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Fact check: What oversight and sanctions do state agencies face for SNAP improper payments and how are QC error rates calculated?
Executive Summary
The SNAP improper payment rate is produced through a two-tiered Quality Control (QC) system that weights state error rates by benefit share to generate a national estimate; USDA/FNS reported an 11.7% improper payment estimate for FY2023 (about $10.5 billion) using that method. States carry primary responsibility for benefit accuracy and face financial accountability mechanisms — including potential penalties and performance pressures — but federal tools for enforcing or incentivizing integrity are limited and focused on QC measurement, funding for program integrity activities, and public reporting [1] [2].
1. Clear Claims: What proponents and watchdogs are saying about SNAP errors
The central claims across sources are consistent: states manage eligibility and benefit verification, while the USDA’s Food and Nutrition Service (FNS) oversees a QC framework that produces national and state-level error rates. Reports assert a rising national improper payment estimate — 11.7% in FY2023 — and tie financial consequences and management attention to those rates. Analysts note a portion of SNAP’s budget is earmarked for program integrity work but lack a consolidated accounting of those expenditures, and commentators propose ROI-based funding decisions to improve efficiency. State-level incidents of fraud, such as Michigan’s card thefts, are cited as examples where state operational failures produced large losses and prompted reforms [2] [3] [1].
2. The mechanics: How QC error rates are calculated and reported
USDA/FNS uses a two-tier QC system: states conduct reviews of sampled case files and calculate state error rates; FNS performs independent verification reviews and then computes the national improper payment rate as a benefit-weighted average of state rates, not a simple mean. Error measurement includes both underpayments and overpayments and excludes trivial differences beneath an annually adjusted tolerance threshold set by statute. Publication of state and national rates is annual, with historical series available for trend analysis. This weighted averaging explains why large states influence the national rate more strongly than small states, and why national estimates can shift even when some states improve performance [1] [4].
3. The fine print: Error tolerance thresholds and what gets counted
Congressional statute authorizes a tolerance threshold that excludes small dollar variances from being counted as errors; that threshold is adjusted annually to reflect changes such as the Thrifty Food Plan. Recent published thresholds show $56 for FY2024 and $57 for FY2025, meaning small administrative and rounding differences under those amounts are not classified as payment errors. This threshold materially affects measured error rates because it removes low-dollar discrepancies that would otherwise count as under- or overpayments. Analysts emphasize that shifts in the threshold or in benefit levels can change the measured error rate without any operational change in eligibility determinations, complicating year-to-year comparisons [5] [6].
4. Enforcement and consequences: What oversight and sanctions states face
The oversight regime blends federal QC oversight with state operational responsibility, creating incentives and limited fiscal sanctions. States are accountable through public reporting of QC rates, corrective action plans, and potential funding consequences tied to poor performance. Reports indicate intense managerial focus on error rates within local SNAP offices because those rates function as a primary performance measure; states invest in corrective activities to lower error rates. However, federal control is bounded: USDA lacks direct operational control of state eligibility determinations and primarily uses audits, reporting requirements, and funding levers for program integrity rather than direct operational mandates [7] [2] [1].
5. Recent numbers and trends: What the data show about the magnitude of improper payments
Recent FNS and GAO reporting documents notable increases in measured improper payments over recent years, with the national improper payment estimate at about 11.7% in FY2023 (roughly $10.5 billion) and a national payment error rate of 10.93% for FY2024 in other reporting, with overpayments making up the bulk of errors. Historically, overpayment rates rose from lower levels (for example, 6.18% in 2019 to about 9.84% in 2022 for overpayments), showing volatility tied to program expansions, administrative stressors, and measurement changes. These figures reflect both genuine eligibility or procedural errors and cases linked to fraud or lax state controls such as card security failures revealed in state investigations [1] [6] [7] [3].
6. Missing pieces and practical alternatives: Where the current system falls short
Key gaps include limited federal ability to directly remediate state operational failures, incomplete nationally consolidated accounting of program integrity spending, and the potential for measurement artifacts (threshold changes, weighting effects) to obscure true performance trends. Proposals in the analyses include using ROI calculations to prioritize integrity investments and modernizing state payment instruments (e.g., chip-enabled cards) after fraud episodes. These proposals would shift incentives by tying funding to demonstrable integrity returns or by reducing fraud vectors, but they would require Congress and FNS to adopt new performance-linked funding approaches and clearer transparency on program integrity expenditures [2] [3].