Authors - Tanmoy De, Vimal Kumar, Pratima Verma Abstract - The traditional centralized insurance operation has contributed to insurance fraud due to poor identity verification systems, fragmented data sharing, and slow manual validation, all leading to substantial financial loss and loss of faith in the integrity of the operation. This research aims to develop a framework for an insurance operation that provides security, transparency, intelligence, and improved fraud detection accu- racy while meeting the privacy and interoperability needs of insurers and their related stakeholders. The proposed framework is a decentralized solution that employs blockchain, self-sovereign identity (SSI), artificial intel- ligence (AI), and federated learning to create secure identity cre- ation processes, transparent policy management, and intelligent verification of claims. The results of experimental evaluations of the proposed framework show that it provides increased fraud detection accuracy, reduced duration of processes, and improvements in transparency over current processes. Thus the suggested method improves efficiency and trust in insurance ecosystems and can be applied to real-world implementations with sophisticated identity integration and extensive blockchain networks.
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