Fraud Detection in Privacy Preserving Health Insurance System Using Blockchain Technology

In developed countries, around 90% of the population is covered by health insurance through public or private providers. However, fraudulent activities account for an estimated 3%–10% of total healthcare expenditures, resulting in financial losses exceeding $300 billion annually. These fraudulent practices erode trust among patients, healthcare providers, and insurers, further complicating the insurance claim process. Additionally, claim rejection rates due to fraudulent activities are estimated to range between 25% and 35%, which impacts its efficiency and trustworthiness and weakens the industry's reliability. The digitization of healthcare and the health insurance industry has amplified the need for robust and trustworthy systems that ensure data security and optimize the insurance claim process. To address these issues, this paper proposes a system that ensures patient anonymity through secure credentials and advanced fraud detection mechanisms. Privacy is preserved using cryptographic techniques such as secure hashing and anonymous credentials, which ensure that sensitive patient information remains confidential throughout the claim process. Smart contract algorithms are utilized in two scenarios: patient-submitted claims and healthcare provider-submitted claims, ensuring accurate processing and validation while detecting fraudulent activities such as duplicate claims, inflated medical bills, billing for unprovided services, falsifying patient records, and submitting claims for nonexistent treatments. The proposed system has been implemented and tested on a blockchain platform, demonstrating its effectiveness in preserving privacy and detecting fraud. Performance evaluations reveal its scalability and efficiency in managing increased user loads, offering a robust solution to modern health insurance challenges while fostering trust and operational efficiency among participants.