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JPMorgan Chase & Co are using machine learning to review financial deals in seconds, that usually keep their legal teams busy for thousands of hours.

The program, called COIN, for Contract Intelligence, does the mind-numbing job of interpreting commercial loan agreements that, until the project went online in June, consumed 360,000 hours of work each year by lawyers and loan officers. The software reviews documents in seconds; is much less error-prone and doesn’t need a lunch break.

While the financial industry has been lagging behind its disruptors in terms of technological innovations, we have now entered a new era of automation, as cheap computing power combines with fears of losing market share to innovative startups.
COIN has been made possible by investments in machine learning and a new private cloud network. It is just the start for the biggest U.S. bank. The firm recently set up tech hubs for teams specializing in big data, robotics and cloud infrastructure to find new sources of revenue, while reducing expenses and mitigating risk.

The necessity to automate tasks and create new tools for its bankers and clients has seen this area being allocated increasingly more budget from firm’s $9.6 billion technology budget.

Behind the strategy, overseen by Chief Operating Operating Officer Matt Zames and Chief Information Officer Dana Deasy, is an undercurrent of anxiety: Though JPMorgan emerged from the financial crisis as one of few big winners, its dominance is at risk unless it aggressively pursues new technologies.

That was the message Zames had for Deasy when he joined the firm from BP Plc in late 2013. The New York-based bank’s internal systems, an amalgam from decades of mergers, had too many redundant software programs that didn’t work together seamlessly.

“Matt said, ‘Remember one thing above all else: We absolutely need to be the leaders in technology across financial services,’” Deasy said last week in an interview. “Everything we’ve done from that day forward stems from that meeting.”

Matt Zames

After visiting companies including Apple and Facebook three years ago to understand how their developers worked, the bank set out to create its own computing cloud called Gaia that went online last year. Machine learning and big-data efforts now reside on the private platform, which effectively has an unlimited capacity to support their thirst for processing power. The system already is helping the bank automate some coding activities and making its 20,000 developers more productive, saving money, Zames said. When needed, the firm can also tap into outside cloud services from Amazon.com Inc., Microsoft, and IBM.

JPMorgan will make some of its cloud-backed technology available to institutional clients later this year, allowing firms like BlackRock to access balances, research, and trading tools. The move, which lets clients bypass salespeople and support staff for routine information, is similar to one Goldman Sachs announced in 2015.

JPMorgan’s total technology budget for this year is 9 percent of its projected revenue — double the industry average, according to Morgan Stanley analyst Betsy Graseck. The dollar figure has inched higher as JPMorgan bolsters cyber defenses after a 2014 data breach, which exposed the information of 83 million customers.

One-third of the 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 a distributed ledger, like blockchain, will pay off, which JPMorgan says is OK. One example executives are fond of mentioning: The firm built 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,” Marianne Lake, the lender’s finance chief, told a conference audience in June. That’s “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, 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, according to its designers.

JPMorgan is scouring for more ways to deploy the technology, which learns by ingesting data to identify patterns and relationships. The bank plans to use it for other types of complex legal filings like credit-default swaps and custody agreements. Someday, the firm may use it to help interpret regulations and analyze 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, Zames said. 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 personnel are more focused on benefits. A survey of more than 3,200 financial professionals by recruiting firm Options Group last year found a majority expect new technology will improve their careers, for example by improving workplace performance.

“Anything where you have back-office operations and humans kind of moving information from point A to point B that’s not automated, it’s ripe for that,” Deasy said. “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.”

To help spur internal disruption, the company keeps tabs on 2,000 FinTech ventures, using about 100 in pilot programs that will eventually join the firm’s growing ecosystem of partners. For instance, the bank’s machine-learning software was built with Cloudera Inc., a software firm that JPMorgan first encountered in 2009.

“We’re starting to see the real fruits of our labor,” Zames said. “This is not pie-in-the-sky stuff.”