Big Data At J.P. Morgan: Delivering The Firm
What’s your take on big data and its potential for Treasury Services at J.P. Morgan (New York; $2.3 trillion in assets)?
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Shah: We’re looking at the broad forces shaping banking and how to use them to drive more value for our clients, how to apply them in the wholesale banking arena. At the highest level there are three macro forces shaping the world of banking: globalization, regulation and technology.
Under the technology umbrella we are exploring social (or the power of networks), mobile, cloud computing and big data. Our chief information officer’s [Guy Chiarello] organization serves as the key bridge between the lines of business, allowing us to leverage the information that’s critical to the big data effort — for example, insights from consumer spending patterns that we can deliver to corporate clients in a meaningful way, or trends in wholesale payments that will shed light on macroeconomic trends.
Big data encompasses advances in hardware, software and mathematics, but in its essence, it’s about creating insights from information. It can help our clients be more effective by building deeper relationships with their customers — reducing risks and costs. At J.P. Morgan, it can help us operate more effectively.
For example, within our Corporate and Investment Bank (which is how we look at our institutional-facing businesses), we offer a large number of products and services to help institutional clients (companies, governments, other financial institutions). Big data helps us to identify the best set of products we can deliver to the client —getting the right product to the right client, at the right time, through the right channel. Bringing the full capabilities of our diverse and global firm to bear for our clients in a context-relevant way is a great opportunity — what [CEO] Jamie Dimon refers to as “delivering the firm.”
How are you doing that?
Shah: One example is enriching payments messages with context-relevant information in addition to that required to exchange value. For example, an insurance company paying a customer for a claim may provide information in a payment message that would help the customer deal with his/her particular damage. A key channel for that — this is where the key forces intersect — is mobile. Overcoming some of the information-carrying limitations of existing payment systems, mobile offers an opportunity for the payment to “do more” for both sender and receiver, and create value in the process.
Is this a capability you’re actually pursuing?
Shah: We’re working on that now. In the spring we’ll be piloting some solutions that bring together the power of mobile and data. The payment then becomes a brand champion for the company with its own customers and suppliers.
We have been leveraging data and analytics in other areas. For example, we’re able to digitize remittance information coming into our lockboxes and make that information available to clients, giving them insights into how their business is performing. Clients can use information flowing through a lockbox to improve the posting of transactions to their receivables systems, address customer inquiries more effectively and use the information for cash forecasting. They also want to know how they perform against their peers, and we can provide benchmarking information. These are ways in which we are already leveraging the power of data and analytics to drive value for our clients.
What about areas such as compliance, security and risk management?
Shah: The Dodd-Frank regulations require financial institutions to deliver much more information about payments than before, particularly as it relates to cross-border money transfers. As a bank to banks, we make our knowledge base of global payments, including how payments clear across various payments systems worldwide, available to our financial institution clients to save them costly investments. Additionally, maintaining the safety of the payment system is a key role for banks, having the ability to apply matching algorithms and big data techniques to reduce false positives and false negatives in the transaction screening process. This has a huge impact on the client experience and the safety of the payment system by catching illicit transactions and letting the good ones through.
What kinds of infrastructure and systems investments has the bank made to enable these kinds of capabilities?
Shah: The cloud allows us to realize the potential of data. J.P. Morgan Access Next Generation, our client Web portal, allows clients to easily access and analyze their banking information to optimize working capital. Additionally, we are leveraging cloud internally to make software and data available to developers and other end users within the bank, driving efficiencies in the delivery, maintenance and use of such services. We also are integrating data resident in various systems so that it’s available for analysis. The many-to-many data-sources-to-applications problem that is typical of complex and mature systems becomes rationalized to one-to-many, creating more efficient flows of data. We also are making investments in other capabilities important to big data, such as storage, visualization and predictive analytics.
Are you seeing any changes in the bank’s decision-making process?
Shah: The traditional approach to problem solving has been that you start with a view of the end and you tailor your analysis around that. Big data, with the ability to automatically process large amounts of information and render it in different ways, allows for the identification of opportunities in a way that doesn’t always begin with a directed question or hypothesis to be proven or disproven. We let the data “speak,” for example, revealing patterns in buying behavior or connectivity between nodes in our client network, and it leads the way. That’s the promise of big data.
[The Morality of Big Data]
What are the barriers to realizing the potential of big data, and what’s the bank doing to address these issues?
Shah: As with any analysis, there’s a junk-in, junk-out problem. The noise-to-signal ratio is pretty high in the deluge of data. So we are spending time cleaning our data so we can improve the quality of the analysis. We’re also trying to propose simple problems to big data and use agile methodologies to do it in bite-size chunks. For example, can we reduce false positives and false negatives in transaction screening? That’s a fundamental question, with an outcome, by which we can measure success or lack of success.
Another opportunity is data governance. For example, we are zealous about protecting client information, and even within our own company, it can be difficult to access information. So we’re establishing a data governance model, which is a set of principles and rules defining who owns the data, who has access to data, how it’s made available and who has the responsibility to maintain it on an ongoing basis so the clutter doesn’t become too much. This work happens up front and is done across the lines of business in partnership with the technologists. It paves the way for sustainable gains from big data efforts.
Vipul Shah has global responsibility for strategy and business development for J.P. Morgan’s Treasury Services operations. He looks for new growth opportunities, as well as ways the bank can deliver value to corporate clients from transformational technology trends such as big data.
Katherine Burger is Editorial Director of Bank Systems & Technology and Insurance & Technology, members of UBM TechWeb's InformationWeek Financial Services. She assumed leadership of Bank Systems & Technology in 2003 and of Insurance & Technology in 1991. In addition to ... View Full Bio