A FORENSIC STATISTICAL ANALYSIS OF FRAUD IN THE FEDERAL FOOD STAMP PROGRAM

• 成果类型: Article
• 署名作者: Woody, Jonathan; Zhao, Zhicong; Lund, Robert; Wu, Tung-Lung
• 署名单位: Mississippi State University; University of California System; University of California Santa Cruz
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/24-AOAS1891
• 发表日期: 2024
• 页码: 2486-2510
• 关键词: detection system; scan statistics

摘要

This study develops methods to detect anomalous transactions linked with fraud in food stamp purchases through order statistics methods. The methods detect clusters in the order statistics of the transaction amounts that merit further scrutiny. Our techniques use scan statistics to determine when an excessive number of transactions occur (cluster), which is historically linked to fraud. A scoring paradigm is constructed that ranks the degree in which detected clusters and individual transactions are anomalous among approximately 250 million total transactions.