What does AI Verify Testing Framework say about AI in banking?

What are the key points of AI Verify Testing Framework?

• Eleven principles: transparency, explainability, reproducibility, safety, security, robustness, fairness, data governance, accountability, human agency and oversight, and inclusive growth, societal and environmental well-being.
• Four elements: principles, desired outcomes, testing processes (technical tests and process checks) and documentary evidence that validates each process.
• Covers both traditional and generative AI and is mapped to the NIST AI RMF, the NIST Generative AI Profile, the Hiroshima Process International Code of Conduct and ISO/IEC 42001.
• A process-checks tool lets organisations 'Generate a summary report that shows your alignment with AI Verify Testing Framework', and technical testing tools complement the framework.
• IMDA's 7 June 2023 release says the pilot 'attracted the interest of over 50 local and multinational companies including IBM, Dell, Hitachi and UBS', and the Foundation launched with more than 60 general members including DBS.
• The PDPC's 2024 Advisory Guidelines (paragraph 10.10) suggest using AI Verify explainability and fairness test results to identify influential data features and show there has been no unreasonable discrimination in AI systems that use personal data.

What did AI Verify Testing Framework change for banks?

AI Verify turned the Model AI Governance Framework into a testable checklist and code base, and the 2023 move to an open-source foundation made it a shared reference rather than a government tool. For banks it is a way to produce structured evidence of explainability, fairness and robustness testing that maps to NIST and ISO frameworks they already use.