On May 19, 2023, the Digital Benefits Network published a new, open dataset documenting authentication and identity proofing requirements across online SNAP, WIC, TANF, Medicaid, child care (CCAP) applications, and unemployment insurance applications.
This Urban Institute article argues that poverty is driven by structural barriers rather than individual choices and advocates for safety net programs that address systemic inequities.
This toolkit is designed to assist state and local TANF agencies in accessing, linking, and analyzing employment data from unemployment insurance (UI) systems.
This article examines how the decentralization of safety net programs after welfare reform has led to growing inequality in benefit generosity and access across U.S. states.
This plan promotes responsible AI use in public benefits administration by state, local, tribal, and territorial governments, aiming to enhance program effectiveness and efficiency while meeting recipient needs.
U.S. Department of Health and Human Services (HHS)
Working with TANF administrators and human services leaders across the country, the American Public Human Services Association (APHSA) embraces the call to reimagine how TANF can work in support of the families it serves and has established a set of TANF Modernization Core Principles to guide our vision for the future of TANF. Grounded in these Core Principles, APHSA’s members have laid out a legislative framework to unlock the potential of TANF. We call upon Congress to use this framework as a starting point to build common ground to achieve a TANF reauthorization that promotes a more equitable and prosperous future for all Americans.
American Public Human Services Association (APHSA)
An America where no one experiences poverty is possible. Already, the U.S. has programs with the potential to make this vision a reality, including programs that provide cash assistance, like Temporary Assistance for Needy Families (TANF). The current TANF program provides very little cash assistance and is marked by stark racial disparities, but it has the potential to reduce child poverty, increase economic security, and advance racial equity. This report offers a vision for an anti-racist approach to the TANF program, with new statutory goals and policy recommendations to advance racial justice.
A case study explaining how a predictive, data-driven machine-learning model was developed to detect unauthorized cash benefit withdrawals more quickly and accurately in California.
This publication explains current state integrated eligibility and enrollment (IEE) system implementation processes, approaches, and opportunities for future processes and technologies. It is a resource for state officials, advocates, funders, and tech partners working to implement these systems.
This publication explains the fundamentals of state IEE systems—including the technology, opportunities, risks, and stakeholders involved. It is a resource for state officials, advocates, funders, and tech partners working to implement these systems.
The Temporary Assistance for Needy Families (TANF) Data Collaborative Pilot Initiative is a component of the TANF Data Innovation project. The 30-month pilot offered technical assistance and training to support cross-disciplinary teams of staff at eight state and county TANF programs in the routine use of TANF and other administrative data to inform policy and practice.
