Fraud Detection and Fraud Prevention AnalyticsAM2017-10-24T16:37:26+00:00
The universal problem is how to quickly determine the root cause of incidents and then contain and remediate them. Once this is completed, the goal is to return intelligence from the analysis back into the system for proactive diagnostics and mitigation for continuous cybersecurity improvement
Purpose of the Study
The purpose of the study was to make as many systematic decisions as possible in order to lower overall overhead costs and ensure optimal customer experience and continuous cyber security enhancements.
We performed fraud analytics and fraud prevention analytics. We collected, processed, and analyzed all characteristics of a transaction and focusing on people, process, and technology needed to improve fraud rates. We iterated through fraud pattern changes, detected anomalies using strong data profiling, and studied 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.