A common use of machine learning in fraud detection is to identify unusual transaction patterns that may indicate fraudulent activity. By analyzing historical data, machine learning algorithms can learn what constitutes normal behavior and flag anomalies for further investigation. This proactive approach enhances security measures and protects organizations from financial losses associated with fraud.