Case Study: Spanish Bank achieves real-time malware detection and fraud prevention with Buguroo

Using deep learning to detect unknown zero-day banking malware

Spanish Bank, one of Spain’s top three banks with more than 15 million customers, needed a better way to fight increasingly sophisticated online fraud and unknown banking malware such as Dridex. Traditional blacklist-based defenses were no longer enough, so the bank looked for a solution that could detect both known and unknown attacks while also identifying the fraudsters behind them. It chose Buguroo’s behavioral biometrics and malware detection platform, bugFraud.

Buguroo implemented a system that builds unique user profiles from behavioral biometrics, device, and network data, then applies real-time risk scoring and deep learning-based malware classification to spot anomalies and “grey list” previously unseen threats. The bank also used Buguroo’s Fraudster Hunter link-analysis capability to trace infected sessions back to their source. As a result, Spanish Bank reduced fraud risk, detected malware including Dridex, Trickbot, and Dyre, identified fraud rings already operating in the bank, improved customer experience with invisible security checks, and maintained compliance with regulatory requirements.