Targeting customers via discovery knowledge for the insurance industry

Authors:
Chien-Hsing Wu;Shu-Chen Kao;Yann-Yean Su;Chuan-Chun Wu
Affiliations:
Department of Information Management, National University of Kaohsiung, Kaohsiung 811, Taiwan, ROC;Department of Information Management, Kun Shan University of Technology, Tainan 700, Taiwan, ROC;Department of Information Management and Communication, Wenzao Ursuline College of Languages, Kaohsiung, Taiwan, ROC;Department of Information Management, I-Shou University, Kaohsiung 840, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2005

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Abstract

In this paper, the knowledge discovery in databases and data mining (KDD/DM), one of the data-based decision support technologies, is applied to help in targeting customers for the insurance industry. In most KDD/DM application cases, major tasks are required, including data preparation, data preprocessing, data mining, interpretation, application and evaluation. A case study is presented that KDD/DM is utilized to explore decision rules for a leading insurance company. The decision rules can be used to investigate the potential customers for an existing or new insurance product. The research firstly constructed the application framework, then defined and conducted each task required, and finally obtained feedback from the case company. Discussions and implications with respect to this research are presented also.