Classified estimation method and device for vehicle insurance
A technology of auto insurance and evaluation model, applied in the fields of instrument, finance, data processing, etc., can solve the problem of not providing auto insurance level assessment, achieve the effect of effective risk level and avoid evaluation errors
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no. 1 example
[0024] This embodiment provides a technical solution of the car insurance classification evaluation method. see figure 1 , in this technical solution, the car insurance grading evaluation method includes: S11, using policy information and vehicle remote information as data sources, extracting risk characteristic information of car insurance; S12, establishing an evaluation model about the probability of accident, and using the maximum likelihood estimation method Estimate the parameters in the evaluation model; S13, use the risk feature information as the input of the evaluation model to evaluate the user's auto insurance rating.
[0025] Specifically, see figure 1 , the car insurance classification evaluation methods include:
[0026] 1) Risk feature extraction, the factors that reflect the risk of the car are called risk features, where the risk features include driver features, vehicle features, and driving behavior features.
[0027] 1-1) Extract driver features. Drive...
no. 2 example
[0074] This embodiment provides a technical solution of a vehicle insurance classification evaluation device. see figure 2 , the auto insurance rating evaluation device includes: a feature extraction module 21 , a model building module 22 , and an evaluation module 23 .
[0075] The feature extraction module 21 is used to extract the risk feature information of auto insurance by using the policy information and vehicle remote information as data sources, wherein the risk feature information includes: driver feature information, vehicle feature information, and driving behavior feature information.
[0076] The model establishment module 22 is used to establish an evaluation model about the probability of accident, and estimate the parameters in the evaluation model according to the maximum likelihood estimation method.
[0077] The evaluation module 23 is used to evaluate the user's auto insurance rating by using the risk characteristic information as the input of the evalua...
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