Quantifying the Problem of Income Misrepresentation in Lending

It’s been around since the dawn of modern lending.  It’s more common than any other type of fraud. It gums up the lending process by creating additional expense and delays.  And its impact on consumers, lenders and, in some cases, the economy is far greater than many would ever expect.

I am talking about income misrepresentation – when borrowers lie about how much they make in order to qualify for a loan.  And when I say borrowers, let me make it clear that sometimes it’s the dealer or finance manager that does it “for” the borrower (sometimes without the borrower even being aware).

Now income misrepresentation may seem commonplace – who hasn’t fudged their income a few dollars here and there in the past?   And it may seem harmless.  After all, the borrowers are real people, not identity thieves, and have all the best intentions of making their payments.

But if you think income misrepresentation isn’t a serious problem, then I encourage you to think again.   It is … and it has substantial impacts on the entire lending process.

Here are seven statistics that tell the story:

#1 – Up to 33% of Borrowers Overstate Their Income by 15% or More

Income misrepresentation is surprisingly common.  To understand how common, Point Predictive analyzed 1.2 million auto loan applications where stated income had been manually verified by lenders through documentation or database checks.   In order to differentiate serious income misrepresentation from small fudging or “rounding up” of incomes, we determined that if the stated income was inflated by fifteen percent or more, it was considered a material misrepresentation.

The analysis revealed that one in five (21%) borrowers materially inflated their income.  In fact, some lenders verified information indicated that nearly one-third (33%) of their borrower-stated incomes were materially inflated.

The effect of this high rate of income inflation is substantial. It gums up the entire lending process. As more borrowers misrepresent their income, it affects the ability of the lender to determine if the borrower can afford the loan.  In response, lenders end up placing more stipulations on loans requiring borrowers to supply proof of their stated income.    This slows down funding, upsets truthful borrowers, and creates a mountain of verifications for lenders to work through.

#2 – In Contrast, only 6% of Borrowers Understate Their Income

If overstating income was just a simple oversight or mistake, that would be one thing – but data analysis suggests otherwise.    In the same analysis of verified incomes, Point Predictive reviewed borrowers that understated their incomes by 15% or more.

We found that far fewer borrowers understate their incomes to lenders (on average, only 6% of borrowers compared to 21% of borrowers that overstate).  The dramatic difference between understating and overstating incomes seems to suggest that borrowers are more apt to inflate their income because it works in their favor.    If income misrepresentation was just an innocent mistake, then we would expect to see just as many borrowers materially understating their incomes as overstating. But that is simply not the case.

#3 – Income Misrepresentation is Increasing Over Time

The data analysis of verified incomes further revealed that income misrepresentation appears to be increasing over time.  In 2016, 21% of borrower’s incomes were overstated but that rate increased to 26% in 2017.

That is a 24% relative increase in overstated incomes and it appears the trend is continuing into 2018. The primary drivers of higher rates of overstated incomes could be a combination of more borrowers attempting to qualify for loans combined with high car values and more expensive monthly payments.

#4 – Up to 1 in 5 Paystubs Are Forged or Created using Internet Tools

Because stated income is so notoriously unreliable, lenders often require proof of a borrower’s income in the form of paystubs or bank statements.

But in many cases, income documentation is just as unreliable as the stated income itself.  Some lenders report that 1 in 5 paystubs that they receive are either forged or generated on the internet with questionable or falsified information supplied.

The growth in internet sites that provide paystub templates that can be customized in just 5 minutes and cost less than $10 is the primary driver of the explosive growth in fake pay stubs.

#5 – 41% of Early Pay Defaults Would Have Had Income Alerts at Time of Application

The impact of inflated incomes can also be seen in the evaluation of lenders’ losses.  Point Predictive data scientists analyzed early payment default losses on millions of funded loans to determine how many had patterns of income misrepresentation on the initial application.

We determined that more than 40% of those loans that defaulted within the first 6 months would have triggered an income alert at application time indicating that the borrower’s stated income was inflated by 15% or more.

The impact of income misrepresentation stretches far beyond the application – it impacts loan quality and the payment performance of the loan.

#6 – Auto Lenders Indicate It Is Their #1 Fraud Type

In the 2018 Point Predictive Auto Lending Fraud Survey, most lenders surveyed by Point Predictive chose Income Fraud as their #1 fraud issue.   While synthetic identity fraud and dealer fraud are also listed as high-risk issues – income fraud is by far the single most damaging type of fraud.

#7 – Most Borrowers Don’t Misrepresent Their Income, But They Are Still Affected

On average, nearly three-quarters of all auto loan application contains accurate borrower-stated income (plus or minus 15% of actual, verified income).  However, as is often the case, a few bad apples spoil the bunch – this is certainly true as it relates to income fraud.  As a preventive measure, some lenders stipulate 100% income validation (through documentation or database checks) knowing that the vast majority will be perfectly fine.  And this is where most of the fallout of income misrepresentation occurs – the impact on good borrowers.

In the end, all borrowers are disrupted based on the actions of a few.

New Technologies are Emerging to Fight Income Fraud

Lenders have historically relied on two primary methods for fighting income fraud – requesting proof of income through documentation (such as pay stubs or validating incomes through shared employer-sourced databases.  Both of these approaches have proven to provide benefit,  but they also have their limitations.   Documents can be forged; shared databases are only as effective as the number of matches that can be found.

To address the issue of income fraud, Point Predictive has launched Income Validation Alert. The solution offered by Point Predictive, analyzes application data (including the borrower’s stated income) to predict if the income is inflated by 15% or more.  It allows the streamlining of low-risk incomes to bypass STIP and verification process while targeting the applications with the riskiest incomes.

An infographic of income misrepresentation statistics from our scientist –  Income Misrepresentation Statistics.