JPMC Delivers on a Visionary Machine Learning Future with Cloudera

Documents cited: Bloomberg, JPMorgan Chase



At Cloudera, we aim to help organizations apply machine learning and advanced analytics to their most critical business problems. Whether that is detecting sepsis rates in hospital patients, identifying genetic variables that may manifest in future illnesses, detecting malicious behavior or access to customer information, or identifying the trends that predict underground child trafficking. We believe data and data science can be a force for good in the world, with an impact that can be felt at every rung of society. Sorting success from failure is often as easy as looking at the investments a company is making on technology to differentiate their platform, service, or product experience.

JP Morgan Chase is a well established leader in commercial banking and not by accident or convenient geography. JPMC has made it a company mandate to lead with technology innovation, ensuring that every solution they build and partner they onboard has an expressed intent to benefit the business. In financial services, risk and reward are all part of the recipe of a market dynamic. One of the reasons JPMC has weathered the changes so well is their ability to adapt to the needs of their customers, the market, and all of the extenuating circumstances. It is best detailed in a recent report from Bloomberg reporting how the bank’s technology team is marshalling an army of developers to automate high finance.

JPMorgan emerged from the financial crisis as one of few big winners, its dominance is at risk unless it aggressively pursues new technologies, according to interviews with a half-dozen bank executives. They have even stated, ‘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.”

So what type of bets has JPMC made over the years and how do they operationalize those efforts?

“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. To help spur internal disruption, the company keeps tabs on 2,000 technology 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.

In the world of banking, some jobs may be considered mundane or viewed as pushing information from one place to another. In these instances machines may be better suited for the task, freeing up valuable brainpower for more high order activities which is the exact reason JPMC created COIN (Contract Intelligence). COIN in their own words….

“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.

“Anything where you have back-office operations and humans kind of moving information from point A to point B that’s not automated is 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.”

JPMC has leveraged Cloudera’s platform to power some of their most aspirational use cases. In contrast to their legacy installations, Cloudera brings the vast opportunity of open source data science and machine learning. This is all delivered with familiar tools and API’s to help bolster delivery of business capabilities. JPMC applies this technology to a variety of business solutions as detailed in their 2016 annual report.

Our relationships with the external technology ecosystem helped drive value across our technology focus areas, including next-generation data and analytics platforms, such as Hadoop and Spark. To maximize the impact of these new data platforms, we have doubled our big data infrastructure consistently year-over-year. We now can access and analyze data in ways that we could not have done before. For example, last year, we re-engineered our Market Risk platform, one of the largest in-memory risk analytics platforms in the world. The platform now manages over 1 billion risk sensitivities and provides visibility 17 times faster than the prior system while delivering a more granular and holistic view of the firm’s risk exposure.


Cloudera has seen a steady rise in data science and machine learning platform use cases. In a recent study of 7,000 Apache Spark professionals over 60% of respondents indicated they use Cloudera for their most critical Spark workloads, data science and machine learning use cases represent roughly 71% of current usage. Cloudera’s platform brings more data to the table, combined with distributed processing leadership with Apache Spark. Since machine learning needs data, Cloudera is well positioned solution for organizations like JPMC to deliver on their future aspirations, as stated by Matt Zames

 

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


 

For more information on Cloudera’s machine learning platform visit our website.