Smart data analytics is set to become a new competitive battleground in 2017 as the pressure on bank FICC desks to perform become even more unrelenting. These desks are under massive cost pressures as they attempt to build up and repair balance sheets in a challenging market and in the face of stiff competition trying to do the same.
Against this backdrop it is more crucial than ever that they find trading opportunities quickly and equip themselves with the tools and insight to react effectively. That means the application of smart data analytics – multiple, non-standardised data feeds are a thing of the past.
2017 will likely see continued cost cutting at FICC trading desks, with significant staff cutbacks, hiring freezes and restructuring programmes. Many large sell-side firms will be looking to adopt differentiation strategies by focusing on specific instruments and geographies instead of general market coverage.
This logic will also be applied to sell-side clients, as sales and trading teams seek to sever ties with unprofitable trading relationships, focusing on fewer, typically higher value accounts. Meanwhile regulatory costs will continue to mount as firms seek to prepare themselves for the arrival of MiFID II.
Advances in data analytics and machine learning, blockchain and ‘Regtech’ will continue, spearheaded by young and nimble financial technology companies, often in partnership with leading investment banks. In fact, FICC teams which proactively start using predictive data analytics will boost profitability by as much as 20% by 2018, according to a detailed report by Gartner.
Failing to plan how to use data analytics over the coming years is simply planning to fail. It will be the difference between success and failure for some desks. Applying real-time data analytics to electronic trade flows will help the productivity of their sales and trading teams through smart, timely business intelligence.
There is a clear and present need for trading desks to derive value from their transaction data, rather than simply storing it as a by-product of an operational process. We have spent the last 12 months developing and fine-tuning our proprietary predictive data analytics solution, which enables traders to predict future client trading behaviour based on historical patterns.
Every bank and fund I speak to says the same thing: that they have to get smarter and need to derive more value and insight from their data to gain a competitive edge. We couldn’t agree more. Smart data and analytics are the future for financial markets, and 2017 will be the wake-up call for many.