As insurers are increasingly utilizing artificial intelligence for underwriting, pricing, and claims processing in an automated manner, end-to-end, open, and industry-level data governance solutions became the top priority. Although numerous AI-driven governance technologies are available, they are mostly purpose-built for generic corporate requirements and do not entirely meet the decision-making-oriented, ethics-conscious, and regulation-compliant insurance industry requirements. This paper presents a comparative evaluation of six top governance platforms—Collibra, Informatica CLAIRE, BigID, Immuta, IBM Watson Knowledge Catalog, and Alation—on eight dimensions, such as explainability, consent management, and insurance-specific flexibility. The research also illustrates the industry specific adoption of AI driven data governance in finance, health care and insurance along with a comparative insights amongst the three most data centric industry.  The study reviews insurance governance practices to assess capability gaps in the existing available commercial tools and strategic recommendations to insurers and tech vendors. This paper provides the basis for building AI governance systems that are compatible, scalable, fair, transparent, and flexible to the specific working context of the insurance data universe by overcoming technical limitations and moral dilemmas.

AI Governance, Insurance Technology, Data Governance Tools, Decision-Centric Automation, Regulatory Compliance, Ethical AI

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