"Data is the core asset now." – Microsoft CEO Satya Nadella, in a March 2016 New York Times interview.
Over 70 percent of consumers use digital banking channels, according to a recent Deloitte global consumer survey, and nearly 60 percent of respondents said they use mobile banking apps. "The current generation of young people, and every subsequent generation from now, will embrace online and mobile banking, more-so than any other generation in history," said Joe Bashta, CEO of Axicor, a company specializing in artificial intelligence solutions for several business sectors, including banking. This shift in consumer behavior demands every industry must become more responsive, meeting their customers' needs where and when the customer chooses. Banks have already seen some of the impact from this change in the emergence of fintech. "It's simple," Bashta said. "Be disrupted or be disruptive. You only need to look at the onslaught of fintech innovations to see that disruption to traditional banking is coming, if not already here."
This wave of change has made data the most valuable asset banks have as well as their best customer service tool. While the banking industry—and the business world in general—is still working to define who owns consumer data and what uses are acceptable, it is widely accepted that banks can (and should) internally utilize the data their customers give them in an effort to provide better service. "The customer has to be completely at the center of everything you do," said Jeff Lee, chief marketing officer at Seacoast Bank in Stuart, Fla. "They expect you to come to them, so you need to anticipate their needs in order to serve them." Over the past several years, Seacoast has undertaken a digital transformation initiative in order to better leverage their customer data in response to changing consumer behavior. "The industry is changing very quickly," said Lee. "Declining foot traffic means we need to do something with data."
The good news is, even small institutions possess a massive amount of valuable information about their customers, making data an equalizer. However, accessing, analyzing, and acting on that knowledge is no simple task. "Banks want a magic pill, but the reality of it is that it's hard work," said Sean Payant, chief consulting officer at Haberfeld. In order to implement data analytics successfully, banks must first view data as a service tool rather than simply a function of IT.
Data as a Service Tool
Many banks don't think of their digital and mobile banking platforms as channels to build customer relationships through personal touch, but implementing a data analytics and usage strategy allows those platforms to provided bank customers with personalized, timely service. "Data analytics provides banks with the ability to 'connect' directly with their customers," Bashta explained. That engagement—and the customer loyalty it generates—is where using data analytics creates the most value. "When done properly, you can use data to have a much better context and deeper understanding of the customer," said Lee. "If you get advanced with it, you can understand that customer's value and potential."
In order to use data to analyze consumer behavior and predict customer needs, bank leaders must learn to use experience and data as equally valid sources of information. "It's human nature to rely on life and industry experience to interpret information and make decisions accordingly," Bashta explained. "However, whilst making decisions based on decades of industry experience is valuable and shouldn't be dismissed, it should also be balanced with evidence-based data. Let the data confirm, or correct, your experience."
With a data-provided deeper understanding of customers comes a benefit Payant calls "increased relational intensity." By using data to provide more personalized products and services, banks can ultimately give their customers a faster, more streamlined banking experience that delivers the right products at the right times. For example, Payant recommends banks utilize their data to create cross-selling opportunities. "Cross-selling is about cross-serving customers," he explained. The key with this strategy is effectively communicating to customers how those products and services will make their lives better. "When you focus on making people's lives better, you get a longer relationship," Payant said.
Using data to provide personalized customer service—as they have always done—community banks can compete effectively in their market against much larger institutions and increase wallet share. It is a matter of confidently telling your customers that your bank is just as capable of delivering quality products and services in modern ways as the competition up the street. "As smaller institutions, we have to put a stake in the ground and say we're good enough to get the entire relationship, not just the loan," Lee said. "It's a giant game of tug of war."
Four Steps to Get Started
1. Create a culture of data.
Bashta says in order for organizations to gain a competitive advantage using data, they must instill a culture of data, which requires support from the top. "When the most senior members of an organization view data as one of their most valuable assets, then that mindset will permeate throughout their organization and will create a culture whereby decisions around systems, processes, and technology will be made through that lens," he explained.
2. Find your focus.
"Choose the mission very carefully," Lee advised. "Pick one thing and get really good at it, instead of a 10-year plan where you try to do everything." Payant also cautions banks against trying to do too much at one time. "Don't try to look at every product and service," he said. "Prioritize and rank which ones are the most important to your current goals, whether that's fee income, core deposits, et cetera, and pick one thing to work on. If you pick ten you won't do any of them." It may be helpful for bank leadership to craft a formal strategy to guide their digital transformation efforts. "Creating an overarching data strategy will lay a solid foundation for short-, medium-, and long-term decision-making on every aspect of a bank's operation, not just technology," Bashta explained.
3. Acquire the skills you need.
Very few bankers enter the industry with a data analytics background, so most institutions will need to either outsource, hire, or retrain in order to gain the expertise needed to execute their data strategy. "If you really want to be good at this, find someone who's really good at data analytics and hire them," said Payant. "Then, train your people on how to recognize opportunities and convey them in a compelling way."
4. Integrate and correlate your data.
Once the strategy is in place, the first step is to assess what data the bank already has. "Most