Governance that holds up to scrutiny.
Every engagement is built around the same principle: AI adoption should survive regulatory review, internal audit, and board-level questioning — not just a pilot demo.
AI & GenAI Governance Frameworks
We design governance structures — policy, roles, controls, and escalation paths — that let institutions adopt AI and GenAI with a defensible story for regulators, auditors, and the board.
- AI governance policy and standards development
- Risk taxonomy and control mapping for AI/GenAI use cases
- Committee structure and escalation design
- Regulatory-readiness review ahead of exams
Model Risk Management
Traditional model risk discipline, extended to cover the questions generative and agentic systems raise that legacy MRM frameworks weren't built to answer.
- Model inventory and tiering for traditional and generative models
- Independent validation approach and challenge
- Ongoing monitoring design for GenAI and agentic systems
- Third-party and vendor model risk assessment
Advisory & Implementation
Hands-on support for institutions standing up an AI governance function for the first time, or maturing one that hasn't kept pace with how fast AI is moving.
- Governance program stand-up, start to finish
- Gap assessments against current supervisory expectations
- Executive and board education on AI risk
- Interim / fractional AI risk leadership
Independent Research
Practitioner-level analysis of how AI risk and governance practice is evolving — used to keep our own frameworks current, and shared with clients directly.
- Ongoing tracking of supervisory guidance and enforcement trends
- Emerging practice benchmarking across peer institutions
- Point-of-view papers on agentic AI and governance maturity
How engagements actually run
Every engagement follows the same four steps. How long each takes depends on where you're starting — but the sequence doesn't change.
Assess
Where the program actually stands against supervisory expectations — inventory coverage, control evidence, ownership gaps. Output is a candid stage placement, not a scorecard designed to flatter.
Design
Framework, controls, and operating model built for how your institution is examined — sized to the risk, not copied from a template.
Implement
Standing the program up in practice: committee structure, escalation paths, validation approach, and the training that makes it stick beyond the first quarter.
Sustain
Monitoring, periodic refresh, and exam readiness — so the program keeps pace with new models and new guidance instead of drifting back to ad hoc.
Not sure which of these you need first?
That's normal — most engagements start with a short scoping conversation.