Blockchain-based Smart Contract with Machine Learning for Insurance Claim Verification
Kruthika Alnavar, C. Narendra Babu
Abstract
Blockchain is a decentralized, immutable, peer-to-peer network which provides trust, transparency, and tamper resistance and these features have led to various applications such as bitcoin and ethereum. Various structures of Blockchains are designed in fields such as e-health as it can facilitate safe and secure storage of the patient’s information in the health care system. Data integration problem in healthcare can be overcome by bringing a decentralized system in the hospital organization. This paper focuses on the use of Blockchains in managing medical records for insurance claim. By removing the central administrator, the suggested architecture uses Ethereum smart contracts to create a tamperproof and transparent healthcare system and ensure the integrity of sensitive patient data. Additionally, the smart contract keeps the patient well-informed and governs the communication between all the participants in the network. The proposed approach provides a solution to eliminate fraudulent insurance claims using Machine Learning (ML) with Blockchain. Machine Learning techniques such as Random Forest Classifier, Support Vector Machines are used along with Python and Solidity languages and an accuracy of 88% is achieved on the healthcare data set.