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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.

AI and Technology

Each of these is named in at least one of the same controls as model validation. The number is how many controls name both.

What the standards actually require on model validation

Requirements naming model validation across 4 standards, quoted from the control text.

IEEE 70001 control

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?
The process of evaluating an AI or analytical model to verify it performs as intended, produces accurate results, and complies with regulatory requirements.
Why is Model Validation important for compliance?
Model Validation is a key concept in AI and Technology. Understanding model validation helps organizations meet regulatory requirements, reduce risk, and demonstrate due diligence during audits. Our compliance platform maps 686 frameworks with 311K cross-framework control mappings.
Which compliance frameworks address Model Validation?
Model Validation appears in the requirement text of IEEE 7000, OECD AI Principles, Own Risk and Solvency Assessment (ORSA) - NAIC Model Act, UK AI Regulation Framework. Across these standards we have identified 4 controls that name it directly, each linked to the control text on the compliance platform.
Where can I learn more about Model Validation?
Explore our compliance framework pages to see how model validation applies across different standards and regulations. Our implementation guides provide step-by-step guidance, and the compliance platform offers AI-powered analysis of how this concept maps across 686 frameworks.

See how Model Validation applies across compliance frameworks

Our platform maps 686 frameworks with 311K cross-framework control mappings. Explore how this concept is addressed across standards.

Written and maintained by Gerard Blokdyk, The Art of Service.