While every company has a need for data quality, financial institutions are perhaps the best equipped to put their data to use, compiling accurate contact information, financial statistics and demographic knowledge on their customers. This in turn can help them perform customer analytics. By checking the veracity of the data they compile on their loyal patrons, banks can become more knowledgeable about people's financial habits and customer service needs.
Catherine Bessant, head of global technology and operations at Bank of America, told Information Management that data quality can help banks to pinpoint even the smallest financial trends that might be relevant to their operations.
"Data might tell you that you have a problem that happens only 0.3% of the time, and you might think you have a process or a platform that's in fully in control," Bessant said. "But there could be trends within that 0.3% that are important. How do we make sense of everything that happens underneath the surface to turn it into something we can see?"
One area where high-quality data can improve banks' operations is analyzing the efficacy of different modes of banking. Local branches were once a mainstay with consumers, but they've since become a way of the past - the populace then gravitated toward ATMs, but now those are slowly becoming obsolete as well, as mobile banking gains traction. By compiling data of the utmost quality, financial institutions can paint a clearer picture of their customers' needs, figuring out who prefers what mode of banking, including when, where and how they access their information.
Bessant has already seen verifiable results from the use of data on consumers' banking preferences. After observing the decline of local branches, Bank of America elected to close 260 of them in one year, approximately 5 percent of its total. Then, when the bank noticed dissatisfaction with the clutter of its mobile applications, it began unifying platforms - it now uses 17 percent fewer apps. For example, the bank used to have 22 different collateral management systems, but now it uses just one.
Cashing in on feelings
As CNBC puts it, banks that gather quality data can use it to "cash in on customer feelings." In other words, there's been an evolution from quantitative analysis of financial data to more qualitative uses. In the early days of bank big data, it was used strictly for mathematical calculations, such as how credit-worthy a consumer was, whereas today, financial companies are able to collect data on more subjective elements, such as a person's happiness with the customer experience.
John Ahrendt, senior vice president of enterprise data and analytics at Wells Fargo, told CNBC that banks are now better equipped to make use of subjective data on customers' feelings.
"There are new technologies now available that allow us to leverage that data," Ahrendt said. "And the price point for working with large sets of data has come down substantially."
Because of that lower price point, data quality now appeals to smaller financial institutions as well as bigger ones, as data analysis tools are more affordable even for firms who use them on a small scale.
There's also been a growth in real-time data - if a consumer is unhappy with customer service, mobile banking options or any other element of financial services, he or she can share feedback, and the bank can incorporate that information immediately. Banks are better equipped to make these adjustments now than ever before, explained Howard Rubin, president and chief executive at technology consultancy Rubin Worldwide.
"There has been a data explosion," Rubin told CNBC. "Data storage at the big banks is growing at a rate of 45 percent per year. For consumers, it's about keeping more historical pattern data available in real time."