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Enterprise Fraud Management

Enterprise Fraud Management

(also EFM)

Enterprise Fraud Management definition

Enterprise Fraud Management is a system or set of processes for detecting and preventing fraudulent operations. It aims to safeguard an organization’s assets, customers, and reputation from fraud.

See also: anti-fraud system, initial fraud alert, wire fraud

Here’s a breakdown:

  • 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.

Further reading

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