There is a grand irony in investment banks – some of the most sophisticated users of data, analytics and technology – failing to use these attributes to help tackle the monumental challenges they face.
What little they are doing so far in ‘big data’ shows this up all too well. While their blue-chip technology clients – Amazon, Google, eBay and Twitter et al – have blazed a trail for years in using big data techniques to advance their businesses at a terrific pace, investment banks are only now beginning to recognize and embrace the power of this scientific phenomenon.
Regulatory pressures have helped force this recognition, but a broader realization is dawning that big data, analytics and technology have huge value for them far beyond their use in fraud detection and regulatory compliance.
Indeed, as Paul Walker, co-head of Goldman Sachs’s technology division, tells Euromoney this month, these three elements combined can enable any bank, big or small, to address some of their most pressing challenges.
“When looking at the future of [the banking] business and what will drive it forward, I think of growth, regulation, the cost base, and capital, liquidity and risk management as some of the top issues,” he says. “I see big data as a technique that allows you, as a bank CEO, to address those four issues more effectively.”
He adds that “automation for fulfilment” coupled with “data is incredibly important to the success of our industry” and those banks that embrace those components successfully “will be the winner in the 2020s”.
The trouble is that for investment banks, using their data in the way they want to, is an almighty challenge, in of itself. Why?
Creaking systems
First and foremost, the systems of investment banks, and the banking industry more broadly, were never built with this type of technological advance in mind.
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Their systems creak under the weight of the new data and information flows, and while they do capture much of this, doing anything meaningful with it is fiendishly difficult because it’s housed in different areas of the banks, which makes accessing and drawing insight challenging.
As one former investment banker, turned technology adviser, explains: “If they want to get close to big data, where it’s almost Nasa-like in its sophistication, investment banks will face multiple challenges. Achieving that will involve centralization of data, of analytics and of reporting. And, as I see it, many investment banks are very far away from that.”
Other less structural, but no less important, challenges include changing internal cultures at investment banks and attracting the biggest and brightest brains in big data, analytics and technology to enable investment banks to make it work.
From the C-suite to the MD-suite, the mindset of investment bankers and traders is all too often short-termist and cynical, which ultimately impedes change. That’s not exclusive to the industry – people find change difficult. But down on the trading floors, the perception is “this is the next person’s problem”.
That next person could be someone hired in from Google, but it’s unlikely.
The cultural differences between an investment bank and a technology firm couldn’t be more stark. That’s one reason why some of the brightest brains in data and analytics are not being drawn to work in investment banks. Another is remuneration – the likes of Google and Facebook are offering so much more.
So can investment banks crack the big data challenge? The answer is they have to. Their success depends on it.