Account Abuse Prevention
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Accurately detect bad actors in real time with machine learning, and prevent them from creating phony accounts on your site or app.
Save time and money by automating how you stop fraudsters, scammers, and spammers from creating fake accounts and abusing your platform.
Remove roadblocks from signup – such as confirmation emails and CAPTCHAs – to get more good users registered on your site.
“Network Visualizations help us find other fraudulent accounts we haven't noticed before. It's easy to find fraud through this tool.”View Case Study
An account abuse specific machine learning model specialized in detecting users creating fake accounts.
The world’s largest network of online businesses anonymously share new account creation and abuse data and analysis to generate the largest database of fraud patterns.
Fraud analysts manually review accounts, explore visualizations, and dig into details such as connected accounts, device fingerprint, email address, browsing behavior, historical data, and more.
Fraud decisions automatically propagate to all your existing systems. No more switching between systems to manage accounts and prevent fraud and abuse.
Analysts can easily configure customizable workflows directly in the console to automate fraud and abuse processes and decisions.
Custom & global machine learning models analyze thousands of account abuse signals every time a user takes an action on your site or any site on our global network. Here are some examples of the data and signals we use to prevent account abuse:
The Sift Science Platform runs the world’s only machine learning system designed from the ground up to learn in real time from live events taking place on web-scale businesses across the world. With over 6,000 sites on the platform, we collect, analyze, and learn from 100s of millions of events every day.
Sift Science is so accurate at detecting fraud and abuse that fraud processes and decisions can be fully automated. Powerful workflow capabilities are easily configured to automate actions based on machine learning predictions or specific data values. Whether you want to automatically block bad users, remove friction for good ones, or assign them to manual review queues, Sift Science streamlines your fraud prevention practice.
Sift Science’s web-based console gives fraud teams the tools they need to efficiently manage their fraud management operations. Manual review queues keep analysts and managers focused on the most important cases, while data visualization tools and user-level event data provide the details needed to find even the most sophisticated fraudsters.