Fraud is increasing dramatically with the expansion of modern technology
and the global superhighways of communication, resulting in the loss of
billions of dollars worldwide each year. Although prevention
technologies are the best way to reduce fraud, fraudsters are adaptive
and, given time, will usually find ways to circumvent such measures.
Methodologies for the detection of fraud are essential if we are to
catch fraudsters once fraud prevention has failed. Statistics and
machine learning provide effective technologies for fraud detection and
have been applied successfully to detect activities such as money
laundering, e-commerce credit card fraud, telecommunications fraud and
computer intrusion, to name but a few. We describe the tools available
for statistical fraud detection and the areas in which fraud detection
technologies are most used.