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auto loan applications

What percentage of the auto loan applications you received this month intentionally misrepresented information about the borrower, vehicle, or dealer? How many delinquent loans were rooted in fraudulent auto loan applications with absolutely no intent to meet payments? Today, how do you recognize intentionally misrepresented information on an auto loan application?

Auto Loan Applications: Change Identity, Income, and Employment in Minutes

As consumers, we benefit from near-immediate access to global products and services, but the personal and financial information that underpins those transactions is often exposed via data breaches. Fraud rings use breached data to create false identities using names, social security numbers, addresses, phone numbers and other personally identifiable information (PII).

Google “create fake identity” and you’ll be overwhelmed with services, examples, and guidance on how easily you can create a false identity. For all the benefits of a digital economy, this a sobering example of how bad actors exploit it at the expense of honest borrowers, lenders, and dealers.  

Income, or lack thereof, is no longer a barrier to purchasing a vehicle. An applicant can misrepresent income on the auto loan application, inflating it to qualify for a new or high-value used vehicle. In the case of a subprime application, an underwriter may include a stipulation to verify income. Online, an applicant can find dozens of services to create a realistic-looking document that confirms the applicant’s income and meets the stipulation.

A stable employment record boosts an applicant’s prospects for obtaining an auto loan. But if a sketchy employment history is a problem, that too can be remedied with services that will confirm your employment with a fictitious company. Fraudsters can buy phone, written or email confirmation of employment, a company website and phone number, and even recommendations from former supervisors of the fictitious company.   

When a lender is fielding hundreds to thousands of auto loan applications per week and is highly motivated to boost, or at least maintain, capture rates, a fraudulent auto loan application can default in a matter of weeks.

Dealers Misrepresent Information Too

Fraud isn’t limited to individuals and criminal elements. Dealers may be moved to misrepresent information by sales quotas, an opportunity to increase the profit margin on a deal, or outright theft. With more dealers adopting a paperless approach to auto loan applications, the lack of a paper trail makes it easy to make modifications to the terms verbally agreed upon in the showroom. Dealers might be tempted to inflate the value of the vehicle, deflate trade-in value, or modify other terms in their favor.

There are endless variations regarding the sophistication and scope of dealer fraud, though identity is a common factor in each. Although the perpetrators were caught, early detection of these schemes would have significantly reduced the financial damage experienced by the lenders:

Auto lenders need to play aggressive defense against unscrupulous borrowersindividuals, fraud rings, and dealers. If not recognized at the outset, the increasing incidence of purposely- misrepresented information on auto loan applications will lead to increased defaults and damaging delinquencies. Facing the reality of the ease of intentionally misrepresenting information, how can lenders prevent these risks from hurting them?

Use Analytics to Identify Fraudulent Auto Loan Applications

Powerful and sophisticated analytical capabilities of leading fintech providers help identify auto loan applications with potentially misrepresented information. Using machine learning, tens of millions of loan applications are analyzed to identify factors that indicate possible misrepresentation. As thousands of new auto loan applications are analyzed, machine learning continues to refine the models, fine-tuning analyses to the needs of individual lenders, tracking fraud rings, and monitoring dealer risk.  

When analysis detects a potential misrepresentation, it provides a fraud score and a dealer score, as well as the reason(s) why the application is suspect. The higher the score, the greater the probability of fraud. Reasons include:

  • Inflated income;
  • Fabricated employment;
  • Dealer associated with high-risk applications; and
  • Inflated vehicle valuation.

Armed with the specific suspicious element, lenders may decide if it merits further verification of the questionable attributes, or if they should just immediately decline the application.

We’ve only scratched the surface of the challenges in detecting fraudulent auto loan applications. If loss from fraud is affecting your profitability, listen to The Hidden Patterns of Auto Lending Fraud Revealed.

When integrated with a modern loan origination system (LOS), fraud analytics support more confident lending decisions. Fraud analytics is the first line of defense against issuing credit to applicants very likely to result in defaults. It lets you proactively recognize fraud and prevent it from hurting your portfolio and profit.

Getting Started

defi SOLUTIONS understands the risks presented by fraudulent auto loan applications. Through integration with other leading fintech service providers we enable lenders to reduce the impact of fraud. Learn how a modern LOS and analytics fight fraud by contacting our team today or registering for a demo of defi LOS.


Get in touch with us today and get a demo!


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