Fraud detection is a topic applicable to many industries. Data mining and statistics help to anticipate and quickly detect fraud and take immediate action to minimize costs.
An important early step in fraud detection is to identify factors that can lead to fraud. What specific phenomena typically occur before, during, or after a fraudulent incident? What other characteristics are generally seen with fraud? When these phenomena and characteristics are pinpointed, predicting and detecting fraud becomes a much more manageable task.
In practice, the fraud detection analyses and systems based on data mining and predictive modelling techniques serve as the method for further improving the fraud detection system in place, and their effectiveness will be judged against the default rules created by experts.
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