Online Auto Loan Application Channels Are Prone To High Rates of Synthetic Identity By Fraud Rings
By Justin Hochmuth, Senior Fraud Analyst and Margo Hoyt, Senior Fraud Analyst
The pandemic, combined with expanding, accessible technology, has changed how consumers purchase cars. A Progressive Insurance study showed that individuals who reportedly bought a vehicle online had much higher satisfaction levels versus individuals who purchased in person at a dealership. However, while online car buying is viewed as ‘fast and easy,’ it is also very ‘fast and easy’ to commit fraud.
Point Predictive has previously released data illustrating the immense growth of auto loan fraud through the pandemic, and online applications help fuel a portion of that growth. Recently, Point Predictive fraud analysts discovered a trend where fraudsters are not only using ‘fake’ and ‘suspicious’ employers but also synthetic identities listing common, large corporations as their employers. The problem is that the employer’s phone number and all the other information on the credit application are fictitious.
The Point Predictive team looked in-depth at one of these situations, where the fraudsters, primarily located out of Illinois, Virginia, and North Carolina, utilized the large insurance provider, AFLAC, as the employer on hundreds of applications seen within the Point Predictive proprietary data repository. Due to the way lenders get ‘peppered’ by these applications and the famous mascot of AFLAC being a duck, we have coined this new fraud scheme, the Bird-Shot Strategy.
Bird-Shot Strategy: A Case Study
Our fraud team recently discovered this fraud ring by noticing a high volume of applications with synthetic markers listing AFLAC as the employer. Applicants were utilizing both manufactured synthetics where all application data was synthetic and traditional synthetics where real information was mixed with fake.
We found 389 applications with 209 unique SSNs, totaling more than $22 million in application value submitted over a 90-day period. The average loan amount for these transactions was more than $56,000. All these applications originated from a single online retailer with the following characteristics:
· The identities on the online credit applications typically had limited or no credit and used a randomly issued Social Security Number.
· The home addresses provided on these applications were primarily unoccupied homes, actively for sale or rent.
· Various employer phone numbers were reported, but the area code consistently started with 336 or 919.
· We observed 173 different work numbers, most of which were randomized and not in service.
· The typical income for these borrowers ranged from $75k to $89k annually, and the listed occupation was ‘sales.’
Many of these individuals supplied numerous SSNs to the same lenders, sometimes as little as a day apart. The fraudsters often selected high-risk / high-value collateral. The fraudsters sought out a retailer known for their hassle-free, online and in-store car buying process. Further research revealed numerous online guides, YouTube videos, and social media how-tos on how to take advantage of this online source of retail auto loans.
‘Quacking’ Down on Fraud
As a result of this discovery, Point Predictive was able to notify lenders that had received these applications and set up flags to ensure that lenders were alerted to this risk in future.
The Point Predictive AI-driven data repository approach gives lenders the best possible defense against fraud schemes like this. The ability to see in-depth insights, application history, and alerts from across the data repository, combined with dedicated fraud analyst support stops this type of fraud in its tracks.
Learn more about how Point Predictive helps lenders fight these types of fraud trends with AutoPass™.