Fraud analysts establish baseline profiles for customer behavior, transaction history, and account details to understand typical shopping patterns. To scale efforts, analysts will use intelligent algorithms and sophisticated fraud detection software to monitor transactions in real-time, setting up alerts to flag unusual patterns or deviations from established norms (which may indicate fraudulent activity). Any deviations from baseline patterns trigger further investigation by the analyst.
Here’s an example of how a fraud analyst uses their behavioral expertise to detect an unusual geographic spending pattern:
Suppose a fraud analyst monitors credit card transactions and notices a series of transactions from a single account. Ordinarily, this account has a history of making purchases within a specific geographic region. However, the analyst observes a sudden and significant increase in transactions from a completely different and distant location within a short time frame. The steps the analyst would take are as follows.
- Establish a baseline: The fraud analyst has previously established a baseline for the account’s typical spending behavior, considering factors like location, transaction frequency, and spending habits.
- Anomaly is detected: The sudden surge in transactions from a distant location triggers an anomaly alert. The analyst’s system flags this as unusual behavior compared to the established baseline.
- Investigation begins: The fraud analyst investigates further, considering factors such as the time of day, merchant types, and transaction amounts. They may discover that the transactions are inconsistent with the account holder’s historical behavior.
- Confirmation of anomaly: After thorough investigation, the analyst confirms that the transactions are indeed unusual and do not align with the account’s regular spending patterns.
- Take immediate action: The fraud analyst acts promptly, such as placing a temporary hold on the account, contacting the account holder to verify the transactions, or escalating the case to the appropriate department for further investigation.
In this example, the fraud analyst’s ability to recognize a deviation from the established pattern of geographic spending played a crucial role in identifying potential fraudulent activity. Such pattern recognition helps prevent unauthorized transactions and protects the account holder from financial losses.