Representative Matters
AI Governance
AI Governance Framework
Built an end-to-end model governance framework covering intake, risk classification, and human oversight.
- Engagement
- Framework design
- Scope
- Governance, policy
- Sector
- Financial services
The challenge
Business units were deploying AI tools independently, with no shared definition of acceptable risk and no record of which systems touched regulated data.
Our approach
01
Model inventory and intake
Created a single register of AI systems with a short intake form gating new deployments.
02
Risk tiering
Defined tiers keyed to regulatory exposure, data sensitivity, and impact on individuals, each with proportionate controls.
03
Oversight and escalation
Assigned accountable owners, documented human-review requirements, and set an escalation path for incidents.
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