The policy and control repository for AI model risk in a financial-services organization, the governance backbone that defines how every model is validated, monitored, escalated, and reviewed across its lifecycle.
Governance is not documentation written after the fact.
It is the standing control layer that decides what is validated, who is accountable, when humans review, and how evidence is retained, before a model ever reaches production. This wiki is that layer for an organization expanding AI into a stronger financial presence: the single, transparent record of model practices, regulation guidelines, fraud-detection guidelines, audit history, and the risk-management procedure.
The defining principle: the higher the risk a model carries, the more often it is reviewed.
This wiki is the policy and control repository, it defines what policies apply, who owns decisions, how AI systems are classified, and when human review is triggered. The AI Transformation Portfolio Office (Lab 02) executes those rules against live initiatives, flagging governance exceptions and enforcing the risk-tiered review cadence across the whole portfolio. Together they form the governance operating system.