This use case describes how Anomali Copilot can detect and prevent fraud across critical public systems such as elections, unemployment benefits, and Medicare. Copilot analyzes large-scale data over long time periods to identify anomalies like duplicate voting, false registrations, and ineligible voters by cross-referencing voter records with public and death records. For unemployment fraud, it detects suspicious claim patterns, inconsistent employment histories, and real-time anomalies across multiple states, helping reduce fraudulent payments. In Medicare, Copilot flags unusual billing behavior, excessive or unnecessary claims, and mismatches between patient histories and services provided. By using machine learning, natural language processing, and entity resolution, Copilot improves in

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