Auto Lending Fraud Trends in 2019

by Frank McKenna
Auto Lending Fraud Trends in 2019

Have you heard this phrase before – “the more things change, the more they stay the same”? This is certainly the case when it comes to auto lending fraud.

Fraudsters may change their stripes and perpetrate new and more clever schemes each year, but in the end the results are the same – lenders and consumers continue to get victimized and continue to lose billions of dollars in the process.

In 2019, PointPredictive estimates that up to $6 billion of auto lending originations may contain misrepresentations on the loan file that could cause serious issues for auto lenders across the US.

Analyzed Historic Applications

PointPredictive analyzed loan originations from 2012 through 2018 using a predictive model that scores the level of misrepresentation on applications. The model looks for misrepresentation related to income, employment, straw borrower, collateral, dealer and identity and scores the application from 1 (low risk) to 999 (high risk).

By aggregating these scores over a 6-year time period a risk index can be created, which helps us understand if fraud risk is rising or falling. The index clearly shows a persistent increase in misrepresentation risk year-over-year.

So what trends are driving fraud risk up? What are the factors that are driving an increase of fraud and misrepresentation at lenders? We analyzed the top 5 trends expected for 2019, and here are our findings:

The Top 5 Fraud Trends Lenders Should Watch Out for in 2019

1. Synthetic Identity Fraud in Auto Lending Continues to Rise

In 2018, Synthetic Identity fraud continued its upward trajectory in auto lending. Statistics and data research points to a problem that simply cannot be ignored. PointPredictive estimates indicate that up to 20% of some lenders-fraud-related defaults could be caused by fraudsters using stolen or synthetic identities.  Further, Trans Union reported that up to $600 million of originated auto loans they analyzed contain synthetic identity patterns. In 2019, this trend will continue and lenders should be on the lookout.

2. Income Misrepresentation Impacts Up to 33% of Applications

We’ve studied and evaluated over 1.2 million historic applications from the consortium to analyze and quantify the impact of income misrepresentation to lenders. Each of the stated incomes on those applications were verified by the lender against income documentation, database checks or other methods.

The analysis concluded that between 14% and 33% of stated incomes were inflated on applications by 15% or more after income validation was completed at each lender. Income fraud continues to be a very pervasive issue for lenders across the industry.

3. Phantom Loan Schemes Against Credit Unions

Auto Lenders in the U.S. are reporting a rise in Phantom Auto Loans, where borrowers and sellers collude to create fake loan transactions. In some cases, the perpetrators are unscrupulous dealers passing off non-existent cars, and in other cases, the loans are private seller transactions.

Phantom Auto Loans are a type of fraud where fraudsters work together to fabricate an entire auto loan when no sale of the car occurs. In these cases, a car is never sold, but the lender provides the proceeds of the loan to a dealer or 3rd party because they have been provided false and misleading information that a real car has exchanged hands.

4. Straw Borrower Schemes Continue to Rise

In 2018 a serial fraudster, Alex Golant, ran a straw-borrowing scheme that purportedly impacted over $30 million in vehicles. To perpetrate his scheme, Golant setup a business called Timeless Auto Group. From there he would recruit straw borrowers from all over the country and have them visit friendly and unsuspecting dealerships that wanted to sell some high-end cars.

We expect straw-borrower schemes will continue to cause problems for lenders as more fraud rings gravitate towards this emerging form of fraud.

5. Systematic Dealer Fraud and Misrepresentation

In 2019, dealer fraud and misrepresentation will continue to impact lenders and consumers alike. Some lenders report that close to 100% of their fraud and risk issues could be attributed to a small fraction of the dealers they do business with – as low as 3% of all their dealers.

Based on analysis of over 70,000 dealers, PointPredictive found that some dealers were able to systematically submit high volumes of bad loans to lenders by sequentially targeting lenders over a long period of time. In one example a dealer was able to send a high rate of fraud loans to 4 separate lenders over 3 years, avoiding detection by targeting a different lender after the relationship was terminated by the first lender.

AI and Machine Learning

Machine learning has been used to tackle the problem of fraud for years. Because machine learning can apply thousands of calculations per second, it is often the perfect technique to uncover statistical deviations that are key signals to fraud behavior.

During my session at CU Direct’s DRIVE Conference in May you’ll be able to gain important insight to fraud trends and how using artificial intelligence can help your credit union solve it.

Don’t miss out — join us at DRIVE and discover the strategies your credit union needs to gain a real competitive edge.

About the Author

Frank McKenna
Frank McKenna is the Chief Fraud Strategist and Co-Founder of AI firm PointPredictive. He has worked and consulted with over 200 banks, lenders and finance companies globally to address the growing problem of fraud across their portfolios.