Safeguarding Consumer Data in Digital Insurance: Legal Frameworks and Ethical Imperatives

Abstract

The insurance industry is one of the industries that are digitally evolving at a high pace; therefore, harvesting and processing sensitive consumer information has become critical issues concerning privacy, security, and the moral mandate. This study explores the possibilities of combining legal frameworks and ethical requirements with technical protective measures to secure consumer information in the digital insurance providers. Conceptual and simulation-based approach was taken by applying synthetic insurance data applying four common data protection algorithms: Advanced Encryption Standard (AES), Rivest -Shamir-Adleman (RSA), k-anonymity, and differential privacy. The experimental results show that AES has a high data confidentiality rate of 99.8 per cent as well as low processing latency whereas RSA offers secure authentication rate of 98.6 per cent and attack resistance. Privacy-preserving analytics had a lower chance of re-identification of 8.5 with k-anonymity and 2.1 with differential privacy but with a slight decrease in the data utility. The outcomes of the ethical assessment showed that the highest score of the ethical compliance (9.3/10) was achieved by the methodology of differential privacy, which outcompeted the traditional security-only approaches. The comparative analysis with related work has shown that overall security, privacy, and ethical alignment scores went from 8.1, 7.4 and 7.0 to 9.2, 8.9 and 9.1 this way, due to the proposed integrated safeguarding. The results highlight the importance of a multi-layered solution that provides legal adherence, ethical governance, and advanced technical systems in order to provide credible and sustainable digital insurance systems.