A Hybrid Approach: Machine Learning and Blockchain in Health Insurance Fraud Detection

This research introduces a system that integrates machine learning with blockchain technology, ensuring data transparency, security, and immutability while enhancing predictive accuracy. Demonstrated with real-world health insurance data, this hybrid approach significantly improves fraud detection accuracy and efficiency. Advanced machine learning algorithms provide insights into patterns and anomalies, enabling proactive fraud prevention. The solution is scalable and adaptable to other sectors prone to fraud. The use of Hyperledger blockchain ensures robust data integrity and security, addressing challenges related to data tampering and unauthorized access. These contributions collectively advance fraud detection and prevention in the health insurance industry.