The Growing Threat of Fraud in Auto Loan Origination

Auto loan fraud statistics show how fraud has hurt auto lenders. Industry articles call attention to the creative methods of fraud perpetration. Now there’s a conference devoted to vehicle finance fraud. However, just as technology is enabling auto loan fraudsters, it’s also helping lenders. The latest advancements in fintech and analytics are helping lenders avoid becoming another auto loan fraud statistic.

Gone in 60 Seconds is so quaint now. Why bother hot-wiring a car when auto loan fraud takes less skill and risk? Individuals, fraud rings, and even dealerships perpetrate fraud. For someone with a low credit score, lying on a loan app can help land a loan or better terms. A fraud ring can use a synthetic identity and a $1,000 down to drive away with a luxury vehicle. Dealers can inflate vehicle values or modify application information to pocket additional profit. In each scenario, it’s the lender who suffers.

The internet and growth of electronic transactions have improved nearly every aspect of commerce, making goods and services better, faster, and cheaper, via desktop or mobile. Unfortunately, personally identifiable information (PII) and financial details associated with the electronic transactions are often subject to data breaches. Unwarranted access to that information is the foundation for many fraud schemes involving identity theft.

The internet also makes it easy to create seemingly legitimate documents that support auto loan fraud. Many online services help fraudsters fake income statements, adding a few zeroes in anticipation of a luxe shopping trip. Similar online services exist to confirm employment at fictitious companies.

Auto loan fraud has become the method of choice for acquiring vehicles with a minimum of cash and risk.

Subprime applicants are frequently granted conditional approvals, subject to stipulations. Income verification is a frequent requirement. There’s no shortage of websites that make it easy to create a fake paystub. Provide a credit card number and they’ll guide you through the process, recommending the type of statement, income, monthly, or weekly pay ranges based upon the supposed occupation and location. The goal is to make the resultant paystub appear as authentic as possible. Fill in the information, click print, and send it to the dealer or lender, who, in the interest of selling the car or booking the deal, may not give it any further scrutiny.

Employment verification is also frequently associated with conditional approvals. You’ll find many online services to confirm employment by phone or letter. Fees for the service vary, from one hundred for the basic service to several hundred dollars for the executive service that can include employer website, phone number and email address for the HR department, references from former managers, and even a customized LinkedIn profile. Of course, all of this is fictitious, but a motivated borrower can rationalize this expense as an economically justified means of acquiring a vehicle. Employment confirmation by phone call or letter can be a quick check-off stipulation, but it merits greater attention based, especially when a high-end vehicle is in the deal.

The typical straw borrower scenario involves someone with poor credit convincing a friend or relative with better credit to front the deal, posing as the one buying the vehicle. A better credit score can get better terms, a more valuable vehicle, or both. In the best case, the actual buyer continues to pay the straw borrower throughout the life of the loan. In a typical case, the loan becomes delinquent, a friend’s credit score takes a hit, and the lender begins the recovery process. In the worst case, the straw buyer using a false identity is part of a fraud ring and the vehicle has been already sold in a foreign market.  

Data breaches that expose personally identifying information facilitate identity theft. It’s difficult for an individual to perpetrate this scheme. When it happens, there’s usually a fraud ring coordinating the effort and deploying the scheme widely to maximize gains.

Synthetic identity allows a perpetrator to combine a variety of illicitly-acquired information to create a false, non-existent, but seemingly credible borrower profile. Excellent credit, a social security number, a home address in an affluent neighborhood, solid employment, and other attributes create a seemingly legitimate persona deserving of a quick approval and great terms. However, a detailed and thorough investigation of this persona will reveal subtle inconsistencies indicative of high-risk.

This scheme is the realm of dealerships. Prior to submitting the loan application to a lender, dishonest dealers have many opportunities to modify the information to their advantage. Inflating the value of the vehicle and reducing or failing to mention the downpayment are two immediate means to boost dealer profit. An astute buyer will eventually notice the discrepancies, but an experienced dealer will have finessed the paperwork making it appear that the buyer agreed to the terms.

You can avoid adding to the growth of auto loan fraud by investing some time to gain a better understanding of the problem and how to fight it in the The Hidden Patterns of Auto Lending Fraud Revealed webinar.

At first glance, auto loan fraud statistics and the five schemes mentioned above may appear to be a greater threat to long-term profitability than decreased demand for autos. However, advances in fintech and analytics give lenders powerful tools to identify auto loan fraud and prevent it from hurting profitability.

When analytics and machine learning are applied to millions of loan applications and loan performance histories, including defaults and delinquencies, they can identify loan application attributes and inconsistencies that are highly indicative of fraud. Machine learning techniques are sophisticated enough to identify the type of suspected fraud—identity, income or employment misrepresentation, straw borrowers, and collateral inflation—as well as provide a confidence factor to help lenders determine what level of additional investigation or verification may be needed.

Analytics and machine learning aren’t the only weapons for fighting fraud. Many other services can be easily used with an LOS to automate verification of applicant attributes. Services provided by ID:Analytics can be called when identify fraud is suspect. When income or employment documents are suspect, Equifax The Work Number can help confirm or refute the claim. Vehicle valuation services from Black Book can determine if a dealer’s valuation is reasonable.

Auto loan fraud is a threat to profitability in an already-competitive lending environment. To effectively fight fraud, take advantage of the latest fintech capabilities. Modern, cloud-based loan origination uses integrated analytics, machine learning, and automated verification services to prevent seemingly-legitimate fake applications from becoming more auto loan fraud statistics.