How Patreon helps creators connect safely
Customer Company Size
Large Corporate
Country
- Worldwide
Product
- Patreon
- Sift
Tech Stack
- Sift Score API
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
Technology Category
- Application Infrastructure & Middleware - API Integration & Management
Applicable Industries
- Software
Applicable Functions
- Business Operation
Use Cases
- Fraud Detection
Services
- System Integration
About The Customer
Patreon is an international platform used by artists ranging from musicians, webcomic artists, and YouTube content creators. It allows creators to obtain funding from their fans or patrons, on a recurring basis (subscription), or per work of art on a one-time basis. Patreon can be accessed on mobile apps (Android, iOS, regular mobile) as well as desktop. Through their wide reach, Patreon helps artists and creators to successfully make a living off of their work and to provide an exemplary experience to their users.
The Challenge
Patreon’s work connecting fans with creators poses unique challenges, particularly around content, account, and payment fraud. Because their platform relies on the instantaneous transfer of funds – unlike in a traditional e-commerce model where a purchased good can be held while cardholder identity is verified – it is imperative to prevent payment fraud before it occurs. Payment fraud for Patreon comes in the form of either money laundering or traditional credit card fraud – and almost always, there are stolen credit card credentials at play. As their global reach grew, chargebacks and their resulting fees began to rise as well. In addition, manual review of listings and shared content was not keeping up with the rapidly expanding platform community. Patreon, a young and agile company with no fraud prevention measures in place, needed a content abuse and fraud solution that could scale with the business and would ensure the user experience remained seamless.
The Solution
Patreon hired Maritza Dominguez for her experience in building, scaling, and managing a smart in-house fraud team. Having worked with Sift in the past – and having had great success automating on Sift Score accuracy and easy feature analysis – Maritza decided to try out the solution for Patreon’s unique business. Within just a few days of implementing Sift, Patreon had a fully customized model to best suit their needs. Utilizing Sift’s Score API, they were able to automate portions of their fraud management system and to block risky content, users, and transactions over a certain score threshold; they use the Sift Score to easily view a user’s riskiness level. When Maritza needs to dive deeper, she investigates signals in the Sift Console, exploring key data points like user behavior, network visualizations of connected accounts, and important addresses linked to the user.
Operational Impact
Quantitative Benefit
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