Our approach to improper payments is failing; the 2024 numbers explain why

Last month, the Office of Management and Budget published 2024 improper payment data. The headline: The overall reported government-wide improper rate was at its lowest level in over a decade at 3.97%.  This sounds like very good news. However, overall improper payment rates frequently dominate headlines while obscuring the underlying reality.

If improper payment rates decline, is it due to better prevention, changes in estimating methodologies, or shifts in program funding? If they increase, is it because agencies are detecting more improper payments or failing to prevent them? Who’s to know?

The overall numbers often hide what’s really going on. This is because the improper payment rate is a percentage of total spending, so if spending outpaced the rate of improper payments, it looks like a decrease in improper payments. This was a reason for much of the drop that OMB celebrated in 2024.

For example, just over half of the 46 programs with available data for both 2023 and 2024 reported a reduction in improper payment rates. Of these, only 36% reduced the actual dollar amount of improper payments. Put another way, of the 64% of programs with increases in improper payment amounts, a third still managed to report decreases in their improper payment rates simply because their rate of spending grew faster. Some programs spent less but reported higher improper payments — highlighting again why improper payment rates alone can be misleading.

At the program level, the problems come into better focus. Take Medicaid, for instance. In fiscal year 2023, it reported a rate of 8.6% in improper payments. The Department of Health and Human Services said this underestimates the actual figures, in part, because of temporary COVID-19 policies that relaxed eligibility requirements.

The Government Accountability Office  reported that HHS computes an annual rolling average of improper payment rates based on a three-year rotation cycle. While COVID-19 flexibilities expired in fiscal year 2023, GAO said those policies would continue to impact the Medicaid estimates until fiscal year 2025 because the estimate is based on a three-year rolling average.

However, in fiscal year 2024, CMS touted a 40% year-over-year drop in the Medicaid improper payment rate to 5.1%. Rather than tout this success, CMS should have qualified that the numbers are artificially low due to the way HHS calculates the rates, as GAO reported.

Problems with improper payment estimating go beyond Medicaid. For example, resource constraints forced the Internal Revenue Service to shrink its sample size in 2022 for estimating improper payments in the Earned Income Tax Credit program, one of the worst offenders across government. The IRS also shifted from fiscal-year to tax-year reporting. The result? A less accurate improper payment rate and a reported $2.5 billion drop in total improper payments driven more by changes in methodology than demonstrable improvements in reducing improper payments. These inconsistencies render year-to-year comparisons almost meaningless.

The result of these shenanigans is a focus on managing processes and improper payment reporting requirements — or worse, optics — rather than meaningful outcomes. The current improper payment reporting framework creates work of questionable value for decision-making. And it perpetuates a culture of compliance that is antithetical to outcome-oriented, proactive, data-driven management of improper payments and fraud risks.

It is clear to us legislative reform is badly needed. Requiring burdensome and wasteful compliance estimating and reporting in service to preventing fraud, waste and abuse is troublingly ironic. Lawmakers should prioritize legislation that prioritizes genuine fraud and improper payment prevention and jettison compliance-oriented requirements that have proven to be ineffective. Three actions Congress can take:

1. Require agencies to identify data gaps and mandate the use of data. Agencies consistently cite a lack of sufficient data as the primary root cause of their persistent improper payments. Yet for the most part, they have done little to address this issue. Treasury’s Office of Payment Integrity is amassing more and more data that can be used to uncover fraud and improper payments. These efforts should be bolstered, and agencies should be required to make use of this data. 
2. Establish a centralized, independent entity aimed at program integrity. This office could promote consistent and reliable improper payment measurement and use of data across government to better identify, detect and prevent improper payments and fraud. Improper payment estimation must be nuanced and contextualized to specific programs, rather than expecting all agencies to apply the same methodologies to all programs. A centralized, specialized office can provide the insight needed to do this. Treasury’s Office of Payment Integrity is well suited to play this role with expanded authorities and funding.
3. Eliminate burdensome requirements on low-risk programs and require data-driven outcomes from those deemed high-risk.  Today, all agencies with program outlays of at least $10 million are required to undertake burdensome compliance activities, which they do with a check-the-box approach, wasting valuable time and resources that could be better spent on data- and outcome-oriented efforts. Instead, those agencies with programs at high-risk of fraud and improper payments should be required to implement proactive, data-driven initiatives to prevent and detect fraud and improper payments and demonstrate meaningful progress. Limiting requirements to high-risk programs allows for a targeted approach that can invest in tailored, evidence-based approaches. The high-priority program established in 2009, coupled with the GAO recommendation to include all new programs with over $100 billion in annual outlays, provides the basis for identifying which programs to include.

After more than 20 years of ineffective tending to the improper payment problem, investing in the same flawed approaches risks falling deeper into a sunk-cost fallacy — pouring resources into a framework that fails to deliver meaningful progress. The path forward demands smarter solutions and enhanced use of critical data sources. By moving in this direction, there’s a better chance of meaningful reduction in fraud and improper payments.
 

The authors are co- founders of the Program Integrity Alliance, a nongovernmental organization aimed at strengthening data-driven fraud prevention in the U.S. government.

Linda Miller is a noted fraud expert, former deputy executive director of the Pandemic Response Accountability Committee, and former senior executive at the Government Accountability Office, where she led the development of GAO’s Fraud Risk Management Framework.

Gavin Ugale served at GAO and the Organization for Economic Cooperation and Development, where he pioneered the work to modernize integrity and anti-corruption efforts through the innovative use of technology and data. While at GAO, he was instrumental in the development of GAO’s Fraud Risk Management Framework.