Insights Gained from Data Mining and Predictive Modeling

Adequate processes for detecting fraud and initiating steps to prevent future fraud is the key to managing this business risk. The overall goal of a fraud detection and prevention program is to protect the organization from the economic, legal and mired reputation that such occurrences can have.

With the downturn in the economy, the frequency of fraud is most likely to increase and monitoring may be lessoned with reduction in staff. With the aid of data mining and predictive modeling techniques, the task of identifying possible fraudulent transactions and the prevention of future instances is much easier.

The tools and models can detection suspicious transactions by analyzing the associated data for anomalies and unusual patterns that may be associated with fraud. The information can then be used by the analyst to verify that fraud did occur and confront the suspected party.

Models Highlighted in this Section

The following pages provide details on three commonly used applications of the data mining and predictive technologies. These pre-built models are shown for illustrative purposes and are not, by any means, the only models we have built in the fraud area. Models detailed are:

• Cash Payments
• Warranty Claims
• Insurance Claims