Wells Fargo has gathered electronic data on its customers for decades, but it is only in the past few years that the fourth-largest U.S. bank has learned how to put all that information to work. Big banks are embracing data analysis as a means to pinpoint customer preferences and, as a result, also uncover incremental sources of revenue in a period of stalled revenue growth.
"There are new technologies now available that allow us to leverage that data," said John Ahrendt, Wells Fargo's senior vice president of enterprise data and analytics. "And the price point for working with large sets of data has come down substantially."
JPMorgan Chase, Bank of America, Citigroup and Capital One are also taking advantage of the big data opportunity.
In the past, banks primarily used data for core numbers-crunching, such as analyzing customers' creditworthiness, but increasingly they are using it to explore new areas such as sentiment analysis, to determine how customers are feeling about the overall user experience.
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"There has been a data explosion," said Howard Rubin, president and chief executive at technology consultancy Rubin Worldwide, which advises large banks. "Data storage at the big banks is growing at a rate of 45 percent per year." Rubin estimates that approximately one-fourth of the new data is regulatory. "For consumers, it's about keeping more historical pattern data available in real-time."
Last year, Wells Fargo became so convinced of the big data advantage that the bank launched its own enterprise big data lab, where the bank's various businesses can experiment with the latest data analysis tools.
Today, Wells Fargo customers typically interact with the bank on many channels and platforms, including the Internet and mobile devices. Each of these interactions provides the bank with an opportunity to more accurately identify the customer's specific needs and interests.
Ahrendt compares the big-data-enhanced banking environment to the neighborhood grocer. In the old days, the grocer knew each customer personally and could recommend cuts of meat based on previous purchases and knowledge of their tastes. Banks like Wells Fargo have millions of customers but can now act like the neighborhood grocer thanks to predictive analytics culled from data sets that are growing exponentially.
"Our primary focus has been on customer service," Ahrendt said.
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By analyzing every transaction, each service inquiry and mouse-click, banks can look for patterns of behavior and learn how customers prefer to interact and what products they may require in the future. The banks are also using data to track consumers' shopping habits to alert them to targeted deals.
Capital One, which recently purchased online-only bank ING Direct and renamed it Capital One 360, now offers discount deals through email and its mobile app that are customized based on the user's past purchases. To take advantage of the deals, the user simply pays with his or her Capital One credit card.
Bank of America has a similar mobile initiative called BankAmeriDeals, which has plans to implement geo-location technology to notify customers when they are near a retailer for which they have a coupon.
Bank of America's head of ecommerce technology, Hari Gopalkrishnan, said data analysis is making the bank more customer-focused. For example, the analysis has shown that mobile is becoming the bank customer's preferred channel.
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Mobile, said Gopalkrishnan, creates a virtuous circle for Bank of America, lowering the average transaction cost while providing customers with the anywhere-anytime services they have come to expect. The key to success is to make sure "we are transparent about what we collect," making customers aware of the kinds of information the bank retains, and giving them the choice to opt out, said Gopalkrishnan.
Rubin said banks are under tremendous pressure to squeeze value out of their transactions, which have increased 10 to 20 percent annually in recent years, even as overall revenues have stagnated. Big data provides a way to increase revenues without adding astronomical IT costs. "The cost of big data is really in the people who are looking at the data and making decision based on it," he said.
JP Morgan has begun combining its own transactional data with publicly available economic statistics. Citigroup is offering commercial customers transactional data from its global customer base, to enable them to pinpoint new trade patterns.
Mindful of privacy concerns, however, banks do not pursue every big data opportunity at their disposal.
Bank of America, for example, has a Facebook banking page. "Technically, we could give access to bank accounts on Facebook, but we choose not to, based on feedback from our customers," Gopalkrishnan said.
Indeed, even if data analysis can be turned into a competitive advantage, large banks are reluctant to characterize the current rush to capitalize on it as a technological arms race. Said Wells Fargo's Ahrendt: "Our best competitive edge is our people working directly with our customers."
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