Digital banking: Clouded thinking

Duncan Kerr
Published on:

Big data, analytics and technology have the potential to transform the global investment banking industry into a leaner, meaner and better-equipped money making machine. Some investment banks have recognised the opportunity. Few, if any, have worked out how to make it happen.

Big data
Can investment banks turn the digital challenge to their advantage? Illustration: Jacey Tech

Walk through the main trading floor of any global investment bank and amid the dizzying rows of flashing screens and the intoxicating buzz of wheeling and dealing, there lingers a thick air of fear and paranoia.

Such are the demands of financial regulators the world over that almost everything that goes on in there is recorded and monitored by compliance teams trying to safeguard the bank from illegal securities sales and trading activity.

From phone conversations, to emails, to instant messaging and social media use, most of what is said and done is more closely watched today than ever before, oversight that is sucking much of the once ubiquitous buzz from these floors.

The financial crisis and the damaging scandals that have broken since in the interbank and foreign exchange markets have made this Orwellian-like surveillance a new imperative for banks, where some of the most sophisticated technology is being employed to ensure their staff stay the right side of the law.

But what if this technology and the rich flow of data that comes from thousands and thousands of phone calls, emails, messages and social media use could be used for a different, potentially more lucrative, purpose?

Indeed, what if investment banks could use the masses of data they accumulate to help ensure they win more deals, to enhance their view of and raise client profitability, to map out specific market and company exposures, and ultimately deliver to clients precisely what they want, and when they want it?

Each investment bank needs to look hard
at how they are optimizing their data usage because
if they’re not doing that, others will

Jason Batt

Such blue-sky thinking may sound fanciful but, faced with the twin challenges of driving profits and reducing costs, it is exactly the kind of new thinking that any global investment banking chief needs to be engaged in.

This is the realm that technologists call 'big data’, where bulbous-brained data scientists and architects use advanced analytics and technology to extract as much insight as possible from all the tera, peta and exabytes of data that is generated daily by the increasingly digital world we all live, work and trade in.

Some of this information within investment banks is structured data such as capital markets transactions, trades, financial markets data, emails, documents, client queries and more. But much of it is unstructured data that is gleaned from other sources that have exploded in use in recent years such as blogs, Facebook posts, tweets, smartphone apps, electronic sensors and pictures, and YouTube video clips.

But the real value is not in the wealth of data itself, but in what investment banks might be able to do with it.

For years the technology titans of Amazon, Google, Facebook, eBay and even Twitter have blazed a trail in using such analytical techniques to track consumer behaviour and propel their businesses forward at a terrific pace. And yet it is only recently, if at all, that the top tier of investment banks, and the executives who run them, have begun to embrace data analytics in a similar way.

"Automation is inevitable," says Paul Walker, co-head of Goldman Sachs’ technology division. "Lest you doubt it, how many people are actually selling US equities over the phone anymore versus how many that were in say, 1990?"

He adds: "The coupling of automation for fulfilment with data is incredibly important to the success of our industry. We think that an investment bank that embraces that successfully will inevitably be the winner in the 2020s."

Digital dilemma

No one global investment bank could claim to have successfully cracked the digital challenge thus far, but look a little deeper into the global markets businesses of some firms and there are examples around how they are thinking about and using big data and analytics to try to do what they do better, faster and far more efficiently.

Some investment banks, says Rupesh Khendry, head of worldwide capital markets at Microsoft, are already using big data analytics to almost immediately assess the impact of the escalation in geopolitical risk on portfolios and their exposures to specific markets or asset classes by combining structured data with the throng of unstructured data that comes from tweets and news.

Similarly, Walker says that at the centre of Goldman’s risk management processes and technology is SecDB, an enterprise-wide database and pricing system, which can model the effects of dynamic market conditions and, in real-time, calculate financial exposure relative to investment positions. 

"This modelling tool considers all of financial positions across the firm and allows for us to run scenarios to improve our understanding and better manage our risk profile for the firm and our clients," he says.

The use of big data analytics can also be seen in other front and back office areas such as in credit line approval in securities trading; real-time economic or inflation indicator analysis; collateral management; credit valuation adjustment calculations; and advanced mortgage analytics.