ARTIFICIAL INTELLIGENCE
AI Governance for Financial Institutions
A decision and control framework that supports AI progress without separating innovation, risk and accountability.
← Back to expertise
Challenges
AI Governance for Financial Institutions
- Use cases launched without common qualification and prioritisation criteria.
- Unclear accountability across business, Data, IT, Risk, Compliance and Legal.
- Fragmented controls for data, models, providers and generative AI uses.
What KALTAVIA brings
What KALTAVIA brings
We design governance around the use-case portfolio: roles, classification, stage gates, documentation requirements, controls and ongoing oversight.
Typical deliverables
- AI governance policy and principles
- Use-case inventory and taxonomy
- Risk-classification model
- Assessment and approval workflow
- Monitoring, documentation and incident framework
Who it is for
- Data leadership and AI Offices
- Risk, Compliance, Legal and Model Risk
- Business use-case owners
- Architecture, security and technology teams
Our approach
Our approach
- 01
Clarify ambitions, constraints and accountabilities.
- 02
Map use cases, models and providers.
- 03
Define controls proportionate to risk and intended use.
- 04
Test the framework on live cases, then organise adoption.
FAQ
Frequently asked questions
Would you like to frame this topic?
Share your context with us. We will use an initial scoping conversation to focus on your priorities.