Fraud Detection refers to the sophisticated methods and advanced systems employed by payment processors, banks, and other financial institutions to identify, prevent, and mitigate fraudulent transactions.
This process often involves the use of machine learning algorithms and artificial intelligence (AI). These advanced technologies are capable of learning from past data, identifying patterns and trends, and making predictions about future behavior. They can also leverage real-time analytics to provide immediate insights into potentially fraudulent activity.
Additionally, rules-based systems, which use predefined rules to identify suspicious activity, continue to play a crucial role in fraud detection. By analyzing patterns of behavior and cross-referencing these against known fraud indicators, these systems can identify anomalies or unusual transactions that may signify fraud.
As fraudsters continually evolve their tactics, the field of fraud detection remains a critical and ever-evolving component of financial services.