Accident Information Based Reliability Estimation Model for Car Insurance Smart Contract


KIPS Transactions on Computer and Communication Systems, Vol. 9, No. 4, pp. 89-100, Apr. 2020
https://doi.org/10.3745/KTCCS.2020.9.4.89,   PDF Download:
Keywords: Blockchain, Reliability Estimation, Regression Analysis, Car Insurance, Smart Contract
Abstract

In order to reduce the time and cost used in insurance processing, studies have been actively carried out to apply blockchain smart contract technology to car insurance. However, by using traffic data that is insufficient to prove accidents, existing studies are being exposed to the risk of insurance fraud, such as forgery and overstated damage by malicious insurers. To solve this problem, we propose an accident data-based reliability estimation model by using both various types of data through sensors, RSUs, and IoT devices embedded in automobiles and smart contracts. In particular, the regression model was applied in consideration of the weight estimation according to the type of traffic accident data and the reliability estimation model trained according to various accident situations. The proposed model is expected to effectively reduce fraud and insurance litigation while providing transparency in the insurance process and streamlining it is well.


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Cite this article
[IEEE Style]
S. Lee, A. Kim and S. Se, "Accident Information Based Reliability Estimation Model for Car Insurance Smart Contract," KIPS Transactions on Computer and Communication Systems, vol. 9, no. 4, pp. 89-100, 2020. DOI: https://doi.org/10.3745/KTCCS.2020.9.4.89.

[ACM Style]
Soojin Lee, Aeyoung Kim, and Seung-Hyun Se. 2020. Accident Information Based Reliability Estimation Model for Car Insurance Smart Contract. KIPS Transactions on Computer and Communication Systems, 9, 4, (2020), 89-100. DOI: https://doi.org/10.3745/KTCCS.2020.9.4.89.