SNAP payment error rates by state

With error rates reaching 24.66% in some states, billions in SNAP cost-sharing obligations loom under the One Big Beautiful Bill Act. This interactive map shows where the problem is worst — and where states are getting it right.

Last updated: February 2026

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SNAP payment error rates measure the percentage of Supplemental Nutrition Assistance Program benefits that are issued incorrectly — whether as overpayments to ineligible households or underpayments to eligible ones. These rates matter because they directly affect the accuracy and fiscal integrity of a program that distributes over $94 billion annually (FY 2024) to more than 42 million Americans. Even small percentage-point differences translate into billions of dollars in misallocated funds and, under new federal rules, significant cost-sharing obligations for states.

The One Big Beautiful Bill Act (OBBBA), signed into law in July 2025, establishes a tiered cost-sharing framework that holds states financially accountable based on their error rates. Starting in FY 2028, states with error rates of 6–8% must cover 5% of their total benefit allotments, states at 8–10% cover 10%, and states at or above 10% cover 15%. States below 6% owe no cost share. With 44 states currently above the 6% threshold (FY 2024), the collective fiscal exposure is projected to reach billions of dollars annually.

Across all states and the District of Columbia, error rates currently range from 3.28% (South Dakota) to 24.66% (Alaska), with a national average of 10.93%. The interactive map below shows official FY 2024 data for all 50 states and Washington, D.C. — click any state to see its detailed error rate breakdown and estimated OBBBA cost-share exposure.


Interactive error rate map

Hover over any state to see its error rate, or click to view detailed information. States are color-coded by error rate severity.

< 6%
6 – 10%
> 10%
Alabama: 8.32% error rateAlaska: 24.66% error rateArizona: 8.84% error rateColorado: 9.97% error rateFlorida: 15.13% error rateGeorgia: 15.65% error rateIndiana: 9.52% error rateKansas: 9.98% error rateMaine: 10.26% error rateMassachusetts: 14.1% error rateMinnesota: 8.98% error rateNew Jersey: 14.33% error rateNorth Carolina: 10.21% error rateNorth Dakota: 7.91% error rateOklahoma: 10.87% error ratePennsylvania: 10.76% error rateSouth Dakota: 3.28% error rateTexas: 8.32% error rateWyoming: 5.12% error rateConnecticut: 10.25% error rateMissouri: 9.42% error rateWest Virginia: 9.43% error rateIllinois: 11.56% error rateNew Mexico: 14.61% error rateArkansas: 9.56% error rateCalifornia: 10.98% error rateDelaware: 12.37% error rateDistrict of Columbia: 17.38% error rateHawaii: 6.68% error rateIowa: 6.14% error rateKentucky: 9.11% error rateMaryland: 13.64% error rateMichigan: 9.53% error rateMississippi: 10.69% error rateMontana: 8.89% error rateNew Hampshire: 7.57% error rateNew York: 14.09% error rateOhio: 9.01% error rateOregon: 14.06% error rateTennessee: 9.47% error rateUtah: 5.74% error rateVirginia: 11.5% error rateWashington: 6.06% error rateWisconsin: 4.47% error rateNebraska: 5.5% error rateSouth Carolina: 9.25% error rateIdaho: 3.59% error rateNevada: 5.94% error rateVermont: 5.13% error rateLouisiana: 6.62% error rateRhode Island: 12.29% error rate

Data based on USDA FNS FY 2024 Quality Control error rate reports. Cost-share estimates based on OBBBA (P.L. 119-21) tiered provisions, Section 10105.


State-by-state data

Click any column header to sort. All 50 states and the District of Columbia are included.

