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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/9829
Title: A Blockchain and ML-Based Framework for Fast and Cost-Effective Health Insurance Industry Operations
Authors: Chamola, Vinay
Keywords: EEE
Blockchain
Ethereum
insurance
Machine Learning
Random forest (RF)
Issue Date: 2022
Publisher: IEEE
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.
URI: https://ieeexplore.ieee.org/abstract/document/9945906
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9829
Appears in Collections:Department of Electrical and Electronics Engineering

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