Stop Fraud and Abuse with Unsupervised Machine Learning
Prevent attackers from creating armies of fake accounts, before they do any damage.
Detect when good users’ accounts have been compromised before attackers can use them to commit fraud or abuse.
Spam and Fake Reviews
Maintain trust in your platform by preventing malicious users from sending spam or creating fake reviews.
Stop bad actors from exploiting new user promotions, virtual currency arbitrage, out-of-policy virtual goods transfers and more.
Reduce e-commerce fraud 30-50% above traditional fraud solutions by catching entire crime rings days before they attempt a fraudulent transaction.
Learn How Customers Have Benefited from DataVisor Solutions
“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
“DataVisor has provided a boost to both our spam coverage as well as our spam detection speed. On the coverage front, after DataVisor was integrated, we catch about 80% of our high risk spammers on the day they sign up.”
– Sriguru Chakravarthi
Protect & Integrity @ Pinterest
Learn More Our Use Cases in the Real World
Key Benefits for Social Commerce Companies
90% of Fraud Detected Early
50% Additional Coverage
Detect the earliest signs of account compromise to prevent damage and improve customer experience.
99% Detection Accuracy
Predict and prevent fraudulent transactions by detecting suspicious crime rings early.
The DataVisor Platform
Unsupervised Machine Learning Engine
Supervised Machine Learning Engine
Automated Rules Engine
Global Intelligence Network
What’s Happening with Social Commerce
With Supervised ML becoming increasingly commoditized, businesses are often left with various components rather than a solution that provides real value.
Fraudsters are constantly coming up with new and innovative ways to commit fraud. Today we are taking a look at product listing fraud, a relatively new type of fraud that is a rapidly growing problem for online marketplaces.