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http://dx.doi.org/10.22156/CS4SMB.2021.11.06.270

A Study on the Blockchain-Based Insurance Fraud Prediction Model Using Machine Learning  

Lee, YongJoo (Division of Software, Chungbuk National University)
Publication Information
Journal of Convergence for Information Technology / v.11, no.6, 2021 , pp. 270-281 More about this Journal
Abstract
With the development of information technology, the size of insurance fraud is increasing rapidly every year, and the method is being organized and advanced in conspiracy. Although various forms of prediction models are being studied to predict and detect this, insurance-related information is highly sensitive, which poses a high risk of sharing and access and has many legal or technical constraints. In this paper, we propose a machine learning insurance fraud prediction model based on blockchain, one of the most popular technologies with the recent advent of the Fourth Industrial Revolution. We utilize blockchain technology to realize a safe and trusted insurance information sharing system, apply the theory of social relationship analysis for more efficient and accurate fraud prediction, and propose machine learning fraud prediction patterns in four stages. Claims with high probability of fraud have the effect of being detected at a higher prediction rate at an earlier stage, and claims with low probability are applied differentially for post-reference management. The core mechanism of the proposed model has been verified by constructing an Ethereum local network, requiring more sophisticated performance evaluations in the future.
Keywords
Blockchain; Machine Learning; Insurance Fraud; Ethereum; Supervised Learning;
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