Processing method and device and processing equipment for insurance service risk prediction

Abstract

The embodiment of the invention discloses a processing method and device and processing equipment for insurance service risk prediction. According to the method, the gradient boosted decision tree canbe pre-used to construct a risk prediction module, and the risk prediction module can be trained by using marked risk associated data related to an insurance service; when the risk prediction moduletraining reaches prediction requirements, the risk prediction module can be used for online risk prediction, insurance service risk prediction is carried out on a to-be-tested user, and a prediction result is output. The provided method can reasonably effectively use multidimensional nonlinear variables in the insurance service; the risk prediction module based on a nonlinear relationship of the gradient boosted decision tree can have good compatibility of linear and nonlinear variables; compared with a conventional linear module, the accuracy of a prediction result is markedly improved, the deficiency of the conventional linear module is effectively remedied, and the service experience of the insurance service is improved.

Description

technical field [0001] The embodiment scheme of this specification belongs to the technical field of computer data processing for insurance business risk prediction, and in particular relates to a processing method, device and processing equipment for insurance business risk prediction. Background technique [0002] Motor vehicle insurance, namely auto insurance (or auto insurance for short), refers to a commercial insurance that is liable for compensation for personal injury or property loss caused by motor vehicles due to natural disasters or accidents. With the development of the economy, the number of motor vehicles continues to increase. At present, auto insurance has become one of the largest types of insurance in China's property insurance business. [0003] When a user purchases vehicle insurance, the insurance company usually conducts a risk assessment on the user, and the result of the risk assessment will directly affect the insured amount and preferential treatme...

AI Technical Summary

Problems solved by technology

[0004] However, with the continuous increase of auto insurance business, Internet data has shown various types and massive data growth, and the traditional GLM model system has become more and more restricted. The shopping and habits of the crowd are related, and different consumption habits change with their own changes, and the age distribution is affected in a non-linear form.

The GLM model can summarize nonlinear variables by binning, but it will lose the accuracy of many variables, and it is difficult to adapt to the current big data and multi-dimensional risk prediction requirements

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