Social Commerce

Predictive fraud detection for the billion users era.

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DataVisor Solutions for Social Commerce

DataVisor helps the largest social networking properties and e-commerce platform to prevent fraud and abuse by using unsupervised machine learning to identify networks of bad actors hiding within their platform. Unlike traditional solutions that look at individual accounts one at a time in isolation, DataVisor’s user analytics platform looks at all user accounts together to find highly correlated, suspicious clusters of accounts. The unique combination of unsupervised machine learning, supervised, rules and reputation signals enable DataVisor to detect fraudulent behavior with unmatched precision and coverage.

detected early or in real-time

Early detection

Detect “sleeper cell” accounts before they wake and conduct damage by analyzing all incubating event types – not just attacking events

additional detection

Unparalleled accuracy and coverage

Detect the entire crime ring at greater than 99% accuracy by linking all malicious users together into fraud groups

accounts protected globally

Massively scalable

Able to to support the largest internet properties by handling billions of events per day

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Key Use Cases

Mass registration detection

Prevent crime rings from creating large armies of fake accounts within your online service, before they can conduct any damage

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Account takeover detection

Detect when good users accounts have been compromised by bad actors before it leads to damage for your customers or your platform

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Spam and fake review blocking

Maintain trust in your platform by preventing malicious users attempting to deliver spam and fake reviews

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Promotion abuse prevention

Identify how bad actors are exploiting first-time user promotions, virtual currency arbitrage, out-of-policy virtual goods transfers and more

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Fraudulent transaction detection

Reduce e-commerce fraud up to 50% above traditional fraud solutions by catching entire crime rings hours or days before they attempt a fraudulent credit card transaction

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Bringing Real Value to Our Customers


“DataVisor’s user analytics are an important part of our spam detection system and helps prevent malicious accounts from interacting with real users and businesses.”

– Jim Blomo | Engineering Manager | Yelp


Learn how Yelp Stops Fake Accounts with DataVisor

The epidemic of fake accounts impacts businesses from social media to ecommerce to banking. Interested in knowing how to overcome this emerging threat? Watch this recording of a webinar hosted by Julian Wong, Technical Architect at DataVisor, and his special guest, Jim Blomo, Director of Engineering at Yelp, to learn how Yelp stops fake users while connecting people with local businesses.

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Key Product Features

Unsupervised Machine Learning Engine

Identify unknown threats by linking bad actors together into malicious campaigns through correlation of user and event attributes

Supervised Machine Learning Engine

Provide supplementary attributes from known bad actors discovered by unsupervised machine learning and client-provided labels

Automated Rules Engine

Automatically generate and sunset rules daily using DataVisor’s recommendation engine, powered by unsupervised machine learning

DataVisor Global Intelligence Network

Monitor the broadest array of telemetry signals from over 1.3 billion users in a variety of verticals

Early detection view shows how DataVisor catches crime rings before damage is done

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Getting Started

Want to get started and find out how DataVisor can help find malicious accounts hiding inside your social platform? Request a security assessment today!

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