Slashing review time in half = more results

Our mission is to safeguard taxpayer dollars through data-driven reviews of pandemic relief programs. To support our partner overseeing a new $150 billion program, we implemented two solutions: one that halved their review time, despite being understaffed, and another that identified billions in potential savings by analyzing which recipients were most at risk of misusing funds.

"Through these solutions, we were able to target our limited resources to oversee the highest risk grantees, save thousands of hours of manpower by moving from manual processes to automated quarterly grant report reviews, and effectively question over $2.2 billion
in costs."

-Deborah Harker, Treasury OIG Assistant Inspector General for Audit

The Program:

The Coronavirus Relief Fund (CRF), established by the CARES Act, allocated $150 billion to state, local, and Tribal governments for pandemic response. Payments went to nearly 1,000 prime recipients, who distributed funds to around 80,000 subrecipients, beneficiaries, and payees to address immediate pandemic-related needs.

The U.S. Department of the Treasury was responsible for ensuring CRF award payments were made. Treasury’s Office of Inspector General (OIG), given unique statutory authorities in the CARES Act, was responsible for ensuring grantees (prime recipients) submitted reports on how funds were spent, monitoring of the use of funds, and oversight of the CRF program.

The Problem:

Overseeing a new $150 billion program posed significant challenges for Treasury OIG. It lacked the staff and analytics resources to handle the massive volume of quarterly data reports from grantees. The audit staff spent nearly 1,600 extra hours each quarter on these reviews, in addition to their regular duties, with no efficient way to identify the most at-risk recipients.

The Partnership Solution:

Treasury OIG enlisted the PRAC to address two critical needs: reducing total staff hours spent manually reviewing grantees' periodic reporting for accuracy, and ranking submissions using a risk model to identify those most at risk for misuse of funds for auditors to examine further.

Our data scientists developed a Robotic Process Automation (RPA) solution that automated the process for reviewing reports from grantees on how their funds were spent. Overall, the RPA solution saves auditors a significant amount of time from manual review and data sampling, and helps improve quality and accuracy of the review.

Additionally, we created a risk scoring model, accessible via an interactive, cloud-based dashboard, helping Treasury OIG identify and prioritize high-risk prime and subrecipients.

The Result:

The PRAC's data analytic process halved Treasury OIG auditors' quarterly review times. In one instance, using the RPA solution, a grantee report review that took over 2.5 hours manually now takes only four minutes. Secondly, the risk model prioritized recipients by risk, enabling Treasury OIG's limited staff to focus on the highest-risk desk reviews. These desk reviews identified $2.2 billion in questioned costs.

The Way Forward:

The PRAC continues to show the value of a permanent data analytics platform within the oversight community to prevent fraud and improper payments and ensure that taxpayer dollars go to those who need it most.

“If the PRAC and its data analytics function are allowed to sunset on September 30, 2025, we believe the federal government will no longer have an entity capable of proactively conducting cross-program, cross-agency analysis to help prevent improper payments in high-risk programs across federal agencies.”  
- PRAC Chair Michael Horowitz

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