Complete SNAP Error Rate Data by State
#
1Alaska24.66%92K$37M
2District of Columbia17.38%131K$48M
3Georgia15.65%1.6M$477M
4Florida15.13%3.0M$982M
5New Mexico14.61%430K$154M
6New Jersey14.33%764K$289M
7Massachusetts14.1%889K$393M
8New York14.09%2.8M$1.1B
9Oregon14.06%765K$239M
10Maryland13.64%674K$225M
11Delaware12.37%131K$38M
12Rhode Island12.29%157K$51M
13Illinois11.56%1.8M$670M
14Virginia11.5%821K$265M
15California10.98%5.1M$1.9B
16Oklahoma10.87%618K$226M
17Pennsylvania10.76%1.8M$640M
18Mississippi10.69%545K$126M
19Maine10.26%193K$55M
20Connecticut10.25%383K$134M
21North Carolina10.21%1.3M$440M
22Kansas9.98%233K$41M
23Colorado9.97%533K$130M
24Arkansas9.56%378K$52M
25Michigan9.53%1.4M$306M
26Indiana9.52%689K$144M
27Tennessee9.47%924K$162M
28West Virginia9.43%291K$57M
29Missouri9.42%756K$151M
30South Carolina9.25%668K$129M
31Kentucky9.11%612K$115M
32Ohio9.01%1.5M$318M
33Minnesota8.98%462K$86M
34Montana8.89%107K$17M
35Arizona8.84%913K$202M
36Alabama8.32%782K$173M
37Texas8.32%3.5M$721M
38North Dakota7.91%57K$6M
39New Hampshire7.57%84K$8M
40Hawaii6.68%172K$37M
41Louisiana6.62%836K$95M
42Iowa6.14%328K$26M
43Washington6.06%915K$96M
44Nevada5.94%434K$0
45Utah5.74%213K$0
46Nebraska5.5%186K$0
47Vermont5.13%75K$0
48Wyoming5.12%31K$0
49Wisconsin4.47%638K$0
50Idaho3.59%192K$0
51South Dakota3.28%100K$0

Understanding state-by-state variations

Highest error rate states

The five states with the highest SNAP payment error rates are Alaska (24.66%), District of Columbia (17.38%), Georgia (15.65%), Florida (15.13%), and New Mexico (14.61%). These states share common challenges: large caseloads relative to available administrative staff, legacy eligibility systems that lack automated verification, and complex state eligibility rules layered on top of federal requirements. Together, they face an estimated $1.7B in combined OBBBA cost-share exposure.

Lowest error rate states

The five states with the lowest error rates are South Dakota (3.28%), Idaho (3.59%), Wisconsin (4.47%), Wyoming (5.12%), and Vermont (5.13%). These states tend to have smaller caseloads, more streamlined eligibility processes, and earlier investment in modernized case management technology. Their success demonstrates that low error rates are achievable with the right combination of process design and technology.

What causes high error rates?

SNAP payment errors stem from systemic issues rather than individual failures. The most common causes include incorrect income calculations during eligibility determination, outdated household composition data, failure to account for deductions and exemptions, delayed processing of recertification paperwork, and manual data entry mistakes in legacy systems. States with high caseload-to-worker ratios are particularly vulnerable, as overtaxed caseworkers have less time to verify each application thoroughly.

Regional patterns and trends

Error rates show clear regional patterns. Southeastern states tend to have higher error rates, driven by larger SNAP caseloads, higher poverty rates, and historically lower investment in administrative technology. States in the Upper Midwest and New England generally perform better, with error rates well below the national average. Western states show mixed results — California and Arizona have moderate-to-high rates reflecting the complexity of large, diverse populations, while Nevada, Utah, and Wyoming maintain rates below 6%.


How Savor Snap addresses these errors

Savor Snap is building machine-learning infrastructure designed to detect and correct SNAP payment errors before they reach recipients, protecting both the fiscal integrity of the program and the 42 million Americans who depend on it.

  • Real-time ML error detection

    Our models are designed to analyze payment transactions as they're processed, flagging anomalies before disbursement.

  • Designed to prevent errors before they occur

    Rather than catching errors after the fact through costly QC reviews, Savor Snap is designed to intercept incorrect payments in the processing pipeline.

  • Reduces state OBBBA cost-share risk

    By driving error rates below the 6% threshold, states can avoid the cost-sharing obligations that OBBBA provisions impose on high-error jurisdictions.

  • Protects 42M Americans receiving benefits

    Accurate payments mean eligible families receive the correct amount — no overpayments that trigger clawbacks, no underpayments that leave households short.


Frequently asked questions

Common questions about SNAP payment error rates, OBBBA cost-sharing, and state performance.

What is a SNAP payment error rate?+

A SNAP payment error rate measures the percentage of Supplemental Nutrition Assistance Program (SNAP) benefits that are issued incorrectly — either overpayments to ineligible recipients or underpayments to eligible ones. These rates are determined through the USDA's Quality Control (QC) review process, which audits a statistically representative sample of cases in each state. The FY 2024 combined error rate includes both over-issuance (9.26% nationally) and under-issuance (1.67% nationally) errors.

Which state has the highest SNAP error rate?+

Based on the most recent USDA FNS FY 2024 Quality Control data, Alaska has the highest SNAP payment error rate at 24.66%. This is significantly above the national average of 10.93%. High error rates can result from complex eligibility rules, staffing shortages, outdated technology systems, and high caseload volumes.

What is the national average SNAP error rate?+

The national average SNAP payment error rate for FY 2024 is 10.93%, comprising a 9.26% overpayment rate and a 1.67% underpayment rate. This means roughly 1 in 9 SNAP benefit calculations contain some form of error. South Dakota has the lowest rate at 3.28%, while Alaska has the highest at 24.66%. The national average is calculated using a dollar-weighted methodology by USDA FNS.

What are OBBBA cost-sharing provisions?+

The One Big Beautiful Bill Act (OBBBA), signed into law in July 2025, establishes a tiered cost-sharing framework for states based on their SNAP payment error rates, taking effect in FY 2028. States with error rates below 6% owe no cost share. States at 6–8% share 5% of benefit costs, those at 8–10% share 10%, and states at or above 10% share 15% of their total benefit allotments. These provisions are designed to incentivize states to invest in error reduction technology and process improvements.

How are SNAP error rates calculated?+

SNAP error rates are calculated through the USDA Food and Nutrition Service (FNS) Quality Control (QC) system. Each state conducts monthly reviews of a random sample of active SNAP cases and negative actions (denials and terminations). Federal reviewers then re-review a subsample for accuracy. The error rate is computed as the total dollar value of over-issuances and under-issuances divided by the total dollar value of benefits issued, expressed as a percentage.

What happens if a state exceeds the error rate threshold?+

Under OBBBA, states are subject to tiered cost-sharing starting in FY 2028 based on their error rate. States at 6–8% share 5% of benefit costs, those at 8–10% share 10%, and states at or above 10% share 15%. However, OBBBA includes a temporary delay for states with the highest error rates. If a state's FY 2025 payment error rate exceeds 13.33%, it is exempt from cost-sharing until FY 2029. If its FY 2026 rate still exceeds 13.33%, the exemption extends to FY 2030. This means the highest-error states may not face cost-sharing obligations for up to two additional years — but if their error rate falls from above 13.33% to between 6% and 13.33% during that period, cost-sharing is triggered at the applicable tier rate. The cost-share estimates shown on this page reflect each state's current tier obligation based on FY 2024 error rates and do not account for this temporary delay provision.

How can states reduce SNAP error rates?+

States can reduce SNAP error rates through several strategies: investing in modern eligibility verification technology, implementing real-time error detection systems powered by machine learning, improving caseworker training and support, simplifying application and recertification processes, and conducting targeted quality improvement reviews. Technology solutions like Savor Snap's ML-powered error detection are designed to identify and correct errors before payments are issued.

How often are SNAP error rates updated?+

The USDA FNS publishes official SNAP error rates annually, typically releasing data from the prior fiscal year. The QC review process runs continuously throughout the year, but the compiled and verified state-level error rates are released on an annual cycle. States receive preliminary data before the official publication, allowing them to begin corrective actions. This map is updated when new official data becomes available from USDA FNS.


Data sources & methodology

The error rate data presented on this page is derived from the USDA Food and Nutrition Service (FNS) Quality Control (QC) FY 2024 reports. The QC system requires each state to review a statistically valid random sample of active SNAP cases and negative actions each month. Federal reviewers then re-examine a subsample for accuracy, and the resulting error rates are published annually.

Error rates represent the combined over-issuance and under-issuance rate, calculated as the total dollar value of incorrect payments divided by total benefits issued. The national average of 10.93% comprises a 9.26% overpayment rate and a 1.67% underpayment rate, calculated using USDA's dollar-weighted methodology.

Estimated OBBBA cost shares are calculated using the tiered framework established by the One Big Beautiful Bill Act: states below 6% owe nothing; 6–8% owe 5% of total benefit allotments; 8–10% owe 10%; and states at or above 10% owe 15%. Benefit issuance figures are from USDA FNS FY 2024 data. These cost-share estimates are projections based on current rates applied to FY 2028 enforcement and may differ from actual assessments.

Cost-share formula:

State Cost Share = [State SNAP Benefit Allotments] × [Applicable Tier Rate]

Tier rates: <6% = 0% | 6–8% = 5% | 8–10% = 10% | ≥10% = 15%

Example: California (error rate 10.98%, FY 2024 SNAP benefits ~$12.4B): At the ≥10% tier → 15% cost share → ~$1.9B estimated annual obligation.

SNAP recipient counts are approximate estimates based on the most recent USDA FNS participation data. All figures are subject to revision as new data becomes available. We update this page when USDA FNS releases new official error rate data, typically on an annual cycle.

Sources: USDA FNS FY 2024 QC Payment Error Rate Reports; USDA FNS FY 2024 SNAP Benefit Allotment Data; One Big Beautiful Bill Act (H.R. 1, 119th Congress).


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