International Journal of Data Science and Analysis

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

Received: 08 November 2017    Accepted: 04 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.

DOI 10.11648/j.ijdsa.20180401.11
Published in International Journal of Data Science and Analysis (Volume 4, Issue 1, February 2018)
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), 2024. Published by Science Publishing Group

Keywords

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

References
[1] Liu Yunbo. Evolution: from supply and demand chain to the ecology, http: //www.e-prot.cn/gmxx/itzx/352.thm.
[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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[12] Zhang Liangjun, XieJiabiao, Yang Tan, Xiao Gang. R and Data Mining [M]. Beijing: Mechanical Press, 2016.
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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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  • 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://download.sciencepg.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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    AU  - Han Song
    AU  - Han Qiuhong
    Y1  - 2018/01/15
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    JO  - International Journal of Data Science and Analysis
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    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.
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