W119: Preventing Fraud: Early Signals, Fast Stops and Smarter Detection
- Room: 204 ABC
- Session Number:W119
Wednesday, July 22, 2026: 2:05 PM - 3:20 PM
Speaker(s)
Description
Fraudsters move fast — so do federal payments. This roundtable convenes federal leaders to reveal the earliest signals of grant fraud, test pre-payment screening strategies and apply AI-powered analytics (e.g., anomaly detection, natural language processing (NLP) and network analysis) to stop bad disbursements before they leave the U.S. Treasury — without slowing mission delivery or compromising privacy.
Key Takeaways
• A shortlist of top proactive indicators worth standardizing across grant and funding programs
• Shared understanding of the biggest blockers: data quality, silos, legacy systems, lack of an AI-ready workforce
• A set of potential capabilities (e.g., analytics center of excellence, pre-payment workflows, data integration) aligned to federal oversight priorities
Learning Objectives
Differentiate reactive versus proactive indicators for grants and funding fraud, waste, and abuse, and where in the lifecycle to deploy them (pre-award, pre-obligation, pre-payment or post-payment). Identify the highest-leverage use cases for AI and analytics (e.g., anomaly detection, NLP, relationship mapping) and the minimum data needed to start. Describe how to operationalize prevention with governance, privacy and oversight, including Do Not Pay expectations and office of inspector general collaboration.
Handouts