DETECTING DECEPTION: LEVERAGING WORK ASSIGNMENTS FOR FRAUD DETECTION AT USCIS
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Authors
Padilla, April Y.
Subjects
fraud
fraud detection
immigration
work assignment methods
strategic
random
hybrid
data analytics
U.S. Citizenship and Immigration Services
USCIS
Social Security Administration
SSA
Federal Emergency Management Agency
FEMA
fraud detection
immigration
work assignment methods
strategic
random
hybrid
data analytics
U.S. Citizenship and Immigration Services
USCIS
Social Security Administration
SSA
Federal Emergency Management Agency
FEMA
Advisors
Morag, Nadav
Aten, Kathryn J.
Date of Issue
2024-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
Immigration fraud harms the integrity of and erodes confidence in the U.S. immigration system by circumventing the legal immigration process. Recent convictions for immigration fraud demonstrate the prevalence of fraud in family-based filings at U.S. Citizenship and Immigration Services (USCIS). Existing research shows that the method of assigning work influences an employee’s skill development. This thesis investigated how work assignment method can influence an Immigration Services Officer’s (ISO) ability to detect potential fraud and which method would best detect fraud in adjudicating I-130 petitions. The thesis reviews relevant literature and applies findings to cases at the Social Security Administration (SSA) and Federal Emergency Management Agency (FEMA) to identify strengths and weaknesses of three work assignment methods: random, strategic, and hybrid. It explores the role of data analytics in fraud detection at SSA and FEMA and analyzes USCIS operations in light of the literature and cases of those agencies. Although each work assignment method has benefits and drawbacks for USCIS, the hybrid work assignment method offers the most significant benefits. Thus, it is the most beneficial for fraud detection at USCIS. To implement its use, USCIS should consider establishing a pilot program to test the hybrid work assignment method. Additionally, USCIS should consider increasing fraud training and incorporating data analytics into USCIS’ fraud detection strategy.
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Thesis
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Distribution Statement
Distribution Statement A. Approved for public release: Distribution is unlimited.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.