September 25, 2018
September 20, 2018
Today’s online lenders are in need of robust and intelligent fraud prevention solutions which equip them to fight sophisticated frauds, often initiated by fraud rings. This online lending exchange connects consumers with multiple lenders, credit partners and banks and was experiencing high levels of fraud, particularly from fraudsters abusing the complimentary credit score service.
Using the ThreatMetrix solution, the lending exchange slashed cost associated with high manual reviews and unnecessary credit checks, while reducing fraud. This helped maintain the company’s trusted reputation and minimized friction for trusted users.
This lending exchange provides customers with a complimentary credit score along with lending options with different banks, lenders or credit partners. The complimentary credit score is provided through a third-party credit bureau that verifies customer information for a fee to the lending exchange. Problems started to arise when fraudsters took undue advantage of the credit score service, creating new accounts to verify stolen customer information and resell it on the dark web. The lending exchange initially leveraged traditional network-level defenses, such as IP address restrictions, to stop fraudsters from leveraging this service. However, traditional methods were found unable to match the pace of sophisticated fraud techniques used by these fraud rings.
Facing thousands of weekly fraudulent requests, the fraud team was unable to keep up and required a robust solution to:
The ThreatMetrix solution is powered by the ThreatMetrix Digital Identity Network which harnesses global shared intelligence from millions of daily consumer interactions including logins, payments and new account applications. Using this information, the lending exchange leverages a unique digital identity for each user by analyzing the myriad connections between devices, locations and anonymized personal information.
Behavior that deviates from this trusted digital identity can be accurately identified in real time, alerting the lending exchange to potential fraud.