Socure announced an identity fraud solution, Socure Sigma Identity Fraud. Sigma Identity Fraud delivers an identity fraud classification model by utilizing over 17,000 features that analyze every dimension of a consumer’s identity—name, email, phone, address, IP, device, velocity, network intelligence, and real-time consortium feedback data—all in a single product.
Socure Sigma Identity Fraud enables enterprises and government agencies to increase auto-approval rates and reduce fraud losses, false positives, friction, and costs associated with manual reviews. Sigma Identity Fraud increases auto-approval rates by up to 60% and captures fraud in the riskiest 3% by 90%, to solve for both fraud protection and revenue generation.
The solution reduces manual reviews by >80% through substantially more accurate decisioning. Sigma Identity Fraud also reduces false positives by >13x compared to legacy solution providers, enabling customers to verify the largest number of good consumers, increase the automation of the onboarding process, and also reduce fraud losses.
Sigma Identity Fraud has become a gold standard for enterprises that are increasingly reliant on digital channels to grow their business. And with that growth comes the challenge of combating identity fraud which is costly and can negatively impact the bottom line. In fact, according to Javelin Strategy & Research, identity fraud losses in the U.S. in 2020 reached a total of $56 billion.
This figure represents a combined total of $13 billion for traditional identity fraud, and $43 billion for identity fraud scams. This inordinate growth can be attributed to the expansion of digital channels combined with fraudsters compromising a treasure trove of personally identifiable information (PII) that enables them to impersonate a consumer’s identity.
“We have created the perfect balance between fraud detection, eliminating customer friction, and reducing false positives all in one solution with our latest Sigma Identity release,” said Johnny Ayers, founder and CEO of Socure. “Enterprises of all sizes rely on Socure not just for fraud protection, but for growing their business. The accuracy of our Sigma fraud classification model has made legacy solutions centered around single identity elements, manual reviews, or knowledge-based authentication a thing of the past.”
“Deploying Socure’s technology has significantly increased our ability to accurately locate identity fraud while also enabling us to auto-accept more good applicants. Our manual account reviews have also decreased dramatically. The innovations delivered by Socure help us to stay ahead of fraud trends while continuing to provide an optimal experience for our customers,” said Mark Kassardjian, director of customer operations at Betterment.
Sigma Identity Fraud Solution
Device intelligence: Socure Sigma Identity Fraud is an application fraud solution that “binds” device data to the individual using the device to deliver better identity decisions in a holistic model.
Data velocity: Socure’s approach to data science enables flexible, advanced ML model development on the largest identity graph and set of performance feedback data in the industry. Utilizing the Socure ID graph of 750+ customers and 600M+ rows of performance data, Sigma Identity Fraud distinguishes names, emails, phone numbers, addresses, SSNs, IPs, devices, and other elements used for multiple fraudulent account openings and subsequent account use.
Data linkages: Socure’s Sigma Identity Fraud is an application fraud solution that analyzes identity behavior across industries and the consumer lifecycle to improve results. It analyzes real-time dynamic linkages across seven billion rows of transaction data to inform the model. Its clustering linkages enable improved identification of fraud and fraud rings.
Consortium data: Trained with feedback data from the consortium of 750+ clients, Sigma Identity Fraud delivers better fraud models and improves any fraud program. Socure’s identity resolution engine analyzes over eight billion records and more than 530 million known good and bad identities to achieve the most accurate view of identity possible.
As the consortium gets larger, Socure gets smarter using feedback data from the expanding network of trusting firms to continually improve results to counter evolving fraud patterns. The attack may be new to a customer, but it is highly likely that Socure has already identified and learned from the fraud attack elsewhere in the network.