Point Predictive Inc., the San Diego-based company that provides machine learning solutions to the lending industry, announced today that its industry-leading fraud team has reached the milestone of identifying $1 billion in fraud loan value tied to more than 5,000 fake employers on auto loan applications. The findings took place from February 2019 through December 2021. Point Predictive is the first company to proactively investigate the fake employer problem in the lending industry and identify the size and scope of the problem.
Point Predictive found that in the cases of fake employer fraud, a borrower creates a fake employer to generate forged paystubs, falsified income and synthetic identities to car dealers and auto lenders during financing. The fake employers were identified by Point Predictive’s Fraud Analysts during investigations of loan applications flagged by Auto Fraud Manager – the companies consortium risk scoring solution used by auto lenders nationwide.
During the investigations, the identified fake employers were associated with fake websites, falsified incomes, high rates of confirmed synthetic identity, and high rates of defaulted loans.
“The rise in the use of fake employers on credit applications is astounding, and the $1 Billion dollar threshold only proves the growing threat of this problem”, said Justin Hochmuth, Senior Fraud Analyst at Point Predictive, “We’re uncovering about 100 new fake employers that are being created each week. The exceptional work done by our team and the power of Auto Fraud Manager prove that we are addressing this threat head-on and strengthening value to our partners as we work to significantly reduce fraud in multiple industries, from auto loans to mortgages and even personal loans and apartment rentals.”
Point Predictive’s unique vantage point with the loan consortium enables identification of these types of hidden fraud patterns which a lender or car dealer may not identify on their own. The Point Predictive consortium contains more than 110 million historic applications and over 10 billion unique risk attributes that can expose patterns, a scale that far exceeds all competitors. In these fraud cases, a lender or dealer may only see a single application associated with an obscure employer and will not have an understanding of the broader fraud scheme at work. However, the consortium can identify how a single fake employer might be associated with hundreds of suspicious applications across many different lenders, information that can save lenders and dealers up to $21,000 in losses per occurrence.
“When we formed the auto loan consortium in 2017, these are exactly the types of patterns we were focused on uncovering”, says Tim Grace CEO of Point Predictive. “When one of these fake employers is used on an application, the loan is significantly more likely not to perform. We’re seeing some of these fake employers associated with default rates between 40% to 100%. We’re proactively identifying these schemes early for our lenders, helping them avoid hundreds of millions in losses each and every year.”
For lenders or other organizations interested in determining whether an employer is considered fake, log onto Point Predictive’s “Employer Check” page for guidance. Click here for the link. And for more information on Point Predictive, please contact firstname.lastname@example.org