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Fraud Risk Management: 2018-2022 Data Show Federal Government Loses an Estimated $233 Billion to $521 Billion Annually to Fraud, Based on Various Risk Environments
GAO-24-105833

No area of the federal government is immune to fraud. We estimated that the federal government could lose between $233 billion and $521 billion annually to fraud.

Given the scope of this problem, a government-wide approach is required to address it. The Office of Management and Budget, working with agencies and the oversight community, should develop guidance to improve fraud-related data—providing a more uniform approach to what data is collected and how.

Also, Treasury should identify methods to expand government-wide estimates of fraud—prioritizing higher-risk program areas.

GAO estimated total direct annual financial losses to the government from fraud to be between $233 billion and $521 billion, based on data from fiscal years 2018 through 2022. The range reflects the different risk environments during this period. Ninety percent of the estimated fraud losses fell in this range.

GAO collected data from three key sources to develop the estimate: investigative data, such as the number of cases sent for prosecution and the dollar value of closed cases; Office of Inspector General (OIG) semiannual report information; and confirmed fraud data reported to the Office of Management and Budget (OMB) by agencies. GAO organized these data around three fraud categories—adjudicated, detected potential, and undetected potential. Model design and validation were also informed by 46 fraud studies. OIG and other knowledgeable officials agreed with these categories and subcategories.

GAO's approach is sensitive to the assumptions made about fraud and accounts for data uncertainty and limitations. GAO used a well-established probabilistic method for estimating a range of outcomes under different assumptions and scenarios where there is uncertainty. The estimate does not include fraud loss associated with federal revenue or fraud against federal programs that occurs at the state, local, or tribal level unless federal authorities investigated and reported it. GAO's estimate is in line with other estimates of fraud losses from the United Kingdom and Association of Certified Fraud Examiners, among others.

As a first of its kind government-wide estimate of federal dollars lost to fraud, there are known uncertainties associated with the model and underlying data important to interpreting the results. These include caveats related to:

-- applying the estimate to agencies or programs. GAO's model was developed to estimate government-wide federal fraud. The fraud estimate's range represents 3 to 7 percent of average federal obligations. These percentages should not be applied at the agency or program level. While every federal program and operation is at risk of fraud, the level of risk can vary substantially. Controls, growth or shrinkage of budget, and the emergence of new fraud schemes are some reasons the risk level can vary;

-- drawing conclusions about pandemic fraud. GAO's estimate is based on data from fiscal years 2018 through 2022. The data include time periods and programs with and without pandemic-related spending. Therefore, the estimate includes, but is not limited to, pandemic-related spending fraud. While the upper range of the estimate is associated with higher-risk environments, it is not possible to break out a subset of our government-wide estimate to describe pandemic program fraud;

-- comparing with improper payment estimates. GAO's estimate is not comparable to improper payment estimates. Improper payment estimates are based on a subset of federal programs, using a methodology not designed to identify fraud. GAO has also consistently reported that the federal government does not know the full extent of improper payments and has long recommended that agencies improve their improper payment reporting. In contrast, GAO's fraud estimate includes all federal programs and operations and is based on fraud-related data. With these differences in scope and data, the upper end of GAO's estimated fraud range exceeded annual improper payment estimates; and

-- assuming the estimate is predictive. GAO's estimate is not based on a predictive model. Factors such as the amount of emergency spending, the effectiveness of federal fraud risk management, and the nature of new fraud threats could substantially impact the scale of future fraud.

All federal programs and operations are at risk of fraud. Therefore, agencies need robust processes in place to prevent, detect, and respond to fraud. While the government obligated almost $40 trillion from fiscal years 2018 through 2022, no reliable estimates of fraud losses affecting the federal government previously existed.

As part of GAO's work on managing fraud risks, this report (1) estimates the range of total direct annual financial losses from fraud based on 2018-2022 data and (2) identifies opportunities and challenges in fraud estimation to support fraud risk management.

GAO estimated the range of total direct annual financial losses from fraud based on 2018-2022 data using a Monte Carlo simulation model. GAO identified opportunities and challenges through interviews and data collection focused on 12 agencies representing about 90 percent of federal obligations.

GAO is making two recommendations to OMB—one in collaboration with the Council of the Inspectors General on Integrity and Efficiency (CIGIE) and the other with agency input to improve the availability of fraud-related data. GAO is also making a recommendation to the Department of the Treasury to expand government-wide fraud estimation, in consultation with OMB. OMB generally agreed with the recommendations but disagreed with the estimate. GAO believes the estimate is sound, as discussed in the report. CIGIE stated it would work with OMB to consider how OIGs might improve fraud-related data. Treasury agreed with the recommendation.

https://www.gao.gov/products/gao-24-105833

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