Which method is commonly used to identify suspicious transactions?

Transaction pattern analysis is a commonly used method to identify suspicious transactions because it involves the systematic examination of transaction data to identify anomalies or deviations from typical behavior. This method focuses on analyzing the frequency, amount, and volume of transactions over a specific period. By establishing a baseline for what constitutes normal transaction behavior for a customer or a group of customers, analysts can highlight transactions that are unusual or unexpected, thereby raising red flags.

This approach is particularly effective in detecting potential money laundering or fraud activities, which often involve structured patterns that can be identified through data analysis. By leveraging sophisticated algorithms and machine learning techniques, compliance professionals can enhance their ability to spot suspicious activities that may otherwise go unnoticed.

In contrast, the other options like customer feedback forms and yearly financial summaries do not provide the real-time analysis or the detailed transaction-level scrutiny needed to effectively identify suspicious activities. Market trend analysis focuses more on broader economic or industry trends rather than individual transaction behaviors, making it less relevant for identifying specific suspicious transactions.