Report

Explaining AI and ML Algorithm Outcomes to Insurance Regulators

Explaining AI and ML Algorithm Outcomes to Insurance Regulators

Pages 6 Pages

The June 2023 report emphasizes that insurers’ AI adoption for underwriting, claims, and document processing will be limited unless decision-making can be explained to regulators, clients, and prospects. AI models often operate as “black boxes,” creating transparency challenges. CIOs and CTOs should establish model explainability and validation processes, assign accountable owners within governance frameworks, enable human intervention with audit trails, ensure transparent and fair outcomes, address data privacy and bias, and provide mechanisms for clients to question and challenge AI-driven decisions .

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