Model Risk Assessment Toolkit (interactive audit + scoring)

Reviewer name

Person completing this audit.

Review date

Use YYYY-MM-DD or your local date format.

Model name / identifier

Unique name or identifier for the model under review.

Model version

Version, commit, or release tag.

Data provenance & labeling — checklist

Select items that are present and verified.

Primary data sources documented

Data lineage and ingestion pipeline traced

Labeling schema and instructions exist

Label quality and inter-annotator agreement assessed

Training/validation sampling and coverage examined

PII removal and privacy-preserving steps documented

Data provenance & labeling — section risk (0–5)

0 = negligible risk; 5 = critical risk; consider data lineage and label quality when scoring

1.0 10.0

Evidence & notes — data provenance

Links to artifacts, datasets, tickets, or short notes.

Explainability & documentation — checklist

Select controls and artifacts available.

Technical specification (objectives, inputs, outputs)

Model card or factsheet created

Feature definitions and importance documented

Interpretability/SHAP/LIME or other analyses performed

Known limitations and intended use documented

Explainability & documentation — section risk (0–5)

Consider clarity of intent, known limitations, and stakeholder-facing documentation.

1.0 10.0

Evidence & notes — explainability

Performance across key slices — checklist

Evaluate evaluation strategy and slice performance.

Holdout and cross-validation results available

Performance reported across meaningful slices (demographic, temporal, geographies)

Calibration and uncertainty estimates computed

Drift detection for features/labels implemented

Robustness/adversarial or stress tests performed

Performance across key slices — section risk (0–5)

Consider worst-performing slices and potential customer/regulatory impact.

1.0 10.0

Evidence & notes — performance

Operational controls & monitoring — checklist

Operational readiness and incident handling.

Deployment runbook and rollback plan exist

Production monitoring metrics & alerts defined

Model retrain/update policy defined

Access controls and change control applied

Incident response and escalation documented

Operational controls & monitoring — section risk (0–5)

Assess ability to detect and correct issues in production.

1.0 10.0

Evidence & notes — operational controls

Regulatory & privacy mapping — checklist

Regulatory, contractual, and privacy requirements.

Regulatory and industry obligations mapped to model use

Data consent and lawful basis documented

Privacy/data protection impact assessment performed

Customer/partner contractual constraints identified

Controls to meet legal/regulatory requirements implemented

Regulatory & privacy mapping — section risk (0–5)

Score regulatory exposure and privacy gaps.

1.0 10.0

Evidence & notes — regulatory & privacy

Overall model risk score (0–5)

Reflects aggregated judgment across sections; use notes to justify a high overall score.

1.0 10.0

Recommended remediation actions

Concrete next steps, owners, and suggested priority.

Links to evidence (tickets, docs, datasets)

URLs, repo paths, or ticket numbers.

Reviewer confidence in this assessment (0–5)

How confident is the reviewer that evidence and checks are adequate?

1.0 10.0

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Model Risk Assessment Toolkit (interactive audit + scoring)

Model Risk Assessment Toolkit — Interactive Audit

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