研究生: |
吳自晟 Tzu-Cheng Wu |
---|---|
論文名稱: |
應用資料探勘技術於保險業顧客關係管理之研究 The Research of Data Mining Techniques applied to Insurance CRM |
指導教授: |
楊文鐸
Wen-Dwo Yang |
口試委員: |
周碩彥
Shuo-Yan Chou 張聖麟 Sheng-lin Chang |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 工業管理系 Department of Industrial Management |
論文出版年: | 2007 |
畢業學年度: | 95 |
語文別: | 中文 |
論文頁數: | 65 |
中文關鍵詞: | 基因演算法 、自我組織映射圖 、K-means 、顧客區隔 |
外文關鍵詞: | Genetic Algorithm(GA)、Self Organizing Map(SOM)?>< |
相關次數: | 點閱:322 下載:2 |
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隨著壽險保單不斷推陳出新,以及顧客的需求不斷改變,保單的目的不再只是單純的銷售,更重要的是能與顧客建立長遠的穩固關係,以獲得顧客終身價值。壽險業的經營方式多利用業務員之人際網絡開發新顧客,若業者能善用既有的資料,從其中挖掘出既有顧客之潛在需求,找出業務員基本資料與客戶保單資料間的關連性,以便於供以後保險業者在訂定經營策略或推出新商品時,能有一個參考的方向,使業者能夠即時掌握客戶的動態。
本文採用資料探勘中的群集分析法,針對保險業務員資料與客戶保單資料做一適當之分群,並希望從中獲取業務員特質與招攬客戶之間關係之資訊。本研究先利用基因演算法(GA)挑選屬性,並結合資料探勘分群工具K-means與類神經網路中自我組織映射圖網路(SOM)作客戶區隔,試圖從分群的資料中擷取一些有用的資訊,以提供壽險公司市場區隔、經營策略參考,藉以提升客戶服務的品質,提高企業的競爭能力。
Along with the new ideas and renovations put forth continuously in insurance policies , and the ever-changing needs of the clients, insurance policies have become more than just simple deals of sales. More importantly, one needs to establish a long –term , stable relationship with the clients as it leads to the foundation of a lifetime value.
Insurance industry often utilizes the interpersonal connections of the brokers to exploit new clients. Should the insurers were able to make use of the provided information , from which explores the potential needs of the customers and furthermore finds the correlation between the broker’s basic information and client’s policy type , it world be of great help to the insurance company in instituting operation schemes and developing new products as it provides a reference resource and enables the insurers to understand the latest customer demands.
In this article , clustering of data mining is selected as the method to categorise the insurance broker’s information and client policy content in order to analyse the relationship between broker characteristics and client recruitment. Genetic algorithm (GA) is adopted in attribute selection in this research , combining data mining tool, K-means, and SOM of ANN, to perform customer partitioning. Thereby attempt to gather useful data for insurance companies in the application of market categorization and administration strategy references, hence to improve service quality and company competivity.
一、 中文部份
1. 林傑斌、張一岑、張太平著(2004),「資料倉儲與資料採擷」,台北縣:博碩文化。
2. 李珮榕(2002),以資料採礦技術分析大台北地區保單貸款,國立政治大學,統計研究所,碩士論文。
3. 呂廣盛(2002),「個人壽險核保概論」第五版,台北市:三民書局。
4. 柳靜慧(2003),顧客流失預警模型之研究─以電信產業為例,私立輔仁大學,資訊管理學系,碩士論文。
5. 涂靜儀(2001),結合自組織映射圖類神經網路與基因演算法建構壽險業顧客關係管理之知識採擷模式,國立高雄第一科技大學,風險管理與保險研究所,碩士論文。
6. 陳佳鈴(2003),應用資料探勘於客戶關係管理之分群研究─以壽險業為例,中華大學,科技管理研究所,碩士論文。
7. 郭良芬(2005),Data Mining在人身保險業保戶特性之分析應用,私立輔仁大學,應用統計學研究所,碩士論文。
8. 陳雲中(1991),「人壽保險的理論與實務」第八版,台北巿:三民書局。
9. 黃志雄(2002),應用資料採礦分析線上拍賣市場之模式,私立朝陽科技大學,工業工程與管理系,碩士論文。
10. 黃渝誠(2002),SOM 應用於知識發掘之研究-以銀行住宅抵押貸款風險聚類為例,國立高雄第一科技大學,風險管理與保險研究所,碩士論文。
11. 葉怡成(2002),「類神經網路模式應用與實作」第七版,台北市:儒林圖書有限公司。
12. 曾龍譯(2003),「資料探勘-概念與技術」初版,台北縣:維科圖書。譯自Jiawei Han& Micheline Kamber(2003)”Data Mining,Concepts and Techniques.”
13. 楊世瑩(2005),「SPSS統計分析實務」第四版,台北市:旗標出版社。
14. 蔡瑞煌(1995),「類神經網路概論」,台北巿:三民書局。
二、 英文部分
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19. Kohonen, T. (1990) "The self-organizing,map, "Proc. IEEE, 78(9), 1480-1481.
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24. Pena J. M., Lozano J. A., Larranaga P., and Inza I.(2001), “Dimensionality Reduction In Unsupervised Learning Of Conditional Gaussian Networks”, IEEE Transactions on Pattern Analysis and Machine Intelligence 23: 6, pp.590-603.
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26. WEKA,http://www.cs.waikato.ac.nz/ml/weka