Briefing overview
Bank AI governance must cover internally developed models, vendor capabilities, generative assistants, analytics, automation, and embedded decisioning without forcing every use through the same process. The briefing focuses on a risk-tiered approach tied to actual banking decisions and customer impact.
Use-case classification
Inventory, data lineage, model and vendor versions, testing, validation, limitations, approvals, deployment, user guidance, monitoring, incidents, issues, and changes.
Lifecycle evidence
Access, grounding, policy boundaries, explanations, human review, overrides, logging, escalation, customer communication, and output handling.
Controls in operation
Risk and use inventory, approval and exception trends, validation and monitoring status, incidents, remediation, vendor change, outcomes, and decisions requiring attention.
Who the briefing is for
- Business and product leaders sponsoring AI use
- Model risk, responsible AI, compliance, legal, and internal audit
- Data science, technology, architecture, and security
- Operations and control owners responsible for human review
- Executives and board committees overseeing material AI risk
