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How Etix keeps fraudulent ticket buyers off the platform

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Moving tickets worldwide

With their headquarters in the U.S. and offices in Europe and Asia, Etix sees millions of unique users visit their website and mobile app every month. They sell 50 million tickets per year via their ticketing platform, with the goal of ensuring a flexible, secure, and premium pre-event experience for their partners and customers. Their suite of products goes beyond online ticket sales, extending to marketing solutions, ads, and analytics to ensure that venues and promoters have a full arsenal of tools to make every event premium. Founded in 2000, Etix is the largest independent ticketing company in North America.


Fraud rings and costly chargebacks

Etix‚Äôs daily visitors number in the tens of thousands, and that number is ever-growing as entertainment seekers gravitate toward the convenience of buying tickets online. However, as their online and mobile business has scaled, attention from brokers and fraudsters has grown. For Etix, these fraudulent transactions result in chargebacks, which cost everyone money and‚ÄĒperhaps more importantly‚ÄĒthe invaluable time of fraud analysts who must work to respond to fraud attempts.

With chargebacks often not being reported until after events, the challenge of discovering fraud through manual review was daunting. Eventually, manually reviewing suspicious orders couldn‚Äôt be maintained. As Etix struggled to balance a premium, frictionless customer ticketing experience with the growing threat of fraudulent activity‚ÄĒthey decided it was time to explore preventative, adaptable solutions.


Easy integration and scalable review processes

To stay ahead of their growing fraud problem, the Etix fraud team sought out a pre-order defense strategy that could respond in real time to potential fraud. Etix decided to implement Sift‚Äôs solution after exploring the intuitive interface and easy-to-understand pricing plans. Working closely with the Sift team‚ÄĒand, in the process, discovering parallel company cultures that allowed for easy communication and rapid support‚ÄĒmade for a quick integration.

A single engineer got the Sift solution fully implemented and running in three weeks. Utilizing the machine learning solution allowed Etix to keep up with their order volume, while the global model’s predictive analytics provided insights to prevent fraudulent orders before they were processed. Leveraging the data of all of Sift’s users empowered the Etix team to block bad users and orders, significantly reducing the volume of orders in their review queues. The Etix team can now automate on Sift Scores, making for a more efficient review process.

Because identifying and acting on suspicious orders saves our clients money, having the auto-reject rules in place saves us a tremendous amount of time, since we no longer have to manually cross-reference suspicious orders to identify fraudulent networks.

Krister Larsson, Director of Intl. Operations


Spotting the good, blocking the bad

Etix found that Sift was accurate right off the bat, and that the fraud true positive rate has continued to improve. In the very first week of their trial period, Etix was able to use Sift to identify and block $15,000 worth of risky orders. Through automation, Etix is also able to focus on only the truly suspicious users and orders, instead of expending analyst hours on manual review of false positives.

Perhaps most invaluably, Etix is better able to quickly identify not only fraudsters and their connected accounts, but also spot and smooth the way for their legitimate ticket buyers. A better user experience for true fans while auto-blocking the bad means that Etix is prepared to continue growing and innovating long into the future.

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