How to Identify and Monitor the Risks of PPP Loan Fraud

As the COVID-19 pandemic forced many businesses to temporarily close, millions of workers found themselves suddenly out of work — and out of a paycheck. To mitigate the effects on workers’ finances, companies’ ability to stay in business, and the general economy, Congress took swift action to implement the Paycheck Protection Program (PPP). PPP is a relief effort designed to ensure workers will continue to be paid during pandemic-forced closures. 

The PPP was a step in the right direction, but no good deed goes unpunished. Even in times of crisis, fraudsters stand ready to take advantage of vulnerable individuals and businesses, and the COVID-19 pandemic has been no exception.

Financial institutions that serve businesses with PPP loans are facing multiple challenges and risks associated with the lending and forgiveness process, particularly in determining the veracity of loan claims and how funds are being used. 

Exploring PPP-Related Fraud Risks 

Though the PPP program is barely two months old, banks are already finding that it’s a customer service minefield. Businesses in dire need of funding aren’t likely to be forgiving when their needs aren’t met. 

So far, complaints of preferential treatment, long hold times at call centers, and lack of guidance in administering the program have surfaced, and potential future rounds of funding could further muddy the waters. 

On top of the existing economic challenges, banks are facing a number of additional risks, including:

Fraud Risks

It’s estimated that PPP fraud could reach as high as 12%, according to the U.S. Department of Justice. Assistant Attorney General Brian Benczkowski notes that when a surge of $1 trillion enters the streets, fraudsters come out of the woodwork to try and claim a piece of it. PPP fraud could increase through identity theft and weak risk management frameworks. If a bank employee becomes involved, the risk for PPP fraud also increases.

Bad Debt Risks

One of the hallmarks of the PPP is the ability to apply for loan forgiveness, depending on how the funds are used. However, loan amounts that are not eligible for forgiveness may carry a higher risk of future default. 

Operational Risks

Operational challenges abound when issuing a high number of loans in a short period of time, particularly in hard-hit areas where small businesses make up the backbone of the local economy. Banks may find it difficult to process loan applications in a timely manner while doing their due diligence, along with navigating new forms and handling overwhelmed call centers.

Compliance Risks

Speed is a major factor in the role of PPP. Small businesses and their employees need loan money quickly, and banks are determined to deliver funds as soon as possible. However, this also means that some compliance measures may be overlooked in the process. What’s more, the volume of loan applications could expose compliance gaps or vulnerabilities. 

Reputational Risks

Banks engaged in issuing PPP loans face reputational risks in the event they must deny a loan application or experience issues in processing applications. Reputational risks are amplified if the bank draws negative attention from the media in regards to PPP loan handling.

It’s important to note that when pre-loan risks (specifically operational and fraud risks) are mitigated, other risks are mitigated, as well.

Identifying Red Flags Associated with PPP Fraud

Red flags regarding PPP loan fraud can manifest during the application phase or when it’s time to determine loan forgiveness. Banks should monitor data at both stages to identify potential instances of fraud and hold applicants accountable. These red flags include but are not limited to the following:

Application Stage Red Flags

• Inflated payroll – applicants may inflate payroll to qualify for a higher loan amount (loan amounts are based on 2.5x the cost of payroll). 
• Business size – the PPP is designed for small businesses with fewer than 500 employees.
• Coordinated crime rings – multiple applications are submitted from eligible businesses using phished information.

Forgiveness Stage Red Flags

• Lack of documentation – businesses must provide proof of how loan funds are used to determine how much of the loan will be eligible for forgiveness.
• Identity theft – loan funds are funneled into an account with a different name than the applicant or business (can also be a red flag at the application stage).
• Errors in forgiveness application – borrowers may try to manipulate funds or documents to meet forgiveness eligibility.

What Banks and Lenders Can Do to Mitigate PPP Loan Fraud

When viewing PPP loan fraud risks at the surface level, it can be difficult for lenders to identify risks in real-time and differentiate suspicious activities from real fraud attempts. Rather, banks and lenders should rely on data-driven activities that can monitor risks and fraud attempts at scale and address each threat in real-time without having to review individual applications. In doing so, banks are positioned to improve operational efficiency while reducing financial risks to the institution.

DataVisor’s machine learning is being used to monitor PPP loan fraud and respond to red flags in real-time. For example, the machine learning solution can help to identify applicants that were not in business at the designated PPP date (February 15, 2020) or not aligned with their typical payroll costs or business size. 

It also takes a holistic approach to data monitoring to identify correlated fraudulent applications that use valid data that might otherwise not be triggered by fraud detection systems. DataVisor’s unsupervised machine learning doesn’t rely on labels and historic data, allowing it to identify patterns in real-time on a large scale to combat application fraud.

The PPP is a new territory for everyone, and it came so quickly that many banks had to act fast to accommodate their customers. In doing so, fraudsters may have already slipped through the cracks to obtain loan funds. But banks still have a chance to mitigate the impact at the forgiveness stage, as well as future rounds of funding and other loan transactions. By developing a better understanding of your data through patterns and big-picture insights, UML can help fight back against fraud, minimize risks, and deliver outstanding service to your customers.