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Framework and processes for the responsible, safe and legally compliant use of AI systems.
AI governance establishes frameworks, processes and accountabilities for safe, fair and legally compliant deployment of AI systems. It includes policies, risk assessments, monitoring and procedures for model explainability and auditability. The aim is to build trust and systematically meet regulatory and ethical requirements across the organization.
Number of model and risk reviews performed per period.
Number of significant misdecision or bias incidents in production.
Number of deviations from internal policies or regulatory requirements.
Organization aligns processes with EU ethics principles, implements impact assessments and documents decisions systematically.
Bank defines different review paths for credit scoring models based on risk and audit needs.
SaaS provider establishes alerts, retraining rules and dashboards to monitor model performance.
Starter assessment for inventory and prioritization
Define policies, roles and review processes
Introduce technical basics: logging, monitoring, explainability