The pricing model of motor vehicle insurance (hereinafter referred to as auto insurance) includes claim frequency model, claim amount model and cumulative loss model. In practical application, different model combinations need to be selected according to the characteristics of data to determine the rate of auto insurance. Machine learning algorithm is a widely used prediction tool. The objective of the project is to predict the possibility of insurance claims being submitted and the amount to be paid based on a set of variables. Variables include: driver's age, number of accidents, insurance company, vehicle manufacturing, vehicle model, driver's living status, vehicle registration status, year of accident, month of accident, date of accident, time of accident, weather conditions, road conditions and traffic conditions.


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    Title :

    Prediction of Auto Insurance Claim Probability and Cumulative Compensation Based on Machine Learning Algorithm


    Additional title:

    Lect. Notes on Data Eng. and Comms.Technol.


    Contributors:
    Jansen, Bernard J. (editor) / Zhou, Qingyuan (editor) / Ye, Jun (editor) / Xinhua, Wang (author) / Qing, Yan (author) / Lianqin, Jia (author) / GKhongwar, J. A. (author)

    Conference:

    International Conference on Cognitive based Information Processing and Applications ; 2022 ; Changzhou, China September 22, 2022 - September 23, 2022



    Publication date :

    2023-04-09


    Size :

    6 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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