While the Paycheck Protection Program is intended to help keep businesses afloat during the economic uncertainty of the pandemic, the impact of those looking to take advantage of the system can reach the local level.
The federal government moved quickly to stand up programs to blunt the economic impact of the COVID-19 pandemic. This was a tremendous undertaking that provided needed financial support to hundreds of millions of Americans. Still, it would be unrealistic to think that such a large-scale effort could be implemented so quickly without any glitches. Unfortunately, fraudsters, both domestically and worldwide, saw this as an opportunity, impacting not only CARES Act funds but Unemployment Insurance (UI) assets, as well. The scope of the issue is vast: Washington state reports up to $650 million in UI money stolen by fraudsters and Maryland has identified more than $500 million in UI fraud.
The Small Business Administration’s (SBA) Paycheck Protection Program (PPP) is intended to keep businesses open by providing forgivable loans to employers to keep workers on the job. However, SBA has been challenged by numerous applications from nonexistent small businesses — duly registered at the state level — claiming they have employees to keep on payroll. Also, some actual small businesses falsified their qualifications for PPP loans, misrepresenting the number of employees and expenses.
While states have no vested interest in PPP funds themselves, fraud has an impact down to the local level:
Through these techniques and more, fraudsters can directly affect state and local resources and tax revenues, while delaying UI payments to legitimate applicants.
“Pay-and-chase” could potentially lead to the recovery of a portion of the lost funds, but historically, a large percentage of fraudulently obtained dollars is never recovered. Pay-and-chase also has its own costs: The original money is gone, and now you have to spend more — in time, resources and personnel — to try to recoup it. Of course, there is also the deterrent value of chasing down fraudsters, but with limited resources available to auditors, the likelihood is that the majority of that money is unrecoverable.
Businesses don’t commit fraud; the people who run those businesses — legitimate or otherwise — do. It’s essential to make sure the applicants are who they say they are, that their businesses are genuine, and that their employees actually exist and work for them.
True, banks are important parties in the loan application process, but the issue starts with state registration, where new businesses register with the Secretary of State and other offices at the city or county level. It’s relatively easy for fraudsters to use stolen identities and fabricated information to create a realistic business entity, complete with management personnel and officers. It’s up to agencies to determine if any or all of the information submitted is true. Historically, this has been tough to do: Research by LexisNexis Risk Solutions shows that only 50 percent of small businesses have a credit history, and half of those with a history only have thin files. Once the business is registered, that information can flow to federal agencies, including the SBA as it reviews PPP loan applications.
The same set of identity issues need to be dealt with when processing UI applicants. Unfortunately, it’s very easy to create an identity that looks real. Online resources exist to falsify an ID or driver’s license, utility bills and pay stubs, so that an applicant can appear legitimate. Stolen or synthetic identities are also being used, which adds to the confusion, as some or all of the information being used about that person is real. The result is that, ultimately, stimulus and UI funds can end up in the wrong hands, leaving the government to recover it from someone who doesn’t exist. These identities may also be used to obtain assistance and benefits through additional state-run programs, as well as to apply for UI and assistance in other states altogether, creating the issue of dual participation.
Preventing fraud requires a judicious, intelligent process that screens applications for business registrations and UI at the earliest possible stage. Most states have systems in place for this, not only for approving business licenses and UI, but also for disaster contingency programs, which require funds to flow quickly from the state or locality to people and businesses. The current environment, however, has made things more complicated, since offices may have limited resources and many applications are completely online to ensure social distancing. But whether in person or digitally, vetting the identities of applicants with confidence can only be done with a comprehensive set of accurate, up-to-date data sources.
Connecting a person’s physical identity — their address, birthdate, Social Security number, etc. — with their digital life — their online activity and where, when and how they interact online — is crucial for building risk scores, which support well-informed decisions on how best to apply limited resources to the issue of fraud. A system that provides real-time identity intelligence and pattern recognition in near-real time would not slow down the application process; in fact, it would improve turnaround time, since less manual vetting is needed.
With a PPP programs extension, the ability to apply for loan forgiveness and the likelihood of another round of stimulus on the way, the opportunities for continued PPP fraud may be growing, further straining citizens, public resources and the economy. A multi-layered physical and digital identity intelligence solution, powered by comprehensive government and commercial data sources, means approvers can more quickly — and more accurately — sort legitimate applicants from scammers by automating the process using a comprehensive data solution. And that helps ensure that funds go where they are needed most to support hardworking people in every state. Hopefully these critical safeguards will be implemented in disaster-ready solutions so we are not chasing taxpayer money next time.
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