Mark Lokanan|Susan Liu
Predicting Fraud Victimization Using Classical Machine Learning
Royal Roads University|Royal Roads University
protecting financial consumers investment fraud recurring problem canada purpose paper predict demographic characteristics investors likely victims investment fraud data paper came investment industry regulatory organization canadas iiroc database january 2009 december 2019 total 4575 investors coded victims investment fraud study employed machinelearning algorithm predict probability fraud victimization machine learning model deployed paper predicted typical demographic profile fraud victims investors classify female poor financial knowledge know advisor past retired investors characterized limited financial literacy longtime relationship advisor reduced probabilities victimized however male investors low moderatelevel investment knowledge likely preyed upon investment advisors statistically significant older adults general greater risk victimized findings paper used canadian selfregulatory organizations securities commissions inform investors protection mandates