AI GOVERNANCE & COMPLIANCE ADVISORY
Before an AI system touches a lending decision, it should be governed like one.
Mieru Consulting helps banks, fintechs, and regulated institutions align AI systems to ISO/IEC 42001 and the NIST AI RMF — and gives compliance teams an independent second opinion before they buy.
WHY THIS MATTERS
Adoption moved faster than the paperwork.
Most institutions already have AI making decisions somewhere inside the business — flagging transactions, scoring risk, screening applicants. Few can produce, on short notice, who owns that model, what data trained it, or when it was last reviewed. That gap is where audits stall, correspondent banks ask harder questions, and regulators start writing new rules. Closing it before you're asked to is the cheaper version of this problem.
SAMPLE POLICY CLAUSE — BEFORE / AFTER
ENGAGEMENTS
Three ways in, one register.
§ 01
Framework Alignment
A structured gap assessment against ISO/IEC 42001 and the NIST AI RMF, translated into a prioritized roadmap — not a slide deck. You'll know exactly which controls exist, which are missing, and what order to build them in.
§ 02
Governance Build-Out
Policies, a model inventory, an oversight structure, and the audit trail to back it up — built to survive an actual examiner's questions, not just a checklist.
§ 03
Buying & Vendor Advisory
Before you sign with an AI vendor, an independent read on what you're actually buying: what data it touches, what governance it assumes you already have, and what you're on the hook for if it's wrong.
HOW IT WORKS
The same four functions your framework already names.
Not a diagram — the actual sequence of an engagement, mapped to the functions NIST's AI RMF already uses, with real deliverables at each stage.
GOVERN
Typically 2–4 weeks
Set ownership and policy before anything else moves.
Nothing else in this list works if no one owns it. This stage puts a name against every AI system in scope, defines who can approve a new one going into production, and writes the policies that make the rest of the engagement enforceable rather than aspirational — acceptable use, model risk tiers, third-party AI, and what happens when something goes wrong.
- AI governance charter and policy set — acceptable use, model risk, third-party AI
- Ownership and accountability matrix, one line per system
- Escalation and sign-off procedure for new AI use cases
- Alignment with existing risk and audit committees
MAP
Typically 3–6 weeks, depending on system count
Find out what's actually running — not what's on the org chart.
Most inventories miss something: a spreadsheet macro that's quietly become a credit-scoring tool, a vendor feature nobody remembers enabling, a fraud model three layers deep in a platform you already pay for. This stage builds the real inventory — every AI system in production or pending, what data it touches, what decision it informs, and who's exposed if it's wrong — then classifies each one by risk so effort goes where it matters.
- Full AI/ML system inventory, including vendor and embedded tools
- Risk classification per system — data sensitivity, decision impact, autonomy
- Data flow and dependency map for each system
- Gap list against your target framework — ISO/IEC 42001 or NIST AI RMF
MEASURE
First pass typically 4–8 weeks, then ongoing
Test each system against the risks that would actually hurt you.
Generic bias-and-fairness testing checks a box; it doesn't tell you whether your fraud model false-flags a specific customer segment, or whether your credit model has drifted since it went live. This stage runs the tests that map to your actual exposure — accuracy and drift, bias across the groups your regulator cares about, explainability for adverse decisions — and documents the results in a form an examiner can follow, not a summary score.
- Testing protocol per system — accuracy, drift, bias, explainability
- Documented results with evidence, not summary scores alone
- Explainability documentation for any system touching adverse decisions
- Residual risk register with named owner sign-off
MANAGE
Ongoing, with a formal handoff
Put controls in place that outlast the engagement.
A governance program that only exists while I'm in the room isn't one. This stage builds the monitoring, review cadence, and incident response your team runs on its own after I leave — including what triggers a re-review, who can pull a model from production, and how an incident gets reported up instead of discovered by a regulator first.
- Monitoring plan and thresholds per system
- Review cadence tied to risk tier
- Incident response and model rollback procedure
- Decommissioning criteria and change management process
- Internal handoff — your team runs it, not me
WHO'S DOING THE WORK
Independent, not embedded in a vendor's roadmap.
Mieru Consulting is an independent AI governance and compliance practice. My background includes implementation consulting at McKinsey & Company, working directly inside large organizations on how strategy actually gets built and run — followed by hands-on AI governance work at an AI governance technology company, with a specific focus on financial institutions: the policies, model inventories, and audit questions regulated clients get graded on.
I work independently now, which means my read on your AI stack — or on the vendor pitching you one — isn't shaped by anyone's sales quota.
QUESTIONS
Before you book a call.
Why an independent consultant instead of a big firm?
A big firm sells you a partner for the pitch, then staffs the actual work with junior analysts who learn your business on your clock — and you pay for that learning curve. Here, one person scopes the engagement and does it. No handoffs, no one billing you to get up to speed.
Are you certified in ISO/IEC 42001 or the NIST AI RMF?
My grounding in both comes from applying them directly — building governance programs against them, not just studying for an exam. If a specific certification is a hard requirement on your end, tell me and we'll figure out if that's a fit before either of us spends time on it.
How long does an engagement take?
A Framework Alignment assessment usually runs 4–10 weeks depending on how many systems are in scope. A full Governance Build-Out typically takes 3–6 months end to end. The stage-by-stage breakdown above (Govern, Map, Measure, Manage) shows the timeline for each phase.
What does this cost?
Readiness assessments start at $3,500. Framework Alignment and Governance Build-Out are scoped after a short call, since price depends heavily on how many AI systems are in play and how many regulators you answer to — a flat number quoted blind wouldn't be honest.
Do you only work with banks?
Most of the work is with banks, fintechs, and trust companies, but the underlying problem — AI making decisions nobody can fully account for — isn't unique to banking. If that's your situation, reach out and we'll figure out if it's a fit.
Do you just advise, or do you implement?
Both. Some clients want a roadmap and take it from there internally; others want the policies, inventory, and monitoring actually built. Either way works — it's your call how far the engagement goes.
GET IN TOUCH
Start with a readiness call.
Thirty minutes, no deck. Tell me what's live, I'll tell you where the gaps probably are.