Sift Science Delivers the Most Advanced Machine Learning Fraud Detection System

New Features Automate Business Decisions Through Machine Learning and Device Fingerprinting, Enhancing Protection Against Online Fraud

SAN FRANCISCO, July 15, 2015 – Sift Science, the leading provider of machine learning fraud detection, today announced new advanced features of its large-scale and automated platform. These features allow companies to streamline fraud prevention and mitigate today’s most advanced fraud threats for the real-time online economy.

News Facts

  • As e-commerce continues to thrive and the on-demand economy grows, more fraudsters are taking advantage of e-retailers and online businesses through credit card fraud, fake accounts and other online abuse.  With the Europay, MasterCard and Visa (EMV) standard set to hit the U.S. in October, online businesses must prepare themselves for the impending wave of advanced and sophisticated digital fraud threats.

  • Sift Science’s customized, cloud-hosted machine learning and behavior analytics platform scrutinizes, in real-time, hundreds of millions of fraud patterns per day to protect hundreds of businesses and thousands of websites from online fraud.

  • Sift Science has added Formulas and Device Fingerprinting, two new features that businesses can use to automate critical business actions, such as canceling an order or preventing a user signup, based on insights derived from Sift Science’s real-time machine learning platform. By leveraging these new capabilities, customers will drastically reduce the time and cost of managing online fraud.

  • Born out of Y Combinator, Sift Science welcomes a significant milestone, celebrating four years since inception. With companies like Wayfair, OpenTable, Kickstarter, and Everlane, Sift Science customers span a wide range of vertical markets, including payment gateways, on-demand businesses, e-commerce, financial services, online communities, marketplaces, and more.

Comments

“With the addition of Formulas and Device Fingerprinting to Sift Science’s already powerful machine learning platform, we now have  an unbeatable combination of technologies and techniques for stopping online fraud,” says Kenneth Sung, Sr. Fraud Analyst at HotelTonight. “We’re excited to take advantage of the automation these new offerings allow, which will expedite our fraud review process and make delivering our product to our customers even faster.”

“Now more than ever, online businesses recognize fraud as a growing risk to their organization,” said Jason Tan, co-founder and CEO of Sift Science. “By providing protection and advanced machine learning to transaction behavior between the customer and merchants, businesses can begin to protect themselves from advanced fraudsters in the on-demand and real-time economy. We’re thrilled to be celebrating our four-year anniversary by adding these integral features of formulas and device fingerprinting to further arm our customers against fraud.”

The Sift Science platform is available today, for more information, visit https://siftscience.com/features  

Tweet This: @SiftScience celebrates anniversary and adds Device Fingerprinting, Formulas, bolstering its advanced fraud protection belt http://blog.siftscience.com/blog/pr-sift-science-formulas-devicefp

About Sift Science

Sift Science provides real time fraud protection through large-scale machine learning and risk scoring that allows online businesses to easily identify all types of fraud and protect their core assets. Sift Science not only provides businesses with the most comprehensive fraud detection platform, it can also be customized for any online business. By utilizing Sift Science’s beautiful Console to effectively visualize site activity in real-time, online business and marketplaces can balance the needs of fraud protection and great customer experience. Sift Science is headquartered in San Francisco, California. Visit us at https://siftscience.com and follows us on Twitter @SiftScience.

Media Contact:

Jim Dvorak
Kulesa Faul for Sift Science
jim@kulesafaul.com
415-735-1622

 

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