Workers Denied: How to Diagnose and Prevent Improper Unemployment Insurance Denials

Summary

Unemployment insurance (UI) benefits can be a lifeline for unemployed workers. But each year many workers who apply for benefits are improperly denied. An improper denial occurs when a state UI agency denies UI benefits to a worker who, based on the law and the facts, is entitled to benefits.

Any improper denial can cause significant hardship for a worker, even if the denial is ultimately reversed. For example, consider if you are laid off from your job. While you feverishly try to find job openings in your area, and deal with the emotional impact of job loss, you apply for UI. Weeks later, your claim is denied. Even if you appeal, in the meantime you still must scramble to figure out how to pay your rent, keep your lights on, and keep your family fed.

Improper denials are a major barrier for workers trying to access the UI benefits they are due. Over the past ten years, between nine and 19 percent of all denials have been improper.[1] Improper denials can occur for a variety of reasons, including the state UI agency misapplying the law, employers failing to provide accurate or complete information on wage[2] or separation reports,[3] or workers being confused by questions on applications or fact-finding questionnaires. A high rate of improper denials can be a symptom of a broader problem in a state’s data collection and/or entitlement determination processes.[4]

This brief provides an overview of the federal data available on improper denials in each state so that stakeholders can identify where their states are falling short in processing claims and how to address these problems to reduce improper denials and improve workers’ access to UI benefits. The brief begins with an introduction to the U.S. Department of Labor’s Denied Claim Accuracy (DCA) data. Subsequent sections walk through how to conduct an annual state-specific “check-up” using DCA data to: (1) determine the severity of improper denial symptoms; (2) locate pain points; (3) find the sources of the problem; (4) review state agency’s actions to detect and remedy the problem; and (5) identify areas for further investigation. The brief concludes with recommendations to reduce the likelihood of improper denials to ensure eligible workers can access the UI compensation they are entitled to.

Key Points

• An improper denial is when a state UI agency denies a worker unemployment insurance (UI) benefits even though the worker is entitled to those benefits based on the law and facts.
• Improper denials can leave workers without critical support during periods of unemployment.
• The U.S. Department of Labor calculates and reports state improper denial rates via the Denied Claims Accuracy (DCA) program.

Key Solutions

• Stakeholders can use the DCA annual report and associated data to:
  • Determine if their state has high improper denial rates;
  • Locate pain points in their state’s determination processes;
  • Identify sources of pain points their state’s determination processes;
  • Review their state’s actions to identify and fix improper denials; and
  • Identify additional resources that can help narrow down the causes of and solutions for their state’s improper denials.
• Federal and state governments and agencies can adopt best practices to prevent improper denials.

Read the Full Brief

Endnotes

[1] Derived from Improper Denial Rates from the U.S. Department of Labor Denied Claims Accuracy Program annual reports and data files from 2013 to 2023. Unemployment Insurance Performance Management U.S. Dep’t of Labor, https://oui.doleta.gov/unemploy/bqc.asp (last visited July 16, 2025).

[2] U.S. Dep’t of Labor, Benefit Accuracy Measurement Payment Integrity Information Act State Data Summary Performance Year 2023 33 (2023), https://oui.doleta.gov/unemploy/bam/2023/PIIA_2023_Benefit_Accuracy_Measurement_Annual_Report.pdf (hereinafter DCA 2023 Report).

[3] U.S. Dep’t of Labor, ET Handbook No. 395 VIII-52 (5th ed. Nov. 17, 2009), https://www.dol.gov/agencies/eta/advisories/handbooks/et-handbook-no-395-5th-edition (hereinafter ETA 395)

[4] DCA 2023 Report, supra note 2, at 1.