Sift
Case Studies
How Carousell keeps fraudulent listings off of their platform
Overview
How Carousell keeps fraudulent listings off of their platformSift |
Analytics & Modeling - Machine Learning Application Infrastructure & Middleware - API Integration & Management | |
E-Commerce | |
Business Operation Sales & Marketing | |
Cybersecurity Fraud Detection | |
Data Science Services | |
Operational Impact
Since adopting Sift, Carousell is detecting 23% more fraudulent users and 10.26% more fraudulent listings, has achieved 2x ROI, and is saving over $350,000 a year. They’re successfully keeping fraudsters off-platform, and preventing them from finding ways to come back thanks to the accuracy of their model. Rather than reacting to fraudulent listings only after they’ve been flagged by users, Carousell is preventing them from being posted in the first place. As a result, Carousell has been able to scale without dividing their time with fraud management and doesn’t need to devote a human team to manual review. Workflows are automating decisions and handling the bulk of the fraud prevention, leaving Carousell’s fraud teams to focus on helping the company continue to grow into new markets and provide the best experiences for their buyers and sellers. | |
Quantitative Benefit
Over $350k saved annually | |
2x ROI using Sift | |
23% more fraudulent users detected | |