Design and Implementation of a Blockchain-Based Family Insurance Policy Inquiry System

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Abstract

Insurance serves as a critical financial planning tool and a safeguard against unexpected events in modern society. However, insurance policies are often complex and lack transparency, making it challenging even for close family members to access clear and accurate information. In situations where a family member experiences a sudden illness or passes away, relatives frequently encounter difficulties in quickly obtaining the relevant policy details. This information gap can lead to unawareness of the policy's existence or misunderstanding of its terms, potentially resulting in the loss of rightful benefits and entitlements. This paper introduces a novel family insurance policy inquiry system leveraging blockchain technology and smart contracts. The proposed system called "ChainSure"addresses critical challenges in traditional insurance policy management, including lack of transparency, limited accessibility, and potential data tampering. By storing insurance policies on a decentralized blockchain, the system ensures data immutability and enhances trust among family members. Smart contracts are employed to automate policy verification and query processes, enabling secure and efficient information retrieval. Family members can seamlessly access policy details while maintaining strict data privacy through role-based permissions. This study outlines the system's design, implementation, and potential to revolutionize the way insurance policies are managed and accessed within a family context. The results highlight its scalability, security, and practicality for real-world adoption, demonstrating its capacity to improve transparency and foster trust in family insurance management.

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APA

Lin, C. C., Lai, Y. C., Ciou, B. H., Tsai, Y. T., Xu, Z. L., & Chang, S. Y. (2025). Design and Implementation of a Blockchain-Based Family Insurance Policy Inquiry System. In BIOTC 2025 - 7th Blockchain and Internet of Things Conference (pp. 32–38). Association for Computing Machinery, Inc. https://doi.org/10.1145/3760550.3760555

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