| Peer-Reviewed

Application of Data Mining Technology in the Loss of Customers in Automobile Insurance Enterprises

Received: 8 November 2017     Accepted: 4 December 2017     Published: 15 January 2018
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Abstract

This paper is based on the customer churn data of auto insurance, construction of index system in three aspects: the customer information, the subject matter of the insurance information and hold product information; This paper uses decision tree and Logistic regression model to analyze the insurance company's customer data; The results show that: discount, total discount rate, total premium and other variables have a significant impact on customer churn, and get the loss probability of each customer and get some main features of lost customers.

Published in International Journal of Data Science and Analysis (Volume 4, Issue 1)
DOI 10.11648/j.ijdsa.20180401.11
Page(s) 1-5
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Customer Churn, Decision Tree, Logistic Regression, Auto Insurance Company

References
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[2] LOUIS A C. Data mining and causal modeling of customer [J]. Telecommunication Systems, 2002, 21 (2): 103-112.
[3] YANG Zi-jiang, WANG Ye, MA Tian-yi .Analysis of the Factors Affecting the Reinsurance Rate of Auto Insurance [J]. Business Research, 2011, 107.
[4] Liang Wuchao, Wang Ying, Wang Shuxia. Research on Win - win Strategy of Customer Missing Based on Fuzzy Analytic Hierarchy Process [J]. Management Manager, 2017.
[5] ZHU Zhi-yong, XU Chang-mei, HU Chen-gang. Analysis of Customer Churn Based on Bayesian Networks [J]. Journal of Computer Engineering and Design, 2013,35 (3): 155-158.
[6] Ding Junmei, Liu Guicheng, Li Hui. Application of Improved Stochastic Forest Algorithm in Prediction of Customer Missing in Telecommunication Industry [J]. Research and Application. 2015.
[7] Gui Xiancai, Peng Hong, Wang Xiaohua. Analysis of insurance customers churn based on decision tree [J]. Computer Engineering and Design.2005.
[8] Tian Chong. Data mining technology in China's automobile insurance industry research [D]. Hubei: Wuhan University of Technology master's degree thesis, 2007.
[9] Zheng Yuchen, Lv Wangyong. Early warning analysis of loss of securities firms based on Logistic model [J]. Journal of Zhengzhou Institute of Aeronautical Industry Management. 2016,34 (5): 80-88.
[10] Wang Jichuan, Guo Zhigang. Logistic Regression Model-Methods and Applications [M]. Higher Education Press.
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  • APA Style

    Han Song, Han Qiuhong. (2018). Application of Data Mining Technology in the Loss of Customers in Automobile Insurance Enterprises. International Journal of Data Science and Analysis, 4(1), 1-5. https://doi.org/10.11648/j.ijdsa.20180401.11

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    ACS Style

    Han Song; Han Qiuhong. Application of Data Mining Technology in the Loss of Customers in Automobile Insurance Enterprises. Int. J. Data Sci. Anal. 2018, 4(1), 1-5. doi: 10.11648/j.ijdsa.20180401.11

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    AMA Style

    Han Song, Han Qiuhong. Application of Data Mining Technology in the Loss of Customers in Automobile Insurance Enterprises. Int J Data Sci Anal. 2018;4(1):1-5. doi: 10.11648/j.ijdsa.20180401.11

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  • @article{10.11648/j.ijdsa.20180401.11,
      author = {Han Song and Han Qiuhong},
      title = {Application of Data Mining Technology in the Loss of Customers in Automobile Insurance Enterprises},
      journal = {International Journal of Data Science and Analysis},
      volume = {4},
      number = {1},
      pages = {1-5},
      doi = {10.11648/j.ijdsa.20180401.11},
      url = {https://doi.org/10.11648/j.ijdsa.20180401.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20180401.11},
      abstract = {This paper is based on the customer churn data of auto insurance, construction of index system in three aspects: the customer information, the subject matter of the insurance information and hold product information; This paper uses decision tree and Logistic regression model to analyze the insurance company's customer data; The results show that: discount, total discount rate, total premium and other variables have a significant impact on customer churn, and get the loss probability of each customer and get some main features of lost customers.},
     year = {2018}
    }
    

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    T1  - Application of Data Mining Technology in the Loss of Customers in Automobile Insurance Enterprises
    AU  - Han Song
    AU  - Han Qiuhong
    Y1  - 2018/01/15
    PY  - 2018
    N1  - https://doi.org/10.11648/j.ijdsa.20180401.11
    DO  - 10.11648/j.ijdsa.20180401.11
    T2  - International Journal of Data Science and Analysis
    JF  - International Journal of Data Science and Analysis
    JO  - International Journal of Data Science and Analysis
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    PB  - Science Publishing Group
    SN  - 2575-1891
    UR  - https://doi.org/10.11648/j.ijdsa.20180401.11
    AB  - This paper is based on the customer churn data of auto insurance, construction of index system in three aspects: the customer information, the subject matter of the insurance information and hold product information; This paper uses decision tree and Logistic regression model to analyze the insurance company's customer data; The results show that: discount, total discount rate, total premium and other variables have a significant impact on customer churn, and get the loss probability of each customer and get some main features of lost customers.
    VL  - 4
    IS  - 1
    ER  - 

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Author Information
  • Department of Statistics, Beijing Wuzi University, Beijing, China

  • Department of Statistics, Beijing Wuzi University, Beijing, China

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