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We use behavioral patterns to build an identity profile for each user. This provides your app with a second factor of authentication that doesn't add friction to the user experience, or even require the user to opt-in. | Sift Science catches fraud by using large-scale machine learning to identify those patterns automatically. |
| - | Reduce manual reviews & chargebacks;Detect Fraud Automatically in Real-Time;Distill Patterns From Data;Billing & Shipping Address Mismatch;Device Fingerprint;Travel Velocity |
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Stacks 4 | Stacks 14 |
Followers 7 | Followers 15 |
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Open security analytics. Understand, monitor, and protect your product from cyber threats, account takeovers, fake accounts, and abuse.

It is the next generation self-service digital identity and fraud prevention collaborative platform for individuals, businesses, and governments.

It is an open source fraud prevention for marketplaces. It is the backbone for your fraud system, bringing all of your data and processes into one place.