Auto Loan Delinquency Statistics


The defi Team defi INSIGHT, defi LOS

application fraud

You’ve processed hundreds to thousands of auto loan applications this month. Some lending decisions were near-instantaneous—auto approval and auto declines—aided by automated decision rules and workflows. Others required underwriter expertise to review the application, assess the risk, and structure the deal. Of those loans you’ve approved, how many misrepresented information that skewed the deal structure in favor of the borrower and introduced loan risk that could come back to hurt you?   

With auto vehicle sales peaking in 2017, the auto lending market has become far more competitive. Many lenders have loosened credit policies to maintain historic portfolio levels. Unfortunately, the combination of loosened credit policies and numerous fraud-abetting online services makes it easy for applicants to misrepresent information in their auto loan applications. Dealers anxious to move cars off the lot and lenders eager to book a loan rarely catch misinformation on applications. Income misrepresentation is one of the most common methods (an estimated 30%) of auto loan application fraud.

Application Fraud: Create Fake Pay Stubs in Minutes   

Loan applicants who need a boost in reported income can google “fake pay stubs”. To appear legitimate, some sites even provide rationale and guidance for creating fake pay stubs with verbiage, like:

  • Useful when you need to submit documentation that your employer doesn’t provide;
  • Ensure the information on your pay stub is factual;
  • Create pay stubs regularly even if you don’t currently have a specific need; and
  • Have pay stubs available to save time when you have an emergency and need to apply for a loan right away.

These sites direct you to “Click Here to Create Your Paystub in a Few Minutes.” Could it be any easier? Use of fake pay stub services has even caught the attention of CarsDirect. Their webpage Can I Fake Proof of Income for an Auto Loan? calls out the deceptive scheme and strongly admonishes borrowers to avoid it. As a further warning, the web page also explains the techniques lenders use to identify application fraud.

  • An experienced underwriter would realize that an applicant’s income of $120,000 doesn’t synch with a job title of forklift operator
  • A lender could place a stipulation, requiring the applicant sign a 4506-T copy of tax returns form, but that stip delays the lending decision
  • Bank statements can also be used to confirm income, but you can generate bank statements as easily as income statements
  • Income could also be verified with a call to the employer, but employment fraud is just as prevalent as income fraud

All of these methods are manual attempts to catch income misrepresentation. They require additional underwriting time that dings overall loan origination process productivity.

Detect Application Fraud Efficiently

With the volume of auto loan applications and high pressure to book deals, lenders are challenged to detect fraudulent applications. Just as technology has made it easier for individuals to commit fraud, technology is also enabling lenders to stay a step ahead of fraudsters, using the latest in machine learning.

Tremendous volumes of digital information about occupations, job classifications, titles, variations, income ranges, and regional differences are available from private services and government databases like IRS income data and US Census data.

Machine learning is applied to analyze these data and to create profiles for occupations and incomes while accounting for regional cost-of-living variations. Lenders can use fraud detection services that employ machine learning. These services plug into modern loan origination systems to review applicant attributes automatically, and to assess the possibility of income misrepresentation.

Benefits of Automated Application Fraud Detection  

Incorporating automated fraud detection services into your loan origination process is a cost-effective way to defend against the economic damage caused by income misrepresentation. The immediate benefits to lenders include:

  • Relieves underwriters of the time-consuming process of reviewing applications and trying to detect income misrepresentation;
  • Automatically reviews applicant credentials and calculates a confidence level regarding the probability of an inflated income; and
  • Eliminates the cost of income verification for many applications.

The long-term benefits are more significant. Detecting income misrepresentation at the doorstep helps lenders reduce the risk of granting credit to applicants with a high probability of defaults—accounts that too often become delinquencies. In a competitive auto lending market, risk avoidance is a critical factor in maintaining profitability.

Getting Started

defi SOLUTIONS loan origination and analytics software experts welcome the opportunity to show how integrated auto loan analytics give you the competitive advantage. Take the first step toward improving the efficiency of your lending practice by contacting our team today or registering for a demo of defi LOS and defi Analytics.


Get in touch with us today and get a demo!


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