Fraud Detection for SWIFT
A number of high-profile – and high impact – cyber heists have used a bank’s connection to the international SWIFT network to execute large-scale fraudulent transfers.
These heists have been successful because the traditional anti-fraud practices that rely on rules, manual controls or segmentation cannot identify fraudulent transfers over the SWIFT network. What is needed is a new technological model that detects unusual payment transactions before they are executed.
NetGuardians uses Big Data, dynamic profiling, and machine learning to continuously monitor users and SWIFT transaction flows. It analyzes combinations of and correlations between variables from SWIFT and other networks to detect unusual transaction patterns and raises alerts in real-time.
NetGuardians' machine learning risk platform can spot unusal:
Alerts can be investigated or accepted via our dashboard before the transaction is completed. And because machine learning algorithms constantly assimilate new data, the number of false positives is kept to an absolute minimum, reducing the need for large risk management departments and maximizing the use of resources.