Resources and Toolkits

Video outlining best practices for states to improve their risk assessment and error detection processes, including model design, review sequencing, feature engineering, review process optimization, and quick wins

Workshop examining how predictive analytics and risk scoring can improve SNAP implementation and evaluation, using Conneticut as a case study.

States can simplify and streamline determinations for individuals and agenciesand, reduce administrative burden, and minimize unnecessary coverage loss by leveraging the overlap in compliance activities and exemption reasons for individuals applying for or enrolled in both programs. Strategies on aligning exemptions, sharing data, and integrating verification processes highlighted through process flows and crosswalks.

Workshop to foster collaboration and share modeling practices among state agencies in response to HR1’s new SNAP PER cost share requirements. Gathering encompassed convened a group of nearly 40 research and data analytics staff from across 15 states involved in SNAP QC data modeling.