Neural network/conceptual clustering fraud detection architecture

摘要

The invention relates to an apparatus for detecting fraud using a neural network. The architecture of the system involves first employing a conceptual clustering technique to generate a collection of classes from historical data. Neural networks are provided for each class created by the clustering step and the networks are trained using the same historical data. This apparatus is particularly useful for detecting the incidence of fraudulent activity from very large amounts of data such as tax returns or insurance claims.