Fraud Analytics

4 credits

In this course students will learn everything they need to know to build statistical/machine learning models to find fraud in data events. We will cover the basics of building fraud models: understanding the problem dynamics, modes of fraud, data analysis, and preparation, building expert variables/features, different algorithm choices, and measurements of model goodness. Students will not receive credit for both MGTA 463 and MGTA 463R. Prerequisites: restricted to MS in business analytics students or instructor approval or department approval.