Advisory

AI Risk &
Governance

AI/LLM model risk, bias, explainability, and data governance —
integrated into your existing risk structures and regulator-defensible.

The challenge

Financial institutions are deploying AI and LLMs across credit decisioning, fraud detection, compliance monitoring, and customer interactions. But most lack dedicated governance frameworks. Existing model risk and operational risk structures weren't designed for AI's unique risks: bias, hallucination, data leakage, explainability gaps, and rapidly evolving regulatory expectations from OSFI, the Federal Reserve, and the EU AI Act.

Our approach

We don't treat AI governance as a separate silo. We integrate AI risk into your existing model risk management, operational risk, and compliance frameworks — so governance is embedded, not bolted on. Our advisors have hands-on experience implementing AI governance at Tier 1 banks under active supervisory scrutiny.

What we deliver

  • AI/LLM model risk framework design and integration
  • Bias and fairness assessment methodologies
  • Explainability frameworks for regulatory defensibility
  • Data governance for AI (lineage, quality, consent)
  • Responsible AI policy and ethical use guidelines
  • Regulatory alignment (OSFI, Fed, EU AI Act, CBUAE)
  • AI model inventory, tiering, and oversight protocols
  • Third-party AI risk assessment for vendor models

Typical outcomes

  • AI governance that holds up under supervisory review
  • Reduced model risk from AI/LLM deployments
  • Clear accountability and oversight for AI usage
  • Faster, safer AI adoption with embedded controls

Ready to govern AI with confidence?

Let's discuss your AI governance needs and build a framework that works.