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
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.
A successful spam campaign is one that obtains maximum return-on-investment (ROI) to the spammer. This means that a spam campaign must reach as many end users as possible, must be robust in the face of blacklisting efforts, and must be scalable. This blog post describes some of the recent techniques employed by spammers to distribute malicious URLs on social media platforms as observed by DataVisor.
The DataVisor Online Fraud Report took a look at our base of more than one billion users across 172+ countries in the world. Using this massive amount of data, we were able to identify some of the favorite tools and attack techniques that online criminals from around the globe favor when doing their dirty work.