Strengthening the Integrity of Government Payments Using Artificial Intelligence

Authors: James E. Cook, Gordon C. Milbourn III, and Chuck Howell


Summary 

Tens of billions of taxpayer dollars are lost every year due to improper payments to the federal government. These improper payments arise from agency and claimant errors as well as outright fraud. Data analytics can help identify errors and fraud, but often only identify improper payments after they have already been issued.


Artificial intelligence (AI) in general—and machine learning (ML) in particular (AI/ML)—could substantially improve the accuracy of federal payment systems. The next administration should launch an initiative to integrate AI/ML into federal agencies’ payment processes. As part of this initiative, the federal government should work extensively with non-federal entities—including commercial firms, nonprofits, and academic institutions—to address major enablers and barriers pertaining to applications of AI/ML in federal payment systems. These include the incidence of false positives and negatives, perceived and actual fairness and bias issues, privacy and security concerns, and the use of ML for predicting the likelihood of future errors and fraud.

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About the Author

James Cook is an advocate for data-driven, outcome-focused government. He has spent his career helping to advance improvements in Federal and State government performance, focusing on better use of technology, acquisition reform, benefits administration, and effective stewardship of public funds through high-integrity payment systems. In his current role, he leads MITRE’s strategic corporate interactions with policymakers in the Executive Office of The President and Congress; and promotes development of new strategic partnerships with the non-profit policy community through MITRE’s Center for Data-Driven Policy. He also fosters partnerships with private sector, academia, and other non-profit associations and foundations to address public interest challenges at the federal, state, and municipal levels. Since 1983, Jim has led major programs at the Federal and state levels focused on modernizing business and technology operations and disbursing large volumes of payments to the public. He has experienced firsthand the importance of ensuring integrity in payment programs and the processes and systems that support them. From 2007 to 2017, Cook was vice president and director for MITRE’s Center for Enterprise Modernization (CEM), the federally funded research and development center sponsored by the Department of the Treasury and co-sponsored by the Department of Veterans Affairs (VA) and the Social Security Administration (SSA). He has sponsored ongoing efforts to research causes of improper payments and financial fraud and advance innovation, collaborative approaches to address them through data sharing, new public-private partnerships, and application of technology to advance prediction, detection and decision-making.


Gordon Milbourn III is MITRE’s Policy Leader for Payment Integrity, focusing on fraud and other improper payment issues across the government. He began his career in 1974 with the IRS Inspection Service, serving in various audit positions nationwide for 12 years before moving to the Naval Audit Service and then the EPA Office of Inspector General. In 1999 Milbourn returned to the IRS as an audit executive with the newly formed Treasury Inspector General for Tax Administration and acted for over 2 years as the Deputy IG for Audit, before completing his federal career as the Assistant IG for Audit at the U.S. Postal Service. Throughout his audit career he concentrated on improving government efficiency and effectiveness and combating fraud, waste and abuse, and in 2008 received the David M. Walker Excellence in Government Performance and Accountability Award. Upon retiring from federal service, Milbourn came to MITRE where he has worked with numerous federal sponsors on systems, accountability, and Payment Integrity challenges. Milbourn received his bachelor’s degree in accounting from the University of Virginia and completed the DOD Program Manager’s Course in leadership and systems engineering. He is a Certified Internal Auditor, a Certified Fraud Examiner, and a Certified Financial Crime Specialist.


Chuck Howell is focused on adapting tools and techniques from high-assurance systems engineering and from various sectors’ risk management frameworks to apply to consequential AI (particularly, machine learning) systems. These tools and techniques can help organizations address concerns about AI system properties such as fairness, operational risk, safety, and credibility. Chuck has over 30 years of experience working in High Assurance Systems Engineering and AI. He previously held roles at Mitretek, Sun Microsystems, Reliable Software Technologies, Verdix, and Computer Sciences Corporation. He was a member of the Institute of Electrical and Electronics Engineers (IEEE) Software Engineering Body of Knowledge Industrial Advisory Board. Chuck chaired the First Annual Assurance Case Workshop in Florence, Italy, and co-chaired the Fall 2015, 2016, 2017, and 2018 Association for the Advancement of Artificial Intelligence (AAAI) national workshops on Cognitive Assistance in Government and Public Sector Applications. He is co-author of the book Solid Software (Prentice Hall, 2001). Chuck is a Senior Member of the IEEE and a member of the AAAI and the Association for Computing Machinery.