Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

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Small Business Credit Model Governance

Github

Small Business Credit Model Governance is an open-source (Apache-2.0) technical demonstration that helps model-risk and compliance reviewers organise repeatable governance evidence for machine-learning-assisted small business credit underwriting. It provides a reproducible workflow, including structured model and version records, threshold monitoring, adverse-action reason quality checks, fair-lending screening, model-change review, issue tracking, and reviewer signoff. The workflow is built around synthetic fixtures and scoped public-data run kits so the process can be inspected without confidential lender data.

The tool supports traceability across the governance lifecycle. It links records, thresholds, reason-code mappings, monitoring outputs, issue registers, and signoff artifacts back to governed inputs and reproducible review runs, and it cross-references its workflow against the NIST AI RMF Govern, Map, Measure, and Manage functions. It ships JSON schemas, governance templates, validation and monitoring scripts, curated evidence packs, and three role-oriented run kits covering adverse-action reason accuracy, model-risk oversight using public SBA loan data, and credit-union AI vendor-risk review.

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Tags:

  • ai governance
  • model validation
  • model risk management
  • traceability
  • credit underwriting
  • adverse action reasons
  • monitoring thresholds
  • evidence packs
  • small business lending
  • financial services
  • issue registers

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.