Labeling Customers Using Discovered Knowledge Case Study: Automobile Insurance Industry

In this paper, we used the knowledge discovery in databases and data mining, one of the data-based decision support techniques to help labeling customers in the automobile insurance industry. In most data mining application cases, major tasks including data preparation, data preprocessing, data transformation, data mining, interpretation, application and evaluation, are required. The results of a case study are presented that knowledge discovery of databases and data mining is used to explore decision rules for an automobile insurance company. The decision rules can be used to label the customers as “bad” or “good” for insurance policies