CARES Act Funding Demonstrates Oversight Challenges in Reducing Fraud

Since the Coronavirus Aid, Relief, and Economic Security (CARES) Act was signed into law in March, government agencies have been scrambling to distribute more than $2 trillion in economic relief funds and other assistance to stem the impact of the COVID-19 pandemic.

In doing so, agencies need to strike a careful balance of being both quick, to get funds in the hands where they are needed, and careful, to ensure funds don’t fall victim to waste, fraud, and abuse.

With the unprecedented scale of this relief effort comes huge potential for widespread fraud and abuse. Recognizing this, Congress has created a robust oversight arm, led by a special inspector general, with expanded authorities to conduct audits and investigations and bring civil and criminal enforcement actions as needed.

Emergency funding is a top target for fraudulent and criminal activity

Nevertheless, without proper information at hand, there will inevitably be problems in implementation, as we have already seen:

  • In May, the Justice Department charged two businessmen with filing fraudulent bank loan applications seeking more than a half-million dollars in forgivable loans guaranteed under the CARES Act.1
  • In April, the Health and Human Services Department distributed $30 billion in stimulus payments to healthcare providers. The news agency Reuters reported that more than a dozen of those healthcare providers that received funds are facing civil or criminal inquiries.2

These news stories highlight the shortcomings of distributing government funds with insufficient or inconsistent data. It’s a tough challenge, as oversight bodies must use data analysis methods that are very much focused on real time observations—since, during a crisis, one often does not have easily referenceable historical data from which to learn. Relying on trustworthy, harmonized data, and analytics will enable agencies to adjust decisions and reactions in real time.

These positive stories are important for the public to know and often get overshadowed by news of waste, fraud, and abuse.

The agencies administering these funds — and the oversight bodies ensuring the integrity of their dispersal — have one other important responsibility besides distributing this money quickly and mitigating any associated risks. They must also be able to tell the positive story of how CARES Act funding is actually making a difference in resuscitating struggling businesses. These positive stories are important for the public to know and often get overshadowed by news of waste, fraud, and abuse. So it’s important for agency leaders to forecast the impact of recovery funding, such as rapid loan distributions to the small business community, and share these projections with the public and government oversight bodies.


Priority number one: get the right data to prevent fraud before it happens

The solution to achieving the goals defined within the CARES Act lies in data and analytics. When the right datasets are viewed through the right analytics and applied with the right subject matter expertise, then government agencies and their overseers can answer the most critical questions: Who is receiving funds? What is the likelihood that they are legitimate or illegitimate recipients? Which companies present the greatest risk of fraud? Which companies are most in need of funds and would have the greatest impact on the larger economy? Where should we focus our limited resources for further scrutiny? What impact are these funds having in helping struggling companies?

There are several important features needed in any data-based solution that agencies and oversight bodies rely on to meet these responsibilities. First, it is critical that the data used present a holistic view of the companies and organizations being reviewed and monitored for federal relief.

Assembling a detailed, holistic picture of a company enables you to look at it in many ways and address multiple indicators of potential risk. For example, working with disparate datasets, one can understand a lot about any particular company: whether it is foreign owned; whether it is located in a high-COVID impact area (and therefore may have more a more dire need for federal assistance than other companies); the number of employees it supports; the degree of financial stress it is experiencing; whether it poses any degree of fraud risk; and its dependencies with other companies from a supply chain perspective; just to mention a few. Having a holistic data picture of any company also enables investigators to alter their analytics lens as needed to adapt to ever-changing fraud tactics.

The data used should also be as close to real time as possible so agencies and oversight bodies have the most current information with which to make decisions.

Finally, oversight teams will need to continuously monitor information about funding recipients so they can spot troubling anomalies and patterns in real time, as well as be able to see how relief measures are making a difference for struggling companies and the economy more broadly.

Even beyond the remit of the CARES Act, many traditional federal programs — including small business assistance, emergency management initiatives, and block grants, among others — will also be endeavoring to repair the damage we see today from COVID-19 for the next few years. As we bounce back and rebuild the economy, we’re not just looking to reduce risk and increase program effectiveness, we also need to be able to tell powerful stories about the benefits of stimulus funding. Agencies and oversight bodies need to produce indisputable information that articulates how public funds are improving our communities, supply chains, and overall national economic health. The solution begins with the identification of the right data and predictive insights to reduce risk, fill information gaps, and run evidence-based recovery programs.