Fraud mitigation requires technologies and business processes that are flexible in their construct, easily understood by all who are involved in fraud prevention, and are agile enough to adapt to new attacks without needing to be rebuilt from scratch.
Data from all business units and functional silos must be included to create a holistic view of the success of fraud operations. The insight found in classical auditing techniques and predictive machine learning models, combined with the expertise of fraud analysts can foster an evidenced-based methodology to quickly respond to new financial crimes.