Firm Insights

Data In, Data Out: Concerns Around PPP Loan Data Accuracy

On Monday, September 1, members of the House of Representatives’ Select Subcommittee on the Coronavirus Crisis (the “Subcommittee”), tasked with overseeing the implementation and effectiveness of the Paycheck Protection Program (“PPP”), issued a memo reporting a lack of oversight, leading to “billions of dollars being diverted to fraud, waste, and abuse . . .” in connection with PPP loans. Such report is not a surprise, especially after the Governmental Accountability Office predicted that:

“Because of the number of loans approved, the speed with which they were processed, and the limited safeguards, there is a significant risk that some fraudulent or inflated applications were approved. In addition, the lack of clear guidance has increased the likelihood that borrowers may misuse loan proceeds or be surprised they do not qualify for full loan forgiveness.”

While concerns with a lack of oversight and guidance have been repeatedly documented, the extent of the potential fraud, waste, and abuse arguably cannot be accurately measured, due to a lack of reliability of PPP loan data. After the Small Business Administration (“SBA”) and Treasury released detailed PPP loan data to Congress and the public, many lawmakers, bankers and businesses raised concerns about the accuracy of the data (read the story that triggered the idea for this post here). As the LA Times reported:

“Bloomberg News spoke to more than a dozen companies that, according to the government, received loans of more than $1 million with a reported one job retained. The borrowers all said there were mistakes in the data set.”

For those who have not perused the PPP Loan Forgiveness Application lately, the application requests a significant amount of data—especially for those borrowers seeking to take advantage of the safe-harbor provisions to avoid reduction in forgiveness. In processing these loan forgiveness applications, the SBA will gather a massive amount of data, just waiting to be scrutinized, analyzed, and compared to other governmental data sets. Several questions arise, including: Should we be concerned with an enforcement strategy focused on data analytics?
Interestingly, applicable borrowers able to use the EZ PPP Loan Forgiveness Application—which the SBA estimates to be ¾ of all PPP loan borrowers—will not be required to report as much data as borrowers having to use the traditional PPP Loan Forgiveness Application. But will that save such borrowers from the concerns outlined throughout this blog post? For example, this past June, Damon Rowe, director of the Fraud Enforcement Office of the Internal Revenue Service, announced the formation of an Emerging Threat Team (the “Team”). The Team’s priority list includes issues relating to the PPP. According to Rowe, the Team, in conjunction with the SBA, has begun developing techniques to verify the information reported by businesses and individuals. Specifically, the Treasury plans to compare PPP borrowers’ loan and forgiveness applications with the borrowers’ Form 941 employment tax returns to find any inconsistencies within the information reported.

But with errors in the PPP data, those tracking, relying, and reporting on the data, and those borrowers for whom the SBA’s data is inaccurate have serious concerns.

To us, one of the more significant issues arising from the inaccuracies in the PPP data is the effect of such mistakes upon governmental efforts to oversee the expenditure and receipt of PPP funds, which we previously wrote about here.

The benefit of—as well as public confidence in—oversight is only as strong as the accuracy of information upon which the analysis is based. And as the world has become more comfortable with “big data”, where sophisticated models are being used to detect trends, compliance and fraud, so, too, has the government. The IRS and the Department of Justice are currently using data analytics to spot trends and detect fraud with respect to the PPP and related CARES Act programs. But such techniques to detect fraud quite literally depend solely on the data, and the inaccuracy of such data may deceive investigators and lead to results that miss the mark. Here, errors in the SBA’s data may cause unwarranted scrutiny of compliant borrowers while raising questions as to whether unscrupulous “borrowers” are avoiding detection. In other words, even if the data “going in” that is provided by borrowers through their PPP Loan Forgiveness Applications is accurate, the data coming “out,” is proving to not always be accurate and, therefore, unreliable. And yet government agencies and governmental oversight programs are relying on such data to detect fraud—as the Subcommittee’s September 1 report, discussed above, likely did. How the SBA and oversight agencies will address this concern remains to be seen.

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