Article by Brian Clifton, Sam Lavigne, and Francis Tseng.
Published by The New Inquiry Magazine.
Financial crime is a rampant but hidden threat. In spite of this, predictive policing systems disproportionately target “street crime” rather than white collar crime. This paper presents the White Collar Crime Early Warning System (WCCEWS), a white collar crime predictive model that uses random forest classifiers to identify high risk zones for incidents of financial crime.
See the related software application developed to predict White Collar Crime Risk Zones. It uses machine learning to predict where financial crimes are mostly likely to occur across the US. Created by Brian Clifton, Sam Lavigne and Francis Tseng.