ncrease the proportion of fraudulent cases. For example, Ezawa & Norton (1995) increase the percentage of fraudulent calls from 1-2% to 9-12%. However, the use of a non-representative training set can be problematic because it does not provide the data mining method with accurate information about the true class distribution (Weiss and Provost, 2003). Marketing/Customer Profiling Telecommunication companies maintain a great deal of data about their customers. In addition to the general customer data that most businesses collect, telecommunication companies also store call detail records, which precisely describe the calling behavior of each customer. This information can be used to profile the customers and these profiles can then be used for marketing and/or forecasting purposes. Chapter We begin with one of the most well-known and successful marketing campaigns in the telecommunications industry: MCI's Friends and Family promotion. This promotion was initially launched in the United States in 1991 and, although now retired, was responsible for significant growth in MCI's customer base. The promotion offered reduced calling fees when calls are placed to others in one's calling circle. This promotion purportedly originated when market researchers noticed small subgraphs in the call- graph of network activity-which suggested the possibility of adding entire calling circles rather than the costly approach of adding individual subscribers (Han, Altman, Kumar, Mannila & Pregibon, 2002). It is worth noting that MCI relied primarily on its customers to bring in members of their calling circle, even though MCI could have utilized its call detail data to generate a list of the people in each calling circle. The most likely reason for this is that MCI did not want to anger its customers by using highly personal information (calling history). This demonstrates that privacy concerns are an issue for data mining in the telecommunications industry, especially when call detail data is involved. The MCI Friends and Family promo