The pioneer in Digital Trust & Safety, Sift, has announced that it has been included in Gartner’s latest Market Guide for Online Fraud Detection. The research by Gartner describes the current condition of the market for online fraud detection and offers strategic advice to SRM (security and risk management) experts who are investigating the various suppliers and solutions that are available.
According to the report, which was written by VP Analyst Akif Khan and Sr. Director Analyst Dan Ayoub, “it is vital that an OFD [Online Fraud Detection] platform can learn and improve from proven loss occurrences across particular regions (preferably across borders and internationally), not simply inside a single business. Telemetry regarding users, devices, and event outcomes (especially verified frauds) must be anonymous before being shared over a network and among all consumers on the platform. This allows for constantly-running updates to systems, regulations, and algorithms to counteract new dangers as they arise.
Leveraging its worldwide network of more than 34,000 sites and applications, Sift’s Digital Trust & Safety Platform then employs its machine learning models to assess more than 70 billion events and analyze millions of global fraud judgments every month. Customers may implement a genuine Digital Trust & Safety strategy—one that protects against fraud while minimizing friction for legitimate users—by using the full power of Sift’s network and both its global and tailored machine learning models.
“We couldn’t agree more with Gartner’s recommendation that SRM leaders select suppliers with SaaS deployment models that share real-time threat information across their networks,” said Mary Writz, Sift’s SVP of Product. “Gartner advises that SRM leaders favour vendors with SaaS deployment models.” Customers of Sift that take use of these features realize significant reductions in the amount of money lost to fraud as well as the amount of time spent manually analyzing cases. Additionally, they can unleash growth.
Technology users should not feel obligated to choose just those suppliers with the highest ratings or other classifications from those included in Gartner’s research publications, nor should Gartner be considered an endorsement of any vendor, product, or service displayed within. Publications from Gartner’s research division should not be taken as declarations of truth but rather as expressions of opinion. In no event will Gartner be liable for any damages, direct or indirect, arising out of or in any way connected with the use of, or the inability to use, the information included herein.
