Sift Case Studies Keeping fraudulent ticket buyers off the platform

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	Keeping fraudulent ticket buyers off the platform Sift

Keeping fraudulent ticket buyers off the platform

Sift

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics
Applicable Functions	Sales & Marketing
Use Cases	Fraud Detection
Services	Data Science Services
Challenge	Etix, the largest independent ticketing company in North America, was facing a growing problem of fraudulent transactions as their online and mobile business scaled. These fraudulent transactions resulted in chargebacks, costing the company money and the invaluable time of fraud analysts who had to respond to fraud attempts. The challenge of discovering fraud through manual review was daunting and unsustainable. Chargebacks often were not reported until after events, making it even more difficult to track and prevent fraud. Etix needed a solution that could respond in real time to potential fraud and prevent fraudulent orders before they were processed. Read More
About Customer	Etix is the largest independent ticketing company in North America, with headquarters in the U.S. and offices in Europe and Asia. The company sees millions of unique users visit their website and mobile app every month, selling 50 million tickets per year via their ticketing platform. Etix aims to ensure a flexible, secure, and premium pre-event experience for their partners and customers. Their suite of products extends beyond online ticket sales to include marketing solutions, ads, and analytics, providing venues and promoters with a full arsenal of tools to make every event premium. Founded in 2000, Etix has grown significantly and continues to innovate in the ticketing industry. Read More
Solution	Etix decided to implement Sift’s fraud prevention solution after exploring its intuitive interface and easy-to-understand pricing plans. The solution was fully implemented and running in three weeks by a single engineer. Sift's 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. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Applicable Functions

Sales & Marketing

Use Cases

Fraud Detection

Services

Data Science Services

Challenge

Etix, the largest independent ticketing company in North America, was facing a growing problem of fraudulent transactions as their online and mobile business scaled. These fraudulent transactions resulted in chargebacks, costing the company money and the invaluable time of fraud analysts who had to respond to fraud attempts. The challenge of discovering fraud through manual review was daunting and unsustainable. Chargebacks often were not reported until after events, making it even more difficult to track and prevent fraud. Etix needed a solution that could respond in real time to potential fraud and prevent fraudulent orders before they were processed.

About Customer

Etix is the largest independent ticketing company in North America, with headquarters in the U.S. and offices in Europe and Asia. The company sees millions of unique users visit their website and mobile app every month, selling 50 million tickets per year via their ticketing platform. Etix aims to ensure a flexible, secure, and premium pre-event experience for their partners and customers. Their suite of products extends beyond online ticket sales to include marketing solutions, ads, and analytics, providing venues and promoters with a full arsenal of tools to make every event premium. Founded in 2000, Etix has grown significantly and continues to innovate in the ticketing industry.

Solution

Etix decided to implement Sift’s fraud prevention solution after exploring its intuitive interface and easy-to-understand pricing plans. The solution was fully implemented and running in three weeks by a single engineer. Sift's 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.

Impact #1	Etix was able to identify and block $15,000 worth of risky orders in the first week of their trial period with Sift.
Impact #2	Through automation, Etix is able to focus on only the truly suspicious users and orders, instead of expending analyst hours on manual review of false positives.
Impact #3	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.

Impact #1

Etix was able to identify and block $15,000 worth of risky orders in the first week of their trial period with Sift.

Impact #2

Through automation, Etix is able to focus on only the truly suspicious users and orders, instead of expending analyst hours on manual review of false positives.

Impact #3

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.

Benefit #1	$15,000 in fraud prevented in the first week
Benefit #2	75% reduction in manual review

Benefit #1

$15,000 in fraud prevented in the first week

Benefit #2

75% reduction in manual review

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Overview

Keeping fraudulent ticket buyers off the platform

Operational Impact

Quantitative Benefit