Case Study: GetMyBoat achieves 30% higher chargeback win rate and reduced fraud losses with Sift

How GetMyBoat fought chargebacks and coordinated fraud rings

GetMyBoat, the world’s largest boat rental and water-experience marketplace with over 140,000 listings across 184 countries, was facing a rising tide of fraud: coordinated fraud rings testing small transactions to find vulnerabilities, a spike in chargebacks (including friendly fraud), and seasonal hotspots that strained resources and threatened revenue. The marketplace needed a way to stop bad actors, reduce dispute losses, and protect customer trust without slowing growth.

By implementing Sift’s global data network and real-time machine-learning scoring, GetMyBoat began cross-referencing IPs, device fingerprints, phone numbers and other signals to pinpoint high-risk accounts and require identity proof when needed, catching fake IDs and shutting down fraudsters before losses occurred. The results included a 30% increase in chargeback win rate, fewer chargebacks and revenue loss, reduced manual review workload, improved operational efficiency, and stronger momentum for company growth.

GetMyBoat

Darrell Diljohn

Director of Customer Service