Sift
Sift is an AI-powered digital risk decisioning platform that helps businesses detect and prevent payment fraud, account takeover, and fake account creation. It leverages a global data network of over 1 trillion annual events to provide real-time risk scores and automated decisioning.
Where Sift ranks
Current edition · updated Oct 20, 2026About Sift
Sift is the leader in Digital Trust & Safety, empowering digital disruptors to Fortune 500 companies to unlock new revenue without risk. Sift dynamically prevents fraud and abuse through industry-leading technology and expertise, an unrivaled global data network of 70 billion events per month, and a commitment to long-term customer partnerships. Global brands such as DoorDash, Twitter, and Wayfair rely on Sift to gain a competitive advantage in their markets.
Products
Detects and prevents fraudulent transactions in real-time, manages organizational risk, and automates payment reviews to approve more legitimate orders.
Proactively detects and blocks account takeover (ATO) attacks using behavioral analysis and device fingerprinting to build consumer trust and manage fraud.
Integrates Sift’s risk intelligence and real-time risk scores into internal risk models or third-party systems, adding external context to internally-built risk engines.
Protects brand loyalty and consumer trust by detecting and preventing spam, scams, and abusive content at their source.
The core AI-powered digital risk decisioning platform that combines deep data, real-time risk scores, and identity graph insights to detect risk, automate decisions, and scale d...
What customers say
“We have to make sure we get it right the first time. We want to be proactive and know what’s happening before it happens.”
“When it comes to seeking and destroying fraud, it’s been just me analyzing the data since our first fraud loss in July 2014 until April 2017, when we added an analyst.”
- Sift Platform
Patreon uses the Sift Platform to analyze user behavior and connections among potential fraud actors. Sift reports reduced fraud losses, a 19x return on investment and a 99.37% new-user acceptance rate.
Case study - Payment Protection
Paula’s Choice reimplemented Sift Payment Protection after a rules-based alternative led to increased chargebacks. Sift reports a 0.2% chargeback level, $100,000 in fraudulent orders prevented in the first three days and…
Case study - Sift Platform
Link Money combines Sift Score API signals with banking and merchant data, and uses the Sift Platform for post-transaction monitoring. Sift reports $3 million saved for one merchant and a 90% fraud-volume reduction…
Case study
Security and compliance
As reported by Sift. Ask for audit reports before you buy.
SubprocessorsAnthropic
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