基于区块链和机器学习的高效健康保险管理框架

Adit Goyal, Anubhav Elhence, V. Chamola, B. Sikdar
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引用次数: 4

摘要

考虑到不断增加的医疗费用,拥有一份健康保险对每个人都很重要。医疗紧急情况可能会造成严重的经济和情感影响。然而,目前的保险制度非常昂贵,理赔过程过于冗长,使其变得乏味。这导致投保人无法成功地向保险公司提出索赔。在本文中,我们专注于为健康保险行业开发基于区块链技术和机器学习的快速且具有成本效益的框架。区块链能够通过形成智能合约来移除所有第三方组织,使整个过程更加顺畅、安全、高效。合同根据索赔人提交的单据解决索赔问题。根据当前保单期限内的索赔总额以及其他几个因素,使用山脊回归模型来最优地计算保费。采用随机森林分类器进行风险预测,帮助计算风险级保费返还。
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A Blockchain and Machine Learning based Framework for Efficient Health Insurance Management
Having a health insurance is important for everybody, bearing in mind the increasing medical costs. Medical emergencies can have a severe financial and emotional impact. However, the current insurance system is very expensive and the claim settlement process is excessively lengthy, making it tedious. This results in policyholders not being able to successfully make a claim with their insurance company. In this paper, we focus on developing a fast and cost-effective framework based on blockchain technology and machine learning for the health insurance industry. Blockchain is capable of removing all third-party organisations by forming a smart contract, making the entire process more smooth, secure, and efficient. The contract settles the claim on documents submitted by the claimant. A ridge regression model is used for computing the premiums optimally, based on the total amount claimed under the current policy tenure, along with several other factors. A random forest classifier is applied for predicting the risk that helps in the computation of risk-rated premium rebate.
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