What type of characteristics does fraud detection typically look for?

Fraud detection primarily focuses on identifying irregular and suspicious transaction behaviors. This is because fraudulent activities often manifest as deviations from expected norms in transaction patterns. For instance, if a customer typically makes small purchases but suddenly tries to make a large and unusual transaction, it may trigger red flags for fraud detection systems. These systems are designed to analyze various aspects of transaction data to pinpoint anomalies that could indicate fraudulent activities, such as unexpected locations, unusual transaction amounts, or sudden changes in spending behavior.

On the other hand, while assessing normal transaction patterns, recognizing customer loyalty signs, and analyzing transaction volume can provide useful context, they are less focused on the identification of fraud. Instead, those methods might be more relevant for understanding customer behavior and improving engagement strategies rather than specifically targeting fraud. This delineation is crucial for maintaining the integrity of financial systems and quickly identifying potential security threats.