Account Abuse Prevention
Powered by real-time machine learningCreate Free Account
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, such as confirmation emails and CAPTCHAs, from the signup flow to get more good users registered on your platform.
“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 across desktop and mobile - both browser and native app..
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.
Customizable workflows are easily configured directly in the console by analysts 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:
Account Abuse Prevention is powered by the Sift Science Trust Platform. One simple integration gives you access to an integrated suite of fraud and abuse products running on a single platform that includes a unified web console, automation capabilities, and real-time machine learning.
The Sift Science Trust 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 desktop and mobile apps across the world. With over 12,000 sites and apps on the platform, we collect, analyze, and learn from 100’s of millions of events each and every day.
Sift Science’s machine learning is so accurate at detecting fraud and abuse that many fraud processes and decisions can be fully automated. You can easily configure workflows 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 users 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.