A Blockchain and ML-Based Framework for Fast and Cost-Effective Health Insurance Industry Operations

【Author】 Elhence, Anubhav; Goyal, Adit; Chamola, Vinay; Sikdar, Biplab

【Source】IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS

【影响因子】4.747

【Abstract】Health insurance is crucial for each person, bearing in mind the increasing medical costs. COVID-19 has been an eye-opener as to how important it is to have health insurance. Medical emergencies can have a severe emotional and financial impact. Thus, a health insurance policy can help mitigate financial risks in unpredictable circumstances. However, the current insurance system is very expensive, as thousands of people pay the premiums, and very few take the claims. Furthermore, the claim settlement process is excruciatingly long and tiresome. In this article, we focus on establishing a rapid and cost-effective framework for the health insurance market, based on machine learning and blockchain technology. By developing a smart contract, blockchain may eliminate any third-party organizations and make the complete process safer, easier, and more efficient. The contract pays the claim based on the claimant's documentation. We optimized the premiums using a regression model based on the net amount claimed during the current policy tenure and various other criteria. For anticipating risk, a random forest classifier is used, which aids in the risk-rated premium rebate computation for policyholders for their next term of insurance.

【Keywords】Blockchain; Ethereum; insurance; machine learning; random forest; regression; smart contract

【发表时间】

【收录时间】2022-12-08

【文献类型】理论模型

【主题类别】

区块链应用-实体经济-保险领域