AI Governance in Insurance: Establishing Controls for Transparent and Auditable Decisions

Authors: Jalees Ahmad

DOI: https://doi.org/10.37082/IJIRMPS.v13.i5.232938

Short DOI: https://doi.org/hbphz9

Country: United States

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Abstract: The insurance industry is undergoing a structural metamorphosis driven by the integration of artificial intelligence across the entire value chain. From automated underwriting and real-time risk assessment to sophisticated fraud detection and claims triage, AI-driven systems are replacing static, rule-based legacy processes. While these advancements offer significant improvements in operational efficiency and pricing precision, they also introduce systemic risks related to algorithmic bias, opacity, and regulatory non-compliance. This report examines the foundational requirements for establishing robust AI governance frameworks designed to ensure transparency and auditability. By analyzing global regulatory developments—including the European Union AI Act and the National Association of Insurance Commissioners (NAIC) Model Bulletin—this study delineates the technical and organizational controls necessary for responsible AI deployment. Key focus areas include the implementation of Explainable AI (XAI) techniques, the establishment of comprehensive "AIS Programs," the adoption of semantic record-keeping, and the integration of rigorous bias mitigation strategies. The findings emphasize that governance must move beyond a check-the-box compliance exercise toward a "defensible-by-documentation" architecture that preserves consumer trust while fostering sustainable innovation.

Keywords: AI Governance, Algorithmic Transparency, Insurance Regulation, Explainable AI, Model Risk Management, Bias Mitigation, Auditability, Actuarial Science.

Paper Id: 232938

Published On: 2025-10-10

Published In: Volume 13, Issue 5, September-October 2025

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