Imagine lending money to a company and not knowing if they have substantial hidden federal tax debts. Would you be shocked if we told you we see bankers doing this all the time? And it costs them millions.
Why? Simple: they’re not checking all the boxes.
For decades, bankers have conducted their typical due diligence when assessing a potential borrower — tax returns, bank statements, and so forth. But the reality is, lenders have ignored one of the most significant credit risks that are often hidden from the balance sheet: federal payroll taxes.
The SBA lent out almost $23 BN in 2019 alone — they can’t afford to lend money to companies with misleading financial assessments. Banks need to know if a business has actually been paying their payroll taxes — as failure to do so is one of the largest indicators that a business has trouble keeping a regular cash flow.
How does this happen?
For more than 20% of the companies that have outstanding payroll tax debts owed to the federal government, there’s no tax lien filed. For the other 80%, the information that lenders receive from the IRS is at best, many months behind and at worst, mislabeled, and can drastically alter how bankers view the financial health of a business. When bankers are analyzing credit risks, they’ll often use the antiquated process of searching public records for federal tax liens to determine if the business is paying its tax obligations.
Suppose you only ignored a company’s stock performance for the last 16 months (including the entire pandemic) — that’s effectively what lenders are doing when they look at a tax lien. A run-of-the-mill search will only show the amount owed on the lien when the lien was filed. Depending on when the search is done, the debt amount could actually be much higher. A simple search provides an incomplete and often inadequate picture to the underwriter.
Payroll tax is the most predictable indicator of cash flow problems.
When a company starts to have cash flow problems, as many have in the past year, often the first expense they ignore is the IRS, because it’s the last one to have consequences.
Think of it this way: if a business doesn’t pay their employees, they don’t show up. If vendors don’t get paid, they stop servicing. If you’re a small business trying to cut costs to secure your future in a post-pandemic world, the repercussions for not paying the government are the easiest to push aside.
It’s a temporary band-aid that will be resolved in the near future, right? Maybe, but the problem is the correlation that exists between the moment companies stop paying their payroll taxes and the ones who eventually default on their loans. Tax Guard’s data shows that companies who see a 10-15% decrease in their payroll tax deposits have nearly a 50% chance of eventually defaulting. The emergence of payroll tax compliance insight proves why tax data is becoming one of the most predictable indicators of cash flow issues.
For lenders, it’s not an intentional misstep. Many believe they’re following the proper procedure with a public records search for tax liens — but this type of search will show an incomplete picture 20% of the time — it’s now possible to go deeper and gain more useful insights into the health of a borrower. With the increasing scrutiny placed on cash flow as small businesses move towards recovery, unpaid tax debts should be a red flag for bankers to review thoroughly.
Thankfully, we can see the light at the end of the seemingly endless COVID-19 tunnel, and the picture for small businesses seems a bit brighter. On the heels of a $1.9 trillion COVID-19 relief initiative, expect consumers and small businesses to start spending again and applying for loans that can help sustain their future.
The bottom line
History tells us that for lenders it will keep coming back to unpaid payroll taxes (as well as other off-balance sheet liabilities). It’s an issue that we’ve seen come back to haunt lenders over and over again, and there’s no doubt that as small businesses begin to make their rebound, uncovering hidden tax debts will become an increasingly crucial data point to identify and monitor.
