Auto Lending fraud and risk losses are on the rise in the US. The numbers are out and they are not good. Last quarter uncollectible auto loans soared to over $1.1 Billion dollars and delinquencies on subprime loans hit their highest level since the worst recession in US history. More concerning is that the rapid growth in auto lending is being fueled in part by deep subprime lending to borrowers with credit scores less than 500.
With auto lending origination levels soaring to some of their highest levels in history the downstream impacts are beginning to reveal itself with concerning levels of fraud.
As former experts in Mortgage Fraud Analytics, PointPredictive is beginning to see history repeat itself – but this time in the Auto Industry. In 2004, Mortgage lending volumes were hitting new heights thanks to an increase in subprime and non-direct lending through brokers. Fast forward 12 years later and the Auto industry is experiencing the same types of rapid growth which is fueling the same sparks of fraud risk that erupted in the mortgage industry.
The Hidden Cost of Auto Lending Fraud are in 3 Areas
There is no central reporting agency for US Auto Lending Fraud so assessing the absolute levels of fraud losses in the US is difficult. The cost of Auto Lending Fraud does hit the bottom line of banks and lenders but it may not always be categorized or recognized as a fraud loss.
Auto lending fraud losses are typically seen in the following areas:
1) Early Payment Default – Loans that default within the first 6 months have a much higher probability of containing material misrepresentations in the original loan application than loans that default much later. PointPredictive believes that between 30% to 40% of early payment defaults in the auto lending industry can be directly linked back to some type of fraud misrepresentation.
2) Dealer Losses – Auto Lenders, particularly in subprime lending experience high levels of risk based losses that can be tied back to individual dealers. Some dealers have extremely high levels of early payment default, known fraud and bad loan quality that leads to losses.
PointPredictive analysis has determined that based on the lender, that almost 100% of their fraud losses may be coming from less than 3% of their dealers and close to 100% of their early payment default losses may be coming from just 10% of their dealers.
Dealer losses may not always be categorized as fraud, however through careful analysis lenders often determine that many of the losses they take are due to intentional misrepresentation at an industrial scale.
3) Fraud Losses – Most auto lenders do have some tracking in place for their fraud losses however it may not always reflect all of their losses since so much fraud is often hidden. Identity Theft, Straw Borrower, Collateral and Dealer Fraud often top the categories of losses that lenders take on for fraud.
US Auto Lending Fraud Losses are in the Billions
Based on data analysis and industry studies, PointPredictive believes that auto lending fraud loan originations are between $2 billion to $3 billion annually based on the current origination volumes of $600 billion dollars.
This conservative estimate assumes that approximately 30% of early payment default losses in the US contain material misrepresentation and that identified fraud is running at approximately 20 basis points of origination volume.
By applying conservative estimates to the origination volumes, it is clear that auto lending fraud is not a small problem but one that cost the auto lending industry potentially billions a year. Additionally, with loan quality (particularly in subprime) eroding quickly PointPredictive believes that auto lending fraud losses and rates could rise dramatically in the next 18 months.
Applying Analytic Models to Assess Risk
PointPredictive applies analytic pattern recognition models which helps auto lenders determine the latent levels of fraud and risk sitting in their servicing portfolios. By analyzing application and loan level information, PointPredictive estimates which applications and loans are most likely to contain fraud and misrepresentation which helps lenders and banks understand how much risks is sitting on their portfolios
Additionally PointPredictive deploys these same models with auto lenders to identify risky loans prior to approval so underwriters can take the necessary actions to stop the fraud and risk before it is approved.
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