Enterprise Fraud Management (EFM) definition
Enterprise Fraud Management (EFM) is a system for detecting and preventing fraud to protect an organization's assets, customers, and reputation.
See also: anti-fraud system, initial fraud alert, wire fraud
EFM explained: From monitoring to case management
- Monitoring. EFM constantly checks transactions on online platforms, point-of-sale systems, or ATMs.
- Detection algorithms. EFM uses algorithms to identify unusual or suspicious behaviors. These include sudden large transactions, rapid multiple transactions, and other suspicious patterns.
- Real-time analysis. Advanced EFM systems analyze transactions in real-time spotting potential fraud as it occurs.
- Alerts & automation. When suspicious activity is detected, the system generates alerts for human review. EFM can also automatically block transactions based on predefined criteria.
- Data analytics & machine learning. EFM systems often use data analytics to study transaction patterns. Machine learning allows the system to “learn” from past fraud incidents, to detect them better in the future.
- Integration. EFM systems integrate with other organizational tools, pulling data from various sources to get a holistic view of activities.
- Case Management: Post-detection, EFM tools assist in documenting, investigating, and resolving fraud cases.
- In essence, EFM is a technical toolset that helps businesses identify and combat fraud, leveraging algorithms, data analytics, and automation.
