Big data

An EY survey indicates that companies need to look at a broader set of risks, incorporate more data sources, use better tools and move to real-time or near real-time analysis of increased data volumes. The results? More effective and efficient compliance programs that are highly focused on key fraud risk areas.

A leading global pharmaceutical company, we'll call it Pharminc, sought to use forensic data analytics (FDA) to monitor compliance with policies and procedures designed to govern interactions between their sales representatives (REPs) and the health care professionals (HCPs) they interact with in certain high-risk countries. Many anti-fraud practitioners in the past — using traditional FDA methodologies — would consider only one primary data source for analysis, such as travel and entertainment accounts. Pharminc took a different approach and incorporated "big data" thinking. The company not only used traditional spreadsheet and database applications, it integrated multiple structured and unstructured data sources with more sophisticated visual analytics and text mining applications.

These data sources included speaking events data, travel and entertainment accounts, product samples, sales and customer relationship management data, physician interaction data and even social media data.