  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.
