Alexander Widder, Rainer v. Ammon, Gerit Hagemann, Dirk Schönfeld
A new approach to detect fraudulent event patterns in the field of insurance fraud detection by using a combination of discriminant analysis and neural network techniques is presented. The approach is embedded in a Complex Event Processing (CEP) engine. CEP is an emerging technology for detecting known patterns of events and aggregating them as complex events at a higher level of analysis in real-time. In the insurance domain, fraud detection often is a manual task and automatically fraud detection contains an enormous potential for streamlining and saving costs.