The purpose of the study was to 1) iterate through fraud pattern changes, 2) detect anomalies using strong data profiling, and 3) study fraud indicators, derived from the current transaction attributes as well as cardholder’s historical activities. We built models using algorithms and machine learning. We provided more predictive capabilities that could identify and mitigate fraud.