Poster Session 2, 11:30 AM - 12:15 PM: Campus Center Auditorium [A47]

Presenter: Kyle Joseph Grosso

Faculty Sponsor: Zaur Rzakhanov

School: UMass Boston

Research Area: Artificial Intelligence

ABSTRACT

The rapid development of generative artificial intelligence (AI) in finance and accounting has changed how financial fraud is committed and detected. This descriptive, non-causal study examines annual data from the Federal Trade Commission’s Consumer Sentinel Network Data Books on imposter scam reports and reported losses and the FBI’s Internet Crime Complaint Center (IC3) Internet Crime Reports on business email compromise (BEC) complaints and adjusted losses from the period 2019 - 2024. Each series is summarized with trend figures and year-over-year growth calculations. Reported imposter‑scam losses rise from $0.67 billion in 2019 to $2.95 billion in 2024, while imposter‑scam reports increase from 647,472 to 845,806, with some fluctuation. BEC adjusted losses increase from $1.78 billion in 2019 to a peak of $2.95 billion in 2023, then decline to $2.77 billion in 2024, while BEC complaints average near 20,000 each year. To compare fraud trends alongside regulatory responses, a dated regulatory timeline consisting of notable announcements, alerts, and enforcement actions regarding AI-enhanced financial crime during this time period is compiled, and these events are placed alongside each series. This comparison establishes whether changes in financial fraud align with changes in regulatory activity. As an extension, a monthly series will be created to examine trends from the Consumer Financial Protection Bureau in complaint narratives which include AI-related terms during this period, with time trend regression models using ChatGPT’s first release: November 2022, as an intervention point. This thesis is designed to help define an evolving “arms race” between regulators and fraudsters.