EmergingFinancial services risk and compliance AI

Banking AI Governance Specialist

Also called Financial Services AI Risk Lead

A Banking AI Governance Specialist sets up and runs the controls around AI in banking and payment workflows. They help a company show regulators, partners and its own board that AI decisions are accountable and risks get closed.

What they do

The work starts with mapping where AI touches a financial workflow, such as fraud screening, credit decisions, customer queries or case triage. The specialist then defines the controls for each use: who approves it, what gets tested, what is monitored and when a human steps in. They work with model validators, engineers, compliance and operations to gather evidence and keep it in usable records. They run reviews, log findings, chase owners and check that fixes actually land. They also translate between technical teams and risk functions, so each side knows what the other needs.

What a strong hire delivers

In the first months, a strong hire produces a working control framework for the highest-risk AI uses, with named owners and clear approval steps. They set up evidence records that stand up to an audit or a partner bank's questions. They clear a first set of material risk findings and leave a visible trail of decisions. Teams also know when to involve governance and how long it takes.

How you can tell they are good

Ask them to walk through a control framework they built or ran, and what evidence it produced. Strong people explain trade-offs, not just policy. They can describe a finding that mattered, who owned it and how it was closed. Ask how they would test an AI tool they did not build. Worry if they only talk in frameworks and never in cases.

Why it is hard to fill

Few people have held this title, because the work usually sits inside model risk, financial crime, compliance or analytics jobs. Candidates tend to be strong on banking governance or on AI, rarely both. Titles vary widely, so searching by name misses most of them. We look at what people have actually owned and evidenced, then judge how far their experience stretches to AI.

Where to find them

Most come from model risk and validation teams in banks, payment firms and fintechs. Others come from financial crime analytics, fraud modelling, or financial machine learning teams that were pulled into oversight work. Some sit in second-line risk or internal audit and have started covering AI systems. Look for people whose current title says risk, analytics or validation but whose recent work is about AI.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for a Banking AI Governance Specialist

  1. Describe a control framework you built or ran for a model or automated decision. What evidence did it produce?

    A strong answer names the controls, owners and evidence records, and says how they were used in a review or audit. Worry if the answer stays at policy level or claims credit for a team's whole output.

  2. How would you validate an AI tool in a banking workflow when you did not build it and have limited access to its internals?

    Look for testing on outcomes, benchmark data, sampling, monitoring and clear documentation of limits. They should say what they cannot conclude. Worry about false confidence or insisting on full access as the only route.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are hiring a Banking AI Governance Specialist to set up and run the controls around AI in our banking and payment workflows. You will work across engineering, risk and compliance so that AI decisions are accountable, evidenced and safe to scale.

What you will do

  • Map AI use across financial workflows and rate the risk of each
  • Design and maintain a control framework with clear owners and approval steps
  • Keep evidence records that support audit and partner reviews
  • Work with validators and engineers to test AI systems before and after release
  • Log material risk findings and drive them to closure
  • Brief senior decision makers on risks and options
  • Advise teams early on what governance needs

What you will bring

  • Demonstrated work in model risk, financial crime, banking analytics or financial ML
  • Experience building or running controls and producing audit-ready evidence
  • Working knowledge of financial model validation methods
  • Solid grounding in probability and statistics
  • Understanding of privacy engineering in data-heavy workflows
  • Track record of closing risk findings with busy teams
  • Clear writing and communication with technical and non-technical people

Nice to have

  • Experience with case-management systems
  • Exposure to validating machine learning or generative systems
  • Experience working with regulators or partner banks

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Financial model validationAdvancedChallenge financial-model assumptions and limitations
  • Probability and statisticsAdvancedQuantify variability and statistical evidence
  • AI risk managementWorkingIdentify, assess, treat and monitor AI risks
  • Privacy engineeringWorkingLimit disclosure and unauthorised personal-data use

Other roles in financial services risk and compliance AI

Hiring nowCredit Risk AI ScientistA Credit Risk AI Scientist builds credit models and proves they hold up. They show the models predict well, stay calibrated and treat groups fairly…Hiring nowFinancial Crime AI SpecialistA Financial Crime AI Specialist builds and evaluates models that surface suspicious activity inside governed investigation workflows. They help a…Hiring nowAI Financial Model ValidatorAn AI Financial Model Validator independently challenges the financial AI models a bank or payments company relies on. They find weaknesses before…

Related roles in other families

Hiring nowInsurance ML ScientistInsurance, actuarial and claims AIAn Insurance ML Scientist builds risk, claims and operations models that can be validated, explained and defended. They let a company use machine…EmergingAI Actuarial SpecialistInsurance, actuarial and claims AIAn AI Actuarial Specialist tests whether AI methods hold up inside actuarial assumptions and controls. They give the company defensible models and…Hiring nowClaims Automation AI EngineerInsurance, actuarial and claims AIA Claims Automation AI Engineer builds bounded workflows that support and triage insurance claims, with human escalation built in. They help a…EmergingInsurance AI Fairness AnalystInsurance, actuarial and claims AIAn Insurance AI Fairness Analyst tests whether pricing, claims and underwriting models treat different groups of customers differently, and explains…

How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

← Financial services risk and compliance AIAll new job families

Start a search

Hiring a Banking AI Governance Specialist?

Tell us the work. We find the people already doing it, whatever their job title says, and you meet them already interviewed for your role.