need: can this person challenge a model's assumptions, read its outputs critically and document a decision an auditor could follow later? That gives you a far better brief than a long list of tools.
Next, look across two pools at once. There is the experienced, degree-level specialist who can own model risk, and there is the person you upskill through an apprenticeship who brings strong sector context and grows into oversight. Given that apprenticeships now make up a far larger share of AI hires than they did five years ago GOV.UK / DSIT – AI Labour Market Survey 2025 report, it pays to design a route for both.
Finally, move quickly and keep the process humane. Oversight talent is in demand, so a slow, unclear process costs you good people. Be specific about the problem, be honest about the regulated environment, and give every applicant a clear answer, whether that is a yes or a no.
This is where we help. We search a database of 15 million candidates to find and rank the right people for your model oversight and wider financial-services roles, then we handle the process end to end. Our recruitment agent manages recruitment end to end for 8% on a successful hire, with no monthly fee and no upfront cost. If you are building oversight into your teams this year, talk to Reed.ai and let's get your shortlist moving.
