How Agencies Can Better Combat Fraud in Federal Programs

The global crisis brought on by the COVID-19 pandemic is unlike anything we’ve experienced in recent history. Few of us were here during the 1918 flu pandemic and while most of us have seen the impacts of the 2008 financial crisis, multiple natural disasters and trade wars, nothing prepared us for the dramatic ripple effects of this pandemic on our nation, our economy and our people. 

In March, Congress signed the Coronavirus Aid, Relief, and Economic Security Act into law, quickly releasing more than $2 trillion in economic relief funds and other assistance to stem the impact of the pandemic. While the intention of CARES Act funding was to support businesses and communities affected by the pandemic, it quickly became evident that some funds were distributed to fraudulent parties.

Recognizing the potential for abuse, Congress created a robust oversight arm, led by a Special Inspector General for Pandemic Recovery, with expanded authorities to conduct audits and investigations and bring civil and criminal enforcement actions as needed. Nonetheless, the unprecedented scale of the relief effort brought huge potential for widespread fraud. In one egregious example, on May 13 the Justice Department filed charges against a reality TV personality who obtained more than $2 million in Paycheck Protection Program funds designed for small businesses and spent more than $1.5 million on jewelry and child support payments, among other things. There have also been numerous cases of individuals applying for PPP loans, claiming they need the money to support employees who don’t actually exist. 

Fraudsters have become more sophisticated in their tactics, making it hard to predict their actions. They take advantage of the short timeframes the government has to take action after payment is distributed. And in certain scenarios, the government has to pay out the money and then selectively choose who to chase to recoup misdirected funds, instead of denying payment up front. Fraudsters know that if they can spend the money and disappear before the government decides to pursue them, they’ve won.

Best Practices for Fraud Prevention

With the third wave of COVID-19 cases building across the nation, the White House and lawmakers are considering additional relief funding. So how can the government prevent further fraudulent activity from taking place? 

When building a framework for analyzing and mitigating risk, a best practice is to use the five Cs of fraud prevention. They provide a conceptual framework for building systematic, vigorous and comprehensive due diligence into an agency’s existing controls and information systems. The five C’s are:

1. Confirmation: Make sure the company or person actually exists.
2. Condition: Check if the company has the hallmarks of a normal, functioning business.
3. Consistency: Assess whether the stated facts about the business are consistent with other sources of information.
4. Character: Discover whether any past issues could impose risks on the transaction.
5. Continuity: Determine whether the company’s operational status has changed and might pose new risks.

The best way to build out the five Cs is by applying data and analytics to rapidly identify potential fraudsters among a large group, before payment is issued. To do this effectively, data scientists need a vast body of current, global, business activity data signals, including accounts receivables, inquiries by businesses on businesses, beneficial owner data, network traffic data and firmographic data. Any database that falls short of such data likely won’t provide enough information to find anomalies in interactions between and among businesses. 

When applying the right data science, analytics, and datasets, government agencies and oversight bodies 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, based on industry or high-impact COVID-19 areas? Where should we focus our limited resources for further scrutiny? What impact are these funds having in helping struggling companies? 

A government agency with the right data analytics system in place can quickly access a loan applicant's billing and invoice activity to verify that it is a genuine business operation.

It is critical that government agencies, inspectors general and oversight committees such as the Pandemic Response Accountability Committee continuously monitor their data. This will allow them to spot troubling anomalies and patterns as well as be able to see how relief measures are making a difference for struggling companies and the economy more broadly. 

Adopting such data-driven approaches are not only important to those implementing and overseeing CARES Act programs, but to the many older federal programs—small business assistance, emergency management assistance, block grants, and more—that also need to use data and analytics smartly to ensure their financial programs adequately deliver on their missions, from rebuilding communities to improving supply chains and boosting the nation’s economic health. 

Using more data-driven, diligent practices will help reduce risk, fill information gaps and ensure more effective evidence-based recovery programs today and in the future.

Erik Ekwurzel is the chief technology officer for government solutions at Dun & Bradstreet.