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Overview
Sift is a fraud prevention platform using machine learning across payments, account access, and content, informed by signals from a large customer network.
It covers payment fraud scoring, account-takeover detection, spam and content abuse, and chargeback representment. Scores are returned in real time and can trigger automated decisions or route to manual review. Because decisions are model-driven, individual outcomes are less directly explainable than rule-based systems.
Common use cases
- Score payment transactions for fraud in real time
- Detect account takeover attempts at login
- Block spam and abusive content submissions
- Automate decisions with a manual review fallback
Key Features
- Machine-learning scoring across the full user journey
- Payment fraud, account takeover, and content abuse
- Global data network improving model signal
- Automated decisioning with review workflows
- Chargeback representment support
- Real-time API scoring
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