Only 21 years old, McLean, Va.-based Capital One boasts some 72 million customer accounts and $218 billion in deposits, making it not only one of the top 10 largest banks in the United States, but the only top 10 U.S. bank to have been founded within the last 100 years. It’s by far the largest digital bank; a widely acknowledged leader in the development of mobile consumer banking innovations; and an ace when it comes to leveraging such high-impact social media platforms as Facebook, Twitter, and Pinterest.
The key to the bank’s meteoric rise? “We’re a company that was founded on the notion that you could build a better business strategy by leveraging data analytics,” said Capital One CIO Rob Alexander in a Jan. 15, 2016, address to some 70 M.S. in MIT students. The address, given in McIntire’s Robertson Hall and titled “Big Data Transformation at Capital One,” was jointly delivered with Capital One Vice President of Enterprise Architecture and Data Services Jeff Chapman as part of a daylong M.S. in MIT session on big data and business strategy.
“We were incredibly privileged to have the chance to hear from Rob and Jeff, both of whom are really working at the forefront of big data analytics,” says McIntire IT Professor Ahmed Abbasi, who teaches in the M.S. in MIT Program and serves as Director of the School’s Center for Business Analytics. “Capital One stands out not only for its highly effective utilization of analytics within the banking industry, but as a truly visionary organization—across all industries—in its understanding of the strategic potential of big data.”
The Future Lies Ahead
But as big data becomes ubiquitous, and as the landscape of big data-related technology continues to shift, how will the company position itself for continued leadership?
The beginning of the answer, Chapman told listeners, lies in the “explosion” of innovation that has occurred, largely since 2012, in the development of open-source technologies and platforms such as Hadoop, H2O, and Cloudera, and the resulting stunning advances not only in data collection, but in such value-extracting capabilities as machine learning and pattern recognition. Such new technologies, he explained, allow not only for the low-cost storage of mind-boggling amounts of data—“we’ve moved from terabytes to petabytes,” he told the audience—but, critically, for the virtually instantaneous and highly accurate analysis of that data.
“We’re talking about an absolute revolution in big data capabilities,” Chapman said, noting the increasing potency of technological capabilities as drivers of business strategy. “Open-source technology is one of the most dynamic, exciting, and transformational forces in business today.”
Big Data, Big Changes
Accordingly, Alexander and Chapman said, Capital One has likewise begun to transform itself, embarking on what Alexander characterized as “a wholesale reinvention of how we do data and analytics.”
“As technology changes, our company has to change,” he told the audience. “Our thinking has to change with regard to where we can find leverage and create value, and we have to really rethink our strategy and architecture around data.”
As the company has long understood, all the data in the world is worthless—or worse—without the analytic capabilities to generate meaningful insights that can be used to help support an outstanding customer experience. “Rich Fairbank, our Founder and CEO, started out with the notion that we could really understand our customers through data analysis—and that notion absolutely lies at the heart of our company, and at the core of everything we do,” Chapman said.
Now the company is taking that notion and moving forward with it—at hyper-speed—to make use of the new open-source technologies in new ways that are powerfully relevant to today’s banking customers.
“We’re now able to use big data to extract insights we couldn’t get before,” Alexander explained. “On top of that, we’re able to build models and software applications that can actually predict what a customer wants or means to do. We can put those models into the production systems where the customer interactions actually happen, into what we call the fast data stream. We’re capturing the data, looping it back into the data link, and analyzing it with a very high level of refinement—and all in real time.”
Translation: You pay for a meal at restaurant. You swipe your Capital One credit card, and add in a generous 20 percent tip. But when the payment is processed, the tip is erroneously inflated to 60 percent. In fewer than 30 milliseconds, your credit payment data is fed into the data link, analyzed through comparison to your recent and historical spending and tipping history, red-flagged—and you’re sent a text or email message before you walk out of the restaurant. Similar capabilities are already being utilized to detect—and even instantaneously block—fraudulent purchases, or to draw your attention to questionable fees or payments, among countless other possible high-value uses.
“Our business is built on intangibles—on customer experience, and on the outstanding software, supported by high-grade analytics, that makes that experience great,” Alexander said. “It’s this powerful new real-time integration of operational data and analytical capabilities that’s really going to take us into the future.”
But to make the most of the breathtaking advances in technology, Chapman said, the company needs lots of a very traditional—if scarce—resource: talented, innovation-oriented, forward-looking people. As the need for quality, agility, and responsiveness increases, so has Capital One’s need to have the best people in-house. “We’re engaged in a real talent transformation,” Chapman said, noting that the company hired some 1,500 people in 2015, mostly software engineers, and aims to hire some 1,800 more in 2016.
Indeed, he told listeners, as the company continues to strategically reposition itself for ongoing leadership in an environment characterized by hot competition and rapid evolution, the ability to attract top talent will prove increasingly critical. “That’s where the great divide is going to emerge: between companies that are able to attract top talent and expertise and those that aren’t,” he said.
“The message for today,” he told the M.S. in MIT students, “is ‘Get ready to go really fast—and then to go even faster.’”