SAN DIEGO--(BUSINESS WIRE)--Point Predictive Inc., the San Diego-based artificial intelligence and data science company that helps lenders predict the trustworthiness of loan application information, published research detailing increased levels of attempted loan fraud in 2020, which the company believes could continue through 2021.
The company’s Auto Fraud Report is the auto finance industry’s most comprehensive annual assessment of application fraud risk. The 2020 edition includes unique insights about income and employment misrepresentation, identity fraud, and collateral fraud for US auto lenders, as well as the impacts of the pandemic on this important sector of the economy.
“2020 was a pivotal year for fraud risk, with auto loan fraud reaching $7.3 billion of originations,” said Frank McKenna, Chief Fraud Strategist for Point Predictive. “The pandemic heightened fear and anxiety and likely made consumers more vulnerable to scams and frauds. The ensuing economic turmoil caused an immediate and dramatic rise in unemployment, increasing some people’s willingness to engage in loan fraud. Furthermore, a flood of stimulus money and generous lender forbearance programs simultaneously increased the level of fraud while delaying lenders’ ability to recognize it.”
Many lenders have praised Point Predictive’s research due to the breadth, detail, and scope of the analysis. This year’s analysis drew from the Point Predictive anti-fraud Consortium dataset, a secure and private data science collaboration among dozens of US lenders. The Consortium now includes over 94 million loan applications containing 85 individual fields of data on each application. Every month, activity from 45,000 dealerships contributes to a view of vehicle financing that spans nearly all 157,000 US auto dealers. This data set tracks over $2.7 billion in known early payment default and the company’s machine learning techniques have generated more than 10 billion risk attributes, offering unparalleled insight into mostly hidden risk trends and the ability to predict more fraud than ever before.
“Consortium data is deeper and more predictive of risk than any credit bureau or public records source,” said McKenna. He continued, “This vast and deeply-specific data on each loan application gave us incredible clarity into fraud risk that lenders are exposed to. And one thing is for sure: the risk of fraud to auto lenders rose dramatically as the pandemic unfolded.”
One of the most significant trends addressed by the analysis was the marked uptick in income and employment misrepresentation. As the lockdowns began, Consortium members were suddenly impacted by a 100% year-over-year increase of falsified income and employment claims on auto loan applications, a level of risk which continued throughout the year. Detected among the trend was the use of over 300 new, but bogus employers each month, used by applicants to fraudulently convince lenders of steady sources of income.
Completing a complex risk picture for fraud managers, the report notes that scams like synthetic identity creation, credit washing, and even lawful impacts of credit repair efforts complicate efforts by lenders to guard against fraud in order to more quickly serve trustworthy borrowers.
“As a lender, you have to keep your guard up at all times. No assumptions can be made about any loan application until every single one clears a satisfactory fraud review,” said Steve Christensen, Executive Vice President of Elite Acceptance Corp. “The analysis and outlook from Point Predictive is essential reading in order to be prepared. For Elite Acceptance, the crucial trends to get ahead of are the dealer implications, such as a sale price inflation of over 10% on the top 10 models,” said Christensen. He concluded, “I credit Point Predictive for exposing the truth behind what is presented to lenders by dealers and borrowers.”
Additionally, the analysis of auto loan fraud in 2020 covers other concerning trends, including clusters of fraud in certain states and metropolitan statistical areas (MSAs), new tactics used by self-employed borrowers, patterns of suspicious and ambiguous naming conventions for fake employers, synthetic identity centers, Social Security number manipulation tactics, vehicles subjected to inflated pricing, and the systematic disputing of multiple negative tradelines on a credit report in order to make the borrower appear to be more creditworthy. Power booking is also on the rise, wherein dealers inflate sale prices and falsify down payments to increase the chances of loan approval.
The Auto Fraud Report concludes with recommendations from Point Predictive’s fraud experts for staying ahead of fraud in 2021. Tim Grace, Chairman and CEO of Point Predictive, encourages lenders to bolster fraud defenses and staff. “In times of crisis, there is often a need to reduce costs to stay profitable amidst decreasing volumes. But this is a mistake. The rate of fraud and risk will increase over the next 18 months, making fraud prevention and staffing one of the most important investments you can make in maintaining the health of your portfolio. Resist the urge to cut costs where it matters most.”
Auto, mortgage, and student lenders who are interested in receiving a copy of Point Predictive’s 2020 Annual Auto Fraud Report should contact firstname.lastname@example.org.
About Point Predictive Inc.
Point Predictive enables lenders to fund more loans simply with a unique combination of Artificial and Natural Intelligence™ (Ai+Ni™) to power machine learning technology solutions. Point Predictive helps automotive, mortgage, retail and personal loan finance companies to identify the consumer applications with truthful and reliable information without the intense interrogation and verification of data caused by lower tech solutions currently in use. Highly regarded as the most trusted fraud and misrepresentation analytic solution providers, Point Predictive has transformed that trust to enable lenders to fund more loans to more consumers simply. Point Predictive uses big data 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 with the added natural intelligence of human experience.
Located in San Diego, California, more information about Point Predictive can be found at www.PointPredictive.com.