Buguroo To Use $11M Funding Round For ML-Driven Fraud Detection

A startup that analyzes banking activity to identify fraudulent behavior has raised $11 million in a Series A funding round, according to a report by VentureBeat.

Buguroo, a Spanish cybersecurity company, uses biometrics tied to behavior and deep learning processes to root out fraud. The funding round was led by Ten Eleven Ventures and Seaya Ventures, which is located in Spain. Conexo Ventures and Inveready Technology Investment Group also participated.

The company was started in 2010 to identify malicious actors who try to impersonate legitimate bank account holders. Their technology is designed to recognize illicit activity that comes from either human cybercriminals or bots.

There are several ways in which malicious actors attempt to access accounts, including web injections, form grabbers and trojan malware. Buguroo said its technology can identify new types of malware on a web browser or mobile app. The system identifies user behavior patterns – like how they scroll on a screen, how fast they type, what they typically click on and how they use a mouse – and then use that information to define a typical session. When someone logs in and deviates from that normal routine, the program identifies and flags the session.

Buguroo looks not only for new account fraud (NAF), but also fraud that is perpetrated when someone gains access to the system using stolen credentials. It continuously gathers information and learns from it, using a practice called “cyberprofiling” to root out bad actors.

According to Buguroo, almost 33 percent of fraud comes from accounts that are supposedly legitimate but are actually controlled by fraudsters. The fraud market is expected to become a $57 billion industry by the year 2025; in 2018, it was worth $17 billion.