SAS has joined forces with leading digital identity solutions provider ThreatMetrix. The alliance will help creditors better establish the “who” behind online credit applications, giving them a new edge in rooting out fraud, identity theft and synthetic identities.
Today’s consumers expect to apply for credit at any time and from anywhere. To deliver optimal customer experience, financial institutions must make prompt credit decisions, often in seconds. Incorrectly deny a loan or credit line, and they are apt to lose a valued customer. Grant credit to a would-be fraudster? That’s a mistake that costs the banking industry billions annually.
“Banks are struggling with authentication measures and strategies across enterprises, knowing they must somehow strike that critical balance between security and customer convenience,” said James Ruotolo, Director of Product Management and Product Marketing for Fraud and Security Intelligence at SAS. “Who is really applying for credit on the other side of that phone, tablet or computer? That’s a billion-dollar question for the industry, which knows the foundation of fraud prevention is understanding true identity.”
At the heart of any type of authentication is data. ThreatMetrix analyzes more than 110 million transactions per day across more than 6,000 customers around the world. By tracking and identifying associations between tokenized, crowdsourced data points across its global network, ThreatMetrix derives insight into the true digital identity of users. SAS will enrich that data to inform the automated, predictive models that help determine the likelihood of fraud and accelerate accurate decision making.
“According to our network data, one in nine new online account applications is fraudulent,” said Leah Evanski, Vice President of Alliances at ThreatMetrix. “The ThreatMetrix Digital Identity Network’s cross-industry, global shared intelligence, combined with SAS’ industry-leading fraud detection solutions, will give customers a tremendous advantage in identifying fraudulent applicants and enabling a better experience for everyone else.”
Artificial intelligence (AI) has the ability to improve the speed and accuracy of fraud prediction. But effective AI relies on large data sets. Using credit application data alone, AI-driven models can achieve a certain level of accuracy. Adding complementary data sources to those applications further improves accuracy which helps identify more fraud and avoid costly false positives that introduce unnecessary customer friction.
“As much as digital data is the cornerstone of a true authentication platform, context is key,” said Stu Bradley, Vice President of Fraud and Security Intelligence at SAS. “The industry is not looking at just the transaction any more but rather the bigger picture of who, what, where and when. By augmenting SAS’ advanced analytics with this global shared intelligence from ThreatMetrix, the normal combination of account markers tied to a real person becomes more easily distinguishable from fraudulent ones. Banks can simultaneously reduce false positives and detect more fraud.”