“Big data” is a hot topic right now. It’s clear that companies and government entities are collecting more and more information every year about both the external environment and their internal operations. This, in turn, is driving increased sophistication of data analytics technologies, which have the potential to turn big data into insights. But it’s not necessarily clear how specific corporate functions can utilize big data to improve their value to the organization.
Treasury & Risk sat down with Brian Loughman, Americas leader in the Fraud Investigation and Dispute Services practice at EY, LLP, and Scott Keipper, principal and reporting lead for the Americas Enterprise Intelligence practice at EY, LLP, to explore the opportunities for corporate treasury, finance, and risk management functions to put big data to work.
T&R: When they implement big-data solutions for other purposes, are these treasury and finance functions also gaining new insights into key performance metrics?
SK: Yes, absolutely. Traditionally, finance functions have had access to subledger data, and they’ve been able to do a certain amount of analysis on that data to support financial disclosure. They may have also supplemented that analysis with information from the lines of business or risk management, but the data was disparate, challenging to obtain, and even more difficult to reconcile. As they have access to more robust solutions, they can dive deeper into the data.
T&R: What are some specific performance or risk metrics that companies are pinning down by delving into unstructured data?
BL: Well, I’m sure you’ve heard a lot about all the various compliance issues financial services companies have been dealing with, such as allegations of improper trading, insider trading, and interest rate fixing. Big data can actually be used to ferret out these kinds of activities. It’s not uncommon for all the traders in a market—trading a particular security or currency—to instant message each other all the time. All of that is saved, and some organizations are using software systems to survey it and identify periods of time or certain traders that are causes for concern.