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 4 standards, quoted from the control text.
Clauses 7 + 7.1 establish ethical requirements definition and traceability. Per public IEEE 7000-2021 abstract + Wikipedia + academic literature (full IEEE text NOT reproduced): translate prioritised ethical values + stakeholder concerns into system requiremen...
IEEE7000-EthicalRequirements-ValueBased-Traceability-DesignIntegration · IEEE 7000 Clauses 7 + 7.1 - Ethical Requirements Definition + Value-Based Requirements + Traceability + System Engineering Design Integration + AI Validation →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 →Per NAIC ORSA Guidance Manual Section 3: group risk capital and prospective solvency assessment. Requires Available Capital Assessment per regulatory + economic + rating agency capital measures;
ORSA-S3 · ORSA Manual Section 3: Group Risk Capital and Prospective Solvency Assessment →Per UK AI Principles: Bias detection and mitigation + AI model validation and testing + fairness across protected characteristics + ongoing monitoring.
UKAI-3 · Bias Detection, Fairness, Validation →Questions people ask about model validation
What is Model Validation?
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