Institutional Safety, Governance & Trust / AI Assurance
SUB-T06-002Model Risk Assessment
Definition
Model Risk Assessment is the systematic design and evaluation of model risk assessment within the structured demonstration that AI systems are sufficiently safe, reliable, lawful and fit for their intended purpose.
Why this matters
Weak model risk assessment can lead to unsafe deployment, unlawful or unauthorised action, wasted public resources, loss of rights, poor accountability and declining institutional trust.
Research questions
Which controls, evidence and institutional arrangements make model risk assessment effective in practice, and how do outcomes vary by sector, system risk, organisational maturity and operating context?
Hypotheses
An explicit, testable and continuously evidenced approach to model risk assessment, with clear ownership, independent review, runtime telemetry and recovery, will outperform policy-only or periodic compliance approaches.
Proposed methods
assurance case analysis; model and system testing; hazard analysis; independent review; control validation; red-team exercises; stakeholder interviews; document and control review; fault and incident simulation; longitudinal implementation assessment; methods adapted specifically to Model Risk Assessment
Stakeholders and beneficiaries
citizens; public servants; executives; boards; regulators; auditors; legal and risk teams; technology teams; service users; civil society; suppliers