Case Study: a leading airline company prevents ticket reservation fraud with DataVisor UML

Leading Airline Company - Customer Case Study

A leading airline company faced significant challenges from ticket reservation fraud, where scammers exploited its 30-minute payment window to block seats on high-demand flights. This abuse reduced ticket availability for genuine customers and caused financial losses from unconfirmed bookings. To combat this, the airline partnered with DataVisor and its Unsupervised Machine Learning (UML) service to detect and prevent this coordinated fraud in real time.

DataVisor’s UML solution analyzed patterns across reservations to identify sophisticated fraud rings, including the use of specific third-party payment options, high-frequency orders, and scripted email generation. This real-time detection enabled the airline to immediately reject fraudulent bookings. As a result, DataVisor helped prevent over 2 million fraudulent reservations with a 98.6% precision rate, reducing the held-seat rate from over 40% to a manageable 10% and safeguarding approximately $300 million in ticket value.