This Temporary Assistance for Needy Families (TANF) work verification plan from Vermont shows how a smaller state structures its approach to documenting and validating work participation. For TANF staff, it is useful for understanding how verification systems can be designed to balance compliance with administrative efficiency. It offers a concrete example that can help programs consider scalability, staff training needs, and ways to reduce administrative burden while still maintaining accurate reporting.

This Temporary Assistance for Needy Families (TANF) work verification plan from Arizona provides additional insight into how states operationalize verification requirements within TANF programs. For TANF practitioners, it highlights how definitions of work activities and documentation expectations can vary while still meeting federal standards. This can help TANF program leaders assess whether their own verification policies are overly complex or could be streamlined to better support both staff workload and participant understanding.

This Temporary Assistance for Needy Families (TANF) work verification plan from Nebraska illustrates another approach to implementing federal verification requirements at the state level. The plan is useful for TANF programs looking to understand different administrative models and documentation standards. Programs can use the plan to see how other states structure oversight and reporting, which can support internal conversations about simplifying verification processes or improving training for staff responsible for documenting work participation.

This Temporary Assistance for Needy Families (TANF) work verification plan from Texas offers a real-world example of how one state operationalizes federal work verification expectations. For other TANF programs, it provides a practical reference point for how policies are translated into procedures, including how activities are defined, documented, and reviewed. Programs can use this document to compare their own verification systems, identify gaps in consistency, and consider whether alternative structures could improve clarity for frontline staff while maintaining compliance requirements.

This Administration for Children and Families webpage provides states with a framework for developing work verification systems that document and validate participation activities. For Temporary Assistance for Needy Families (TANF) programs, this webpage is a foundational operations tool because it can guide how compliance is demonstrated and how staff document client work engagement. It supports TANF practitioners in building clearer internal procedures, improving consistency across offices, and reducing uncertainty about what counts as acceptable verification during case reviews or audits.

The Office of Management and Budget (OMB) has proposed changes to the regulations governing federal financial assistance, including grants and cooperative agreements that support programs administered by states, tribes, local governments, and nonprofit organizations. If finalized, the proposed rule could affect how federal funding is awarded, managed, monitored, and reviewed across a wide range of human services and workforce programs.

The National Congress of American Indians will host a webinar on July 1, 2026 at 3:00 P.M. ET to provide an overview of the proposed changes and their potential implications for organizations that receive or administer federal funds. For Tribal Temporary Assistance for Needy Families (TANF) programs, understanding these proposed revisions is important for anticipating how future changes to federal grant requirements could affect program operations, compliance responsibilities, partnerships, and funding administration. The session will offer an opportunity to learn about the rulemaking process, key provisions under consideration, and ways stakeholders can stay informed as the proposal moves forward.

The U.S. Department of Labor (DOL) has issued a Request for Information (RFI) seeking public input on the modernization of CareerOneStop and O*NET, two key workforce information resources used by job seekers, workforce professionals, and employment service providers nationwide. The effort is intended to improve access to career exploration, training, labor market information, and employment resources through a more user-friendly, mobile-accessible platform with enhanced functionality.

DOL is specifically seeking feedback from workforce practitioners, state and local workforce agencies, and other stakeholders on how these tools can better support frontline service delivery, reflect regional labor market needs, and improve the user experience for job seekers. For Temporary Assistance for Needy Families (TANF) practitioners, this RFI is an opportunity to share insights on how clients with employment barriers interact with career and workforce information systems and identify enhancements that could strengthen case management and employment outcomes. Comments will be accepted through August 10, 2026.

The Supplemental Nutrition Assistance Program (SNAP) serves over 40 million Americans annually, and SNAP program integrity involves multiple federal and state responsibilities, including eligibility verification, payment accuracy oversight, fraud investigations, claims recovery, and efforts to address rising third-party EBT theft. Because many Temporary Assistance for Needy Families (TANF) families also receive SNAP, practitioners regularly encounter situations where these issues intersect: a client whose EBT card was skimmed, a case flagged for review, or a question about what "payment error" means. This American Public Human Services Association report walks through the full picture of common SNAP fraud: the different types of integrity risks, the critical difference between intentional fraud and honest mistakes, how the investigation and enforcement process works, and what states are doing to protect benefits from theft.

It is important to distinguish between intentional fraud, unintentional household or agency error, retailer trafficking, and third-party benefit theft, because different integrity risks require different prevention, investigation, oversight, and recovery approaches. For TANF practitioners, this resource is a practical reference for real situations — helping you speak accurately with clients, navigate conversations with partner agencies, and support families whose benefits have been compromised.

The U.S. Department of Labor announced that it has recovered more than $512 million in fraudulent unemployment insurance claims and returned those funds to the U.S. Treasury. This release highlights this ongoing federal effort to identify improper payments after they occur while also improving systems to prevent fraud in future claims. For Temporary Assistance for Needy Families (TANF) practitioners, the value lies in the approaches being used to identify and freeze suspicious funds—data matching, audits, and recovery mechanisms that demonstrate how large-scale program integrity systems operate in practice. These strategies offer useful reference points for TANF agencies working to strengthen oversight, improve payment accuracy, and coordinate more effectively with workforce and unemployment insurance systems.

The Acting Secretary for the U.S. Department of Labor is urging governors to take immediate steps to address ongoing risks of unemployment insurance (UI) fraud, signaling continued concern about vulnerabilities in state-administered benefit systems. This release underscores the expectation that states must strengthen oversight, improve identity verification, and act quickly when suspicious activity is identified.

For Temporary Assistance for Needy Families (TANF) programs, this reinforces a broader shift toward tighter program integrity practices across interconnected public benefits systems. Many TANF agencies rely on shared eligibility data and cross-program verification tools, so improvements in UI fraud controls can strengthen the reliability of information used to determine eligibility and reduce improper payments across programs serving similar populations.