Richard Fairbank: The Scientific Method
We wouldn't be able to ask 'What's in your wallet?' without Capital One cofounder Richard Fairbank's innovations in bringing analytics to the credit cards business.
Understanding how to effectively leverage analytics is one of the hottest topics in banking today. Bankers and regulators recognize the value of applying analytics-related technologies to everything from customer lifetime value to credit risk to channel trends. And vendors have responded with an array of sophisticated standalone solutions as well as by integrating analytics capabilities into core functions as varied as lending, product development, payments, CRM and fraud prevention. The widespread embrace of analytics is enabling banks of all sizes to strive to be "smarter," more responsive and better able to anticipate market changes and opportunities.
But the use of analytics wasn't always so pervasive. While financial services firms have long recognized the value of making better use of customer, risk and performance data, it wasn't until Richard D. Fairbank founded Capital One in 1988 that a company literally based its growth strategies on the ability to drill into customer data, develop targeted products and channels based on the information that came out of that analysis, and also price and underwrite those offerings based on that segmentation. Fairbank essentially made a science of card marketing. According to the McLean, Va.-based company's corporate overview, Fairbank (who now holds the titles founder, chairman and CEO) "founded Capital One ... based on his belief that the power of information, technology and testing could be harnessed to bring highly customized financial products directly to consumers."
Fairbank was not the first to see the potential for analytics -- but he did view its potential differently from his peers at the time, according to Ron Shevlin, senior analyst with Boston-based Aite Group. "Cap One had an analytics-driven culture from the start," he points out. "Fairbank had a strong analytical bent. ... Unlike a lot of other firms, Cap One didn't have to become analytics-oriented; they were born that way."
Shevlin points to a key differentiator between Capital One and other card marketers at the time: "Unlike many other card issuers who used predictive models to drive their marketing campaigns, Cap One was a relentless tester -- they were constantly in the market testing various offers and product combinations," he says. "In contrast, other issuers would develop a predictive model, score prospects and execute [only a few] large-scale campaigns."
As far back as the 1980s, Fairbank, along with eventual Capital One cofounder Nigel Morris, had an idea for a more scientific approach to credit card marketing -- based on a technology-enabled way to analyze and segment customers and develop and price card offerings accordingly. Signet Bank bought into the concept, hired the two men and revamped its card operations based on the their model. What became Capital One Financial Corp. was spun off from Signet in the mid '90s. Today, in addition to being one of the world's largest card issuers, Capital One operates approximately 1,000 branch locations in the U.S. and has operations in the U.K. and Canada. It's currently the eighth-largest U.S. bank, with more than 40 million customers.
A Lasting Impact
Of course, Capital One's use of analytics was not an end in and of itself -- it helped the company develop unique, industry-leading products. "With innovations like teaser rates and zero-balance transfers, Cap One brought a degree of personalization, speed to market and marketing execution flexibility that other firms still aspire to," Aite's Shevlin says.
Though Capital One was founded more than 20 years ago, it has only been within the past decade that analytics have become mainstream in banking. And Fairbank's innovations continue to shape the increasingly complex payments business.
"The potential impact of analytics on the payments business today goes beyond fraud -- it's about predicting purchase behavior," Shevlin observes. "Until recently, a lot of card issuers' analytics efforts were focused on predicting who would be a good credit card customer, and if they could sell a card to that person. Today, the analytics are increasingly focused on analyzing purchase behavior and predicting what cardholders will buy."