Machines poised to take over 30% of work at banks, McKinsey says

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(Bloomberg) -- New technologies are poised to sweep through investment banks, relieving many rank-and-file employees of roughly a third of their current workload, according to McKinsey & Co. The shift, already stoking angst on Wall Street, may take only a few years.

Cognitive technologies -- applications or machines that perform tasks once requiring human thought -- are now cheap enough that banks can deploy them across operations facilitating trades or other capital-markets business. In a report Thursday, McKinsey said automating tasks will “free up capacity” for staff to focus on higher-value work, such as research, generating new ideas or tending to clients.

“This is really starting to take steam and it’s going to transform the industry over the next two to three years,” Jared Moon, a McKinsey partner who co-wrote the report, said in an interview. The consultants estimate cognitive technologies will free 20 to 30 percent of employees’ capacity in units processing trades.

Automation has been sending shivers down spines across Wall Street, as workers worry they will be replaced by machines that can compile and sift libraries of data, interpret contracts and help clients -- just some of the abilities McKinsey describes in the report. But the consulting firm has a relatively benign message: Companies already making the transition aren’t slashing workforces.

“This helps free up valuable subject experts to do more,” Moon said. “It will require people to use new skill sets, taking away manual work but allowing more around analytics, transformation and change.”

That echoes a view expressed last month by Jamie Dimon, the chairman and chief executive officer of the largest U.S. bank, JPMorgan Chase & Co. Technology creates opportunities while keeping costs at bay, he said, predicting headcount at his firm probably will rise over the next 20 years.

Falling Behind

McKinsey’s report also hints at the flip side to that scenario. Banks that embrace automation will become more efficient, innovative and nimble. But that means competitors failing to make the jump risk falling to the wayside.

Still, examples abound of technology shrinking Wall Street’s armies. Gary Cohn, who last year stepped down as president of Goldman Sachs Group Inc., told investors in 2011 that technology had helped the bank shrink its equities staff by more than half over the previous decade. The trend was similar in currencies. And this week, LinkedIn published a survey of more than 1,000 financial professionals, showing roughly a quarter worry automation will eliminate jobs.

The McKinsey report doesn’t focus too much on the so-called front office, where traders and other rainmakers woo clients and draw in business.

Instead, it measures the potential to reshape realms like the middle office, where employees take trades from traders, and finance, which verifies prices and generates profit and loss statements. In those areas, people may see as much as a quarter of their capacity freed up, according to the report. In areas McKinsey dubs operations, where employees send confirmations to clients and process payments, there’s potential to free more than a third.

Helping Traders

Yet improving technology has significant implications for the front office, because it makes supporting departments faster, cheaper and smarter, according to Moon.

“This has been hugely helpful for traders to serve clients better and improve the ways they hedge,” he said.

McKinsey recently examined the extent to which eight banks have adopted technology for their cash equities businesses. Those relying most on digital execution saw front-office revenue per producer jump by as much as eight times. The firms with the best tech in their post-trade operations posted four times more trades per middle- and back-office employee than competitors behind the curve.

In finance, automation is becoming a very broad term. The McKinsey report looks at the potential for a number of specific technologies to perform an array of tasks.

Here are some of its findings:

  • Machine learning -- which uses algorithms to identify patterns in large sets of data -- can help sales and trading staffs understand positions faster and predict what flows will look like.
  • Natural language processing can perform legal and regulatory tasks by scanning through records, emails and recordings to translate them into structured data.
  • Cognitive agents can act as in-house personal assistants or service centers; think of help desks for trading staffs that have issues with their systems.
  • Robotic process automation -- in which machines handle repetitive tasks -- is particularly effective in banks’ middle offices, where it can help with end-of-day valuations and extract data.
  • Smart workflow tools -- including document scanning and automated data entry -- can speed the process of signing up new clients.

When companies combine those tools, the impacts are magnified, Moon said. Integrating machine learning and robotic process automation, for example, produces “a much greater experience and higher growth,” he said. Plus “it will be easier for that technology to manage all of that code.”

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