OIG develops automated fraud data analytics model
The OIG continues to enhance fraud detection using a Department of Agriculture grant to build data-driven methods of identifying beneficiary fraud in the Supplemental Nutrition Assistance Program (SNAP). The OIG’s Benefits Program Integrity (BPI) division was one of nine state agencies across the country to receive a share of the $5 million SNAP Fraud Framework Implementation Grant awarded in September 2020. Agencies received funding for two years to implement innovative concepts and best practices aimed at improving state efforts to detect, investigate and prevent SNAP misuse.
With the awarded funds, the OIG partnered with a vendor to create the Automated Fraud Data Analytics Model, a user-friendly tool that identifies potential cases of SNAP fraud, waste or abuse. The SNAP model is comprised of two different dashboards. The first display shows cases with the greatest potential for misuse calculated through a series of algorithms analyzing eligibility, EBT transactions and investigation data with BPI feedback. All the data from its three main sources (eligibility, EBT transactions and investigations) are easily viewable to OIG investigators for each of the cases identified in this dashboard. BPI designated a specialized team to review identified cases with the greatest potential for FWA and determine if a full-scale investigation is warranted.
The second dashboard allows users to query the Texas Integrated Eligibility Redesign System (TIERS) for data elements and various identifiers that aid in detecting fraud. The purpose is to make the investigative process more efficient. The new search features allow investigators to search for data in a variety of ways to better identify and substantiate fraud, waste and abuse.