Targeting customers via discovery knowledge for the insurance industry

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. q 2005 Elsevier Ltd. All rights reserved.