Fraud is the deliberate use of deception to conduct illicit activities. Automatic fraud detection involves scanning large volumes of data to uncover patterns of fraudulent usage, and as such it is well suited to data mining techniques. We present three general types of fraud that have been addressed in data mining research, and we summarize the approaches taken. We also discuss general characteristics of fraud detection problems that make them difficult, as well as system integration issues for automatic fraud detection systems.
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