Case Study: Zoosk achieves streamlined fraud management and improved user experience with Sift

How Zoosk keeps its community safe while improving user experience

Zoosk is a global online dating leader with 35 million members that uses Behavioral Matchmaking to connect singles across 80+ countries. As the service and payments features grew, Zoosk faced rising payments and friendly-fraud challenges that their in-house tools couldn’t scale or adapt in real time, threatening user experience and revenue.

Zoosk integrated Sift’s real-time machine-learning solution and Sift Score API into its existing fraud-management workflow, giving analysts constantly updated intelligence and unified tools. The result was a streamlined review process, faster and more accurate decisions to block or investigate bad actors, and an improved, more frictionless experience for legitimate members.

Zoosk

Tal Yeshanov

Payments & Risk Manager