SAN DIEGO, Calif — December 2, 2020 — Point Predictive Inc., the San Diego-based company that provides machine learning solutions to the lending industry, has determined that many U.S. auto lenders may be experiencing a 50% increase in fraudulent misrepresentation of applicant income since the onset of the pandemic, an amount that is a major contributor to the estimated $7.3 billion in exposure that the industry has faced in 2020. The company arrived at this conclusion after analyzing tens of millions of loan applications spanning the most recent five-year period and attributes the increase in part to the surge in unemployment and professional fraud activity. The company also calculated that an astonishing 10% of all paystubs submitted to lenders as proof of borrower income are falsified. This rate of fraudulent documentation renders broad reliance on paystubs a highly risky method for lenders to verify borrower income.
As a result of these findings, Point Predictive Co-Founder and Chief Fraud Strategist Frank McKenna urges lenders to reconsider the practice of relying on paystubs to verify every borrower’s income. Instead, McKenna recommends the new IncomePass™ Report, a more reliable and cost-effective way for automotive, personal finance, and mortgage lenders to evaluate income misrepresentation by potential borrowers. This new feature of IncomePass gives lenders a detailed third-party assessment consisting of at least 18 independent data points evaluated against over 80 million previously submitted loan applications, offering a more effective assessment of the risk of misrepresented income. When used early in the origination process, only a concentrated portion of stated incomes require additional documentation and review, which mitigates the risk of applicants and interested third parties who fraudulently seek loan approval.
“The income verification process is completely stacked against lenders,” said McKenna. “There is no single, objective, third-party repository that tracks the incomes of all U.S. borrowers, making it shockingly easy for applicants and interested parties in the loan application process to fabricate authentic looking paystubs and W2s.” He continued, “It only took me a few minutes on the internet to find a way to produce totally fake but seemingly authentic documents that supported any income I wished to claim.” He concluded, “Lenders have a fighting chance against fabricated paystubs when they use the IncomePass Report to compare an applicant’s stated income with what can be determined from 80 million previous loan applications.”
Over a dozen major U.S. lenders are already using IncomePass to validate income reasonability and assess income requirements, saving those lenders unnecessary operational cost, losses, and borrower friction.
McKenna recently disclosed how easy it is to obtain completely fraudulent paystubs during a session he hosted at the National Automotive Finance Non-Prime Auto Financing Conference last month. Since the problem is infrequent but disproportionately costly, even talented fraud analysts struggle to detect all of this fraud when tasked with reviewing hundreds of similar-looking documents every day.
IncomePass harnesses Point Predictive’s patented Artificial + Natural Intelligence™ (Ai+Ni) technology to give lenders at least 18 reliable indicators of the likelihood that the income stated by a borrower on a credit application is substantially misrepresented, all in less than a second. Powered by a consortium data set consisting of over 80 million prior loan applications, nearly 250,000 employers, $3 billion in early payment default history, and Ai+Ni machine learning technology that continuously discovers patterns of fraud, IncomePass is able to clear nearly 75% of applications for income misrepresentation. The IncomePass Report includes details pertaining to employers, occupations, tenures, previous assertions of borrower income, and historically suspicious activity patterns, making IncomePass a powerful tool given that up to half of all applicants have previously stated income history on record with the consortium.
Tim Grace, Chairman and CEO of Point Predictive, sympathized with fraud prevention professionals facing these modern challenges. “In the digital age, it is increasingly difficult to distinguish between an authentic document and a doctored or falsified one,” he said. “IncomePass Report is an incredibly valuable tool for lenders. Not only does IncomePass remove reliance on potentially falsified documents, but it allows lenders to accelerate the process for applicants whose stated income can be trusted,” he added.
IncomePass Report is the newest feature of the income verification solution that Point Predictive launched earlier this year. IncomePass Report is available as a batch or real-time integration into origination and underwriting workflows for all financial services providers who need to verify stated income on loan applications.
For more information on IncomePass from PointPredictive, please contact email@example.com.
About PointPredictive Inc.
Point Predictive is an Ai technology company with deep expertise in building machine learning scoring models that have been widely deployed by banks and lenders. Point Predictive solutions enable lenders to fund more loans using a patented combination of Artificial and Natural Intelligence [Ai+Ni] that powers machine learning risk assessments. Point Predictive helps automotive, mortgage, retail, personal lending and student loan finance companies identify consumer loan applications that have truthful and reliable information without the intense interrogation and verification of data prompted by solutions currently in use. Highly regarded as one of the most trusted fraud and misrepresentation solution providers to financial services companies, Point Predictive leverages that experience to help lenders safely fund more loans to more consumers while reducing their first-party and third-party misrepresentation and fraud losses. Point Predictive is a big data company using unique insights powerfully orchestrated from millions of examples of true and falsified loan applications, billions of derived proprietary data elements, and scientifically selected third-party data sources to build powerful machine learning models augmented by the natural intelligence of human experience. Located in San Diego, California, more information about Point Predictive can be found at www.pointpredictive.com.