Classified estimation method and device for vehicle insurance
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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
Inactive Publication Date: 2017-09-26
清华大学苏州汽车研究院(吴江)
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[0005] Therefore, the prior art does not provide an effective method for assessing the level of the user's auto insurance
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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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Abstract
The invention relates to a classified estimation method and device for vehicle insurance and belongs to the technical field of intelligent vehicles. The method comprises the following steps: risk characteristic extraction is performed firstly, risk characteristics of a driver and a driving vehicle are obtained, and then 8-dimensional risk characteristics describing driving behaviors of the driver are defined by combining with vehicle-mounted remote information; then a mathematical model for the risk characteristics and loss is established through logistic regression, model parameters are estimated on the basis of historical data with a maximum likelihood method, and value-at-risk thresholds of different risk ranking groups are determined after the model parameters are obtained; finally, risk characteristics and risk values of a to-be-estimated customer are calculated, and risk ranking is performed according to a risk rank table. According to the method, vehicle risks can be ranked through effective combination of driver information, driving vehicle information and driving behavior characteristics, artificial participation is not needed in the whole process, dependence on personal experience is avoided, and the method is direct, effective and convenient to use.
Description
technical field [0001] Embodiments of the present invention relate to the technical field of smart cars, and in particular to a method and device for classifying and evaluating auto insurance. Background technique [0002] Insurance premium determination is the core link of insurance business. In the auto insurance business, the auto insurance cost is estimated by measuring the policy information, namely: the policyholder and his vehicle information. The cost determination logic of traditional auto insurance is relatively simple. It is generally classified based on static data, mainly including driver-related attributes and vehicle-related attributes, and risk assessment is performed through a fixed formula. However, the existence of these static features has great limitations. First, most of the static features are reported by the policyholder to the insurance company, such as the personal information of the policyholder and the average annual driving mileage. These self-r...
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