These guidelines provide technical requirements for federal agencies implementing digital identity services and are not intended to constrain the development or use of standards outside of this purpose. This guideline focuses on the enrollment and verification of an identity for use in digital authentication.
National Institute of Standards and Technology (NIST)
This report outlines key lessons and recommendations from Code for America's collaboration with the Voluntary Income Tax Assistance program, which served over 800,000 clients via GetYourRefund.org.
On July 16, members of the Digital Identity Community of practice gathered to learn how peers are gathering beneficiary feedback on their experiences with accounts and proving their identity.
This page includes data and observations about account creation and identity proofing steps specifically for online applications that include MAGI Medicaid.
The California Employment Development Department (CA EDD) launched the EDDNext initiative to modernize benefit delivery, focusing on user-centric procurement for a new identity verification system.
Digital IDs can improve convenience, but they risk surveillance, data misuse, and exclusion if not designed with privacy, security, and accessibility safeguards.
The vast fraud committed through the use of stolen and synthetic identities in UI programs has spotlighted the need for updated identity fraud detection mechanisms. As states are implementing new technologies and systems, they need to consider the ways in which they are impacting racial inequities in UI benefits.
This post argues that for the types of large-scale, organized fraud attacks that many state benefits systems saw during the pandemic, solutions grounded in cybersecurity methods may be far more effective than creating or adopting automated systems.
In February 2023, the Digital Benefits Network at the Beeck Center for Social Impact + Innovation released a dataset documenting authentication and identity verification requirements that unemployment insurance (UI) applicants encounter across the United States. This resource outlines high-level observations from the data and more information about the research process.
