Insurance fraud detection method and system

Abstract

The embodiment of the invention discloses an insurance fraud detection method and system. The detection method comprises the following steps: constructing a database according to preset data; establishing a corresponding risk rule engine base according to the preset risk rule and the database; receiving self-defined rule information set by a user, establishing a corresponding self-defined rule engine base; receiving suspicious case data uploaded by the user, and performing hiding processing on the case data, and feedbacking an uploading result to the user; performing rule operation on the processed case data, and feedbacking the operated risk level result and the corresponding case risk analysis report to the user. Through the detection method disclosed by the embodiment of the invention,the corresponding case data is operated by constructing the risk rule engine base and the self-defined rule engine base so as to obtain the risk level result and the risk analysis report of the case,the problems of high auto insurance claim settlement risk, high anti-fraud cost and low efficiency are solved, and then a technical effect of replacing the artificial investigation with the bit data distributed computing analysis is achieved.

Description

technical field [0001] The invention relates to the technical field of big data distributed computing analysis, in particular to an insurance fraud detection method and system. Background technique [0002] In the era of Internet +, the traditional auto insurance survey and claims operation has basically realized the Internet transformation, and the operation timeliness and user experience have been greatly improved. The Internet has stimulated the rapid development of the auto insurance market. However, scale is not the decisive factor for underwriting profits. Operating efficiency and risk selection ability comprehensively determine whether it is a loss or a profit. In 2016, an average loss rate of 58% caused 80% of insurance companies to lose money in the field of auto insurance. The high loss rate was mainly due to lax control of underwriting, risk loopholes in the loss assessment process, and weak risk identification capabilities. [0003] Most of the existing insuranc...

AI Technical Summary

Problems solved by technology

In 2016, the average loss rate of 58% caused 80% of insurance companies to lose money in the field of auto insurance. The reasons for the high loss rate are mainly due to the lax control of underwriting, risk loopholes in the loss assessment process, and weak risk identification capabilities

[0004] 1) The audit volume of the case is large, the audit work is difficult, and the audit efficiency is low, resulting in an asymmetry between cost input and output;

[0005] 2) Relying on personal experience, the audit investigation threshold is high, and the human judgment is greatly different from the facts, and there are many misjudgments and missed judgments;

[0006] 3) It can only be analyzed based on the surface of the data, and the depth and dimension of the analysis are insufficient;

[0007] 4) There are obstacles in the sharing of data information among various insurance companies, which makes data analysis unable to accurately locate risks

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