Case Study: Global Payments Company prevents coordinated BIN fraud with DataVisor's Unsupervised Machine Learning

Transaction Fraud Case Study 1 Detecting a Coordinated BIN Attack for a Global Payments Platform

The Global Payments Company, a provider of corporate card and expense management tools, faced a sophisticated, large-scale coordinated BIN attack from fraudsters. This evolving threat, which involved high-frequency transactions across multiple cards and merchants, was designed to bypass traditional fraud detection methods. To combat this, the company turned to DataVisor and its Unsupervised Machine Learning (UML) solution.

DataVisor's UML solution analyzed transactions holistically in real time, clustering them to reveal hidden links and patterns indicative of a fraud ring. This approach identified over 200 fraudulent transactions, preventing more than $700,000 in losses that would have been missed by traditional systems. The solution provided the client with the ability to visualize and shut down the entire coordinated attack immediately, showcasing DataVisor's effective and proactive defense.