Amanda Raad and Rosemarie Paul from Ropes & Gray look into how the FCA are adapting their priorities to  “work with firms to promote and embed healthy culture, focusing on four drivers of behaviour – purpose, leadership, reward and managing people and governance.”

Regulators are increasingly using data analytics during investigations and compliance exercises. However, the benefits of data analytics as a risk management and investigation tool is useful in helping detect and investigate any form of white collar crime.

The backdrop to this is the ever increasing volume of data that companies hold that they regularly use to increase business and make the processes more efficient or to interact with customers more effectively.  They don't always use that same data to monitor for and tackle white collar crime, and it should be used for risk management and investigations.

There are many advantages associated with data analytics throughout the timeline of an incident, be it:

  • to help identify areas within a business to focus attention on;
  • as an integral part of any audit or risk management program;
  • to analyze the population of data looking for unusual transactions, patterns or relationships within the data; and/or
  • to test hypotheses; if there are suspicions it can be used to validate and quantify the extent of what is suspected.

Data analytics should not be seen as a separate, standalone task, but should be fully incorporated within the overall scope of the matter.  It can then feed into and be fed by the overall work program and add the maximum value, including enriching the data with appropriate external data sources.  Specific tests and approaches will vary greatly depending on the matter in hand and the nature of the industry involved, but there are a large inventory of tests, tools and approaches that can be invaluable to detect and investigate white collar crime.

Data is a key source of intelligence and evidence and should not be overlooked!