Case Study: Carousell prevents fraudulent listings and saves $350K+ annually with Sift

How Carousell keeps fraudulent listings off of their platform

Carousell is a Singapore-based peer-to-peer marketplace operating across Southeast Asia and Australia with millions of listings and transactions. As it scaled, the platform struggled with phony and spammy listings, repeat fraudsters who kept returning under new accounts, and a rules-based fraud system that was slow, reactive, and hard to maintain across markets.

Carousell implemented Sift’s Content Integrity—using machine-learning risk scores and automated Workflows to block high-risk users, merge duplicate accounts, and hide flagged listings pending review—supplemented by hands-on support from Sift engineers. The change delivered faster, proactive prevention: 23% more fraudulent users and about 10.3% more fraudulent listings detected, over $350K saved annually, and a 2x ROI while reducing manual review and enabling continued growth.

Carousell

Tan Su Lin

Vice President