WHY THIS MATTERS IN BRIEF
With massive technology budgets and a paranoia of startups stealing a march Wall Street is going all in on innovation and automation.
With companies like LawGeex and ROSS Intelligence trying to automate the legal world it was only a matter of time before the technology started stomping all over the legal teams at a big bank, and now it has. Or at least it’s started to. At JPMorgan Chase, a learning machine is parsing financial deals that once kept legal teams busy for hundreds of thousands of hours. The program, called COIN, for Contract Intelligence, automates mind numbing task of reading and interpreting commercial loan agreements which, until it went online late last year, consumed over 360,000 hours of work each year by lawyers and loan officers. Now it’s done in seconds and with fewer errors by a system that never sleeps.
While the financial industry has long touted its technological innovations, a new era of automation is now sweeping the industry as cheap computing power converges with artificial intelligence (AI), and fears of losing customers to start ups. Made possible by investments in machine learning and a new private cloud network, COIN is just the start for the biggest US bank. The firm recently set up technology hubs for teams specializing in big data, robotics and cloud infrastructure to find new sources of revenue, while reducing expenses and risks. The push to automate “mundane tasks” and create new tools for bankers and clients, is a growing part of the firm’s $9.6 billion technology budget.
Behind the strategy, which is overseen by COO Matt Zames and CIO Dana Deasy, is an undercurrent of anxiety. Although JPMorgan emerged from the financial crisis as one of few big winners, it feels its dominance is at risk unless it aggressively pursues new technologies.
After visiting companies including Apple and Facebook three years ago to understand how their developers worked, the bank set out to create its own hybrid computing cloud called Gaia that went online last year. AI, under the auspices of machine learning, and the bank’s big data projects now sit on top of Gaia, which effectively has limitless capacity to support its thirst for processing power.
The system already is helping the bank automate some coding activities and making its 20,000 developers more productive and saving money, and when needed, the firm can tap into the resources of public cloud providers such as AWS, Google, IBM and Microsoft.
JPMorgan’s total technology budget for this year amounts to 9 percent of its projected revenue, double the industry average and the dollar figure has inched higher as JPMorgan bolsters cyber defenses after a 2014 data breach, which exposed the information of 83 million customers.
“We have invested heavily in technology and marketing, and we are seeing strong returns,” said Deasy, and now over a third of the company’s technology budget is for new initiatives – a figure Zames wants to take to 40 percent in a few years. He expects savings from automation and retiring old technology will let him plow even more money into new innovations.
Not all of those bets, which include several projects based on distributed ledger technology, like blockchain, will pay off though and the company’s okay with that. One example executives keep mentioning is an electronic platform to help trade credit-default swaps that sits unused.
“We’re willing to invest to stay ahead of the curve, even if in the final analysis some of that money will go to product or a service that wasn’t needed,” said Marianne Lake, the lender’s finance chief, “but that’s okay because we can’t wait to know what the outcome, the endgame, really looks like, because the environment is moving so fast.”
As for COIN, according to its designers, the program has helped JPMorgan cut down on loan-servicing mistakes, most of which stemmed from human error in interpreting 12,000 new wholesale contracts per year, and now the bank is scouring for more ways to deploy the technology, which learns by ingesting data to identify patterns and relationships.
The bank also plans to use it for other types of complex legal filings like credit-default swaps and custody agreements, and someday, they may use it to help interpret regulations and analyse corporate communications.
Another program called X-Connect, which went into use in January, examines E-Mails to help employees find colleagues who have the closest relationships with potential prospects and can arrange introductions.
For simpler tasks, the bank has created bots to perform functions like granting access to software systems and responding to IT requests, such as resetting an employee’s password, and the bots are expected to handle 1.7 million access requests this year, doing the work of 140 people.
While growing numbers of people in the industry worry such advancements might someday take their jobs, many Wall Street executives are more focused on benefits.
A survey of more than 3,200 financial executives by recruiting firm Options Group last year found a majority expect new technology will improve people’s careers, for example by improving workplace performance. However, ultimately, there will come a time when the human-hybrid model falters and when the machines simply take over, as is already being witnessed at two of Wall Street’s largest players Goldman Sachs and Bridgewater Associates.
“Anywhere you have back office operations and humans moving information from point A to point B that’s not automated is ripe for automation,” said Deasy, “people always talk about this stuff as displacement. I talk about it as freeing people to work on higher value things, which is why it’s such a terrific opportunity for the firm.”
That is of course, unless you happened to be one of the data shufflers that just got automated… This kind of corporate language is common among executives who are keen to extoll the upsides of technology and not the downsides.
To help spur internal disruption, the bank now keeps tabs on 2,000 technology ventures and is running over 100 pilot programs with a number of partners who’ve joined its new innovation ecosystem. For instance, the bank’s machine-learning software was built with Cloudera, a software firm that JPMorgan first began working with in 2009.
“We’re starting to see the real fruits of our labor,” Zames said. “This is not pie-in-the-sky stuff.”