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A Systematic Examination of PPP Loans
for Potential Fraud

Over $670 billion has been allocated by Congress under the Paycheck Protection Program (PPP) to help small businesses cope with the COVID-19 pandemic. Shortly after the launch of the program, media outlets began reporting on specific and isolated incidents of borrower fraud. The private nature of small business financials makes it difficult to accurately assess how widespread this problem could be.

 

Integra FEC is an economic consulting firm that specializes in forensic data analysis to identify and analyze financial fraud. Using datasets released by the SBA and the IRS, Integra has conducted an analysis that focused on nonprofit PPP borrowers and their prevalence of potential fraudulent borrowing.

 

Based on a conservative analysis, we identified at least $771 million in PPP loans issued to 1,068 nonprofits as highly suspicious, of which $212 million were beyond what could be justified by the nonprofits’ financials on file with the IRS. This represents at least 3.6 percent of PPP nonprofit loans. Additionally, our analysis discovered several specific patterns:

  • Certain lenders have a significantly higher percentage of suspicious loans as flagged by our methodology.

  • Loans made during Round 2 of the PPP have a higher rate of being flagged as suspicious compared to loans made in Round 1 of the PPP. Additionally, loans made in the later part of Round 2 are more suspicious than loans made in the earlier days of Round 2.

  • Nonprofits with higher executive compensation compared to total compensation are also more likely to have suspicious loans.

  • Nonprofits that received PPP loans with higher loan value per job retained are more likely to have suspicious loans.

  • Nonprofits that appear to inflate the number of jobs retained on their PPP application are more likely have suspicious loans.

  • Certain sectors and states are found to have a significantly higher percentage of suspicious loans. For example, over 16 percent of loans to nonprofits in the real estate sector and over 12 percent of loans to nonprofits in the information sector are flagged as suspicious.

 

Our analysis applies several conservative assumptions, including that we consider the lower bound of SBA-reported loan values throughout our analysis. For example, if the loan size reported by the SBA is $5 to $10 million, we assume a loan value of $5 million in our calculations.

 

On the other hand, our report has some caveats. First, we strictly rely on the accuracy of the PPP data released by the SBA. Potential data inconsistencies have been analyzed by some members of the press but have not been confirmed by the SBA. A second potential caveat to our analysis is that it is limited to only comparing SBA loan sizes to a nonprofit's Form 990 financials, which may not capture all treatments of qualifying employees, affiliates, and payroll expenses. For example, it is possible that a nonprofit has affiliated entities that would justify a higher loan amount than would be justified solely based on its Form 990. These data limitations are mitigated but cannot be completely accounted for without private tax and financial documents.

 

As additional analyses, we also find that at least $6 billion was lent to companies that reported exactly 500 jobs retained, including 24.9 percent of all nonprofit and for-profit loans with loan value between $5 to $10 million. This is particularly significant since most businesses would not have qualified to borrow under the PPP guidelines if they employed more than 500 employees. Integra also finds an abnormally high number of loans that report a round number, such as 100 or 200, or a number with a unit place of a 0 or 5 for the number of jobs retained. Both of these findings suggest that reported employee figures are not being correctly reported by borrowers, though it is unclear whether these types of potential misstatements would be material to the amount of funds received.

 

To learn more details about our results and analysis, please visit this link to download the report.

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