Information Systems Education Journal


V19 N1 Pages 16-22

Feb 2021

Can you Predict the Money Laundering Cases?

Richard McCarthy
Quinnipiac University
Hamden, CT USA

Wendy Ceccucci
Quinnipiac University
Hamden, CT USA

Mary McCarthy
Central Connecticut State University
New Britain, CT USA

Nirmalkumar Sugumar
Peoples United Bank
Bridgeport, CT USA

Abstract: This case is designed to be used in a business analytics course; particularly those that emphasize predictive analytics. Students are given background information on money laundering and data from People’s United Bank, a regional bank in the northeast United States. The students must develop their hypothesis, analyze the data, develop and optimize predictive models, and then score the models. Students are challenged to develop a better baseline model than what is currently being used by People’s United Bank.

Download this article: ISEDJ - V19 N1 Page 16.pdf

Recommended Citation: McCarthy, R., Ceccucci, W., McCarthy, M., Sugumar, N., (2021). Can you Predict the Money Laundering Cases?. Information Systems Education Journal19(1) pp 16-22. ISSN : ISSN: 1545-679X. A preliminary version appears in The Proceedings of EDSIGCON 2020