Tag: Auto Fraud Scores

10
Mar

The Hidden Risk of Auto Lending Fraud Exposed

hidden-fraud

Auto lending fraud doesn’t get a lot of attention.  You don’t read about it daily.  It doesn’t make front page news.  In fact most people probably don’t even know what it means.  Well, the same was true of the mortgage industry 10 years ago and we learned some valuable lessons.  Auto Lending fraud will become news someday and it’s important we get ahead of the curve and do things to prevent that.

Fraud occurs when there is too much trust and not enough vigilance

There is a tendency for lenders across industries to rely too much on FICO scores and to trust information that is supplied by borrowers and third parties too much.  When this happens, the lenders can be exposed to more fraud and default risk than they were expecting.

What the Mortgage Industry Learned about fraud

In 2004, the mortgage industry was in full swing. The housing market was booming and mortgage originations were closing in on close to $3 trillion dollars annually.  Everything was seemingly going right, or was it.

Fundamentally things were about get very bad for lenders but they didn’t realize what was brewing.  In attempt to gain market share and keep up with the seemingly endless supply of people that wanted houses, lenders were expanding loan programs and layering risk in new ways that had never been tested.

In 2006, the cracks began to show – primarily in subprime lending and by 2008 the mortgage industry had completely melted down.  Loans were not performing and borrowers were defaulting at record levels.   So what happened to cause such a massive collapse.

1)  FICO scores were trusted too much – Lenders relied on FICO scores too much, however many borrowers with great credit scores were defaulting because FICO scores were primarily built on credit not mortgage data.

2) Lenders trusted the information from borrowers and brokers too much – The second problem that emerged was fraud.  Lenders trusted the information supplied by borrowers and mortgage brokers too much when in fact fraud was commonplace.   Studies indicated that 3% of mortgage brokers accounted for most of the fraud accounts and were systematically conning lenders into making bad loans.  The credit rating agency Fitch even did a study which indicated that 25% of the subprime mortgage loans that defaulted had fraud in the application.  Fraud hurt the mortgage industry dramatically.

3) Warnings of Fraud were Ignored – Lenders were in a race to get loan volume and ignored industry experts that warned of fraud.  It was commonly known that loan programs called Stated Income Programs were also called “Liar Loans” but lenders loaned on them anyway since they assumed they would perform.

4)  Over-reliance on the Collateral –  As housing prices soared property values were skyrocketing creating a market where homes became like ATM Cash machines.  When borrowers needed money they could simply refinance their houses and take the equity out.  Borrowers that could not afford their mortgage payments could simply “refinance” their way out of the problem.  Lenders were lulled into a false sense of security since the default rates were artificially low because of this natural re-aging process.

5) Hard and Fast Rules – Lenders attempted to stop the fraud problem by putting data checks and validations into place.  For example, lenders implemented processes to check pay stubs and borrowers social security numbers against public records databases.  There was a feeling that fraudsters would keep doing the same things that they had always done and that they could stop the fraud.  But this wasn’t the case, lenders relied too much on non-dynamic fraud tools and processes which were easily overcome by the clever fraudsters.

6) The Belief that Fraud Doesn’t Exist – Mortgage lenders rarely detected their fraud so they never reported it.  Because they never reported it, the believed that it never actually existed.  But they were wrong.  Fraud did exist and it was hidden in their early payment default losses.  Studies indicated while reported fraud losses were low, hidden fraud losses were in fact high.  Studies conducted in 2004 indicated that between 30% and 70% of early payment default losses had fraud in the original loan file.  Fraud was simply hidden in the lenders early payment default populations and they did not know about it.

The mortgage industry took these learnings and applied some really great technologies and processes to reduce fraud.  They began adopting fraud scores, pattern recognition technologies and fraud reporting.  They became experts in detecting fraud and they were successful.  As a result mortgage fraud losses dropped by 50% between 2008 and 2010 based on industry studies.

So What is Auto Lending Fraud?

Auto Lending fraud is unique but in many ways similar to industries such as mortgage.  There are about 8-10 primary types of auto lending fraud that impact lenders.

Income Fraud – Income Fraud is one of the most common types of auto lending fraud and it occurs when borrowers or borrowers coached by dealers inflate or outright lie about their income.

Employment Fraud – Employment fraud is commonplace in auto lending.  When borrowers lie about about their employer or employment status this is considered employment fraud and it impacts the performance of the loan.

Identity Theft – When borrowers use a social security number or identity that is not their own this results in identity theft and it has historically been a pretty sizable problem for auto lenders.  Since 2009, lenders have achieve far few losses by using external tools such as Lexis Nexis to verify identity and social security numbers.

Straw Borrower Fraud- The third most common type of fraud is straw borrower fraud.  This occurs when a borrower is either recruited by an unscrupulous buyer or broker to act as the purchaser of the car so that the real party can be hidden.  The straw borrower can be a family member or in some cases someone unknown to the actual borrower.  Straw borrowing is often confused with identity theft since the results are often the same.

Dealer Fraud  -  Dealer fraud may be less common, however the impacts are far greater.  Lenders report to PointPredictive that used car auto dealers often represent their highest risk factor when determining a loan.   Dealer fraud occurs when a dealer or finance manager systematically manipulates or coaches borrowers to misrepresent information on their applications.  Lenders report that less than 10% of their dealers represent an overwhelmingly majority of all of their fraud and early payment default risk.

Collateral “Stuffing” Fraud – Manipulation of the car value through a variety of methods including add-ons that never existed is fairly common with instances of auto lending fraud.  Since the collateral value dictates the amount of money that is leant on an automobile, collateral fraud is often one of the most damaging fraud types to lenders.

Excessive Dealer Markups – When dealers systematically markup loans against certain borrowers such as subprime or elderly borrowers this can be a big risk to lenders.  While it is not necessarily considered fraud it is oftentimes closely associated with fraudulent dealers.  Dealers with excessive markups may be more likely to be engaged in dealer related fraud.

Odometer Fraud – Odometer fraud which is has been declining is another example of fraud against lenders.  If odometers are rolled back the lenders are likely to value the collateral too highly and loan too much money on a vehicle.

Yo Yo Fraud – Yo Yo fraud occurs when a consumer is given temporary registration for a car and drives the car off the lot but the dealer later changes the terms of the sales contract forcing the buyer to accept the new terms.

What are the Cost of Auto Lending Fraud?

There are currently no industry reported fraud losses due to auto lending fraud.  But PointPredictive is analyzing the cost of fraud with lenders that are contributing to the auto fraud consortium.

There are several things that we are learning in our analysis.  We believe that auto lending fraud is running anywhere between 10 to 50 basis points of origination volume in fraud based on the portfolio and business practices.

Early Pay Default Losses are Linked to Fraud – There is some evidence to suggest that approximately 30% of early payment default losses may be related to fraud in the original loan file.  Loans that default within the first 90 days after origination and never cure have a very high correlation with fraud.

Less than 10% of Dealers Account for Most Risk –  Based on lenders surveyed and extensive data analysis, PointPredictive believe that between 3% and 10% of dealers represent an overwhelming majority of that lenders fraud and early pay default risk.  This finding is important because it follows closely with the experience of the mortgage lending industry with brokers.

Fraud Losses are Increasing with Subprime Boom – As the subprime lending industry booms, fraud losses are on the rise.  Experian reports that early pay default losses are rising to their highest levels since 2008.  PointPredictive believes that the eroding loan quality is partly due to increasing fraud on the application.

Exposing the Hidden Risk of Auto Lending Fraud

PointPredictive performs retroactive analysis to help lenders determine their fraud losses.  By using pattern recognition models built by trusted fraud scientist, PointPredictive is able to provide a lender with an independent view into their fraud risk exposure.  There are 3 primary ways PointPredictive provides the service

1) Application Fraud Scoring Model – Using millions of historic applications across lenders, we have created a sophisticated scoring algorithm that determines the probability that a loan contains material misrepresentation.  Each application in a portfolio can be scored and ranked according to risk.  PointPredictive than benchmarks the portfolio against other lenders in the consortium

 2) Default Probability Scoring Model – PointPredictive has also created a Default Probability Scoring Model which can determine the likelihood that an auto loan will default within the first 6 months.  By analyzing the early payment default population, a lender can determine if their fraud risk is also elevated.

3) Dealer Scorecard and Benchmark – Based on historical data from thousands of dealers nationwide, PointPredictive has created a predictive dealer scorecard which ranks each dealer according to their risk level.  The risk model scores each dealer every time a new loan is submitted so lenders can determine how to handle the dealer and the loans that they are submitting.

Best Practice Implementation

PointPredictive Fraud Consultants have worked with over 150 financial institutions and lenders worldwide.  By working hand in hand with lenders consultants have been able to reduce fraud losses and exposure significantly and in some cases have been able to save lenders in excess of $80 million dollars in fraud loss annually.

To reach us, please feel free to contact Frank McKenna at fmckenna@pointpredictive.com

Thanks for reading!