Model Validation
What is Model Validation?
The process of evaluating an AI or analytical model to verify it performs as intended, produces accurate results, and complies with regulatory requirements.
Terms that appear alongside model validation
Each of these is named in at least one of the same controls as model validation. The number is how many controls name both.
- governance 2 shared controls
- bias detection 2 shared controls
- nist 2 shared controls
Frameworks that govern model validation
What the standards actually require on model validation
Requirements naming model validation across 3 standards, quoted from the control text.
Starting from the business case, the requirements (business information, functional, technical and control) across all initiatives needed for the intended outcomes are identified, ranked, specified and agreed: every stakeholder requirement, acceptance criteria...
cobit-2019::BAI02.01 · BAI02.01 Define and maintain business functional and technical requirements →Adhere to OECD AI Principles Section 1.4 (Robustness + security + safety). AI systems should be robust + secure + and safe throughout their entire lifecycle so that in conditions of normal use + foreseeable use or misuse + or other adverse conditions they func...
OECDAI-3 · Robustness, Security, Safety, and Adversarial Attack Protection →Section 2 summarises quantitative and qualitative assessments of exposure for each material risk category named in Section 1 (for example underwriting, credit, market, liquidity and operational risk) under both normal and stressed conditions, with methods prop...
ORSA-S2 · Guidance Manual Section 2: Insurer's assessment of risk exposures →Questions people ask about model validation
What is Model Validation?
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Which compliance frameworks address Model Validation?
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See how Model Validation applies across compliance frameworks
Our platform maps 1,016 frameworks with 316K cross-framework control mappings. Explore how this concept is addressed across standards.