Name
Title | ||
|---|---|---|
A Blockchain and Machine Learning based Framework for Efficient Health Insurance Management |
Abstract | ||
|---|---|---|
ABSTRACTHaving 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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3485730.3493685 | Embedded Network Sensor Systems |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adit Goyal | 1 | 3 | 1.40 |
| Anubhav Elhence | 2 | 0 | 0.34 |
| Vinay Chamola | 3 | 0 | 0.34 |
| Biplab Sikdar | 4 | 7 | 6.60 |