Payment Fraud Prevention
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Accurately detect fraudsters in real time with machine learning. Prevent fraudulent transactions and chargebacks before they happen.
Save time by automatically blocking fraudsters at scale. No need to hire more staff or dedicate more resources to fraud review.
Confidently accept more good orders and give legitimate users the smooth, easy buying experience they deserve.
“We reduced chargebacks by 50% while blocking over 6.5x more orders automatically.”View Case Study
A payment fraud-specific machine learning model that gets smarter by the millisecond, analyzing billions of global payment fraud patterns across desktop and mobile - both browser and native apps.
The world’s largest network of e-commerce merchants anonymously share fraud patterns and analysis to generate the most accurate fraud predictions.
Fraud analysts can manually review orders, explore visualizations, and dig into details such as geolocation, order history, connected accounts, historical data, and more.
Fraud decisions automatically propagate to all your existing systems. No more switching between systems to block a bad order.
Analysts can easily configure customizable workflows directly in the console to automate fraud processes and decisions.
Custom & global machine learning models analyze thousands of payment fraud signals every time a user takes an action on your site. Here are some examples of the data and signals we use to prevent payment fraud:
Payment Fraud 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 6,000 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.