A modular AI model risk scoring engine forming the foundation of an internal AI governance toolkit.
This project operationalises a structured and extensible risk scoring framework using model complexity and data sensitivity to:
- Classify AI models into risk tiers
- Support governance-based escalation pathways
- Visualise accountability across model owners and departments
- Enable consistent oversight across the AI lifecycle
The engine is designed to evolve into a broader internal AI governance toolkit supporting policy alignment, regulatory readiness, and operational risk monitoring.
- Risk scoring logic
- Governance factor weighting
- Configurable inputs
- Extensible architecture
- Python 3
- Virtual Environment
- Git + GitHub
- Add risk scoring logic
- Add weighted scoring model
- CLI output formatting
- Config file support
- Basic web UI (future)
Built as part of AI GRC engineering exploration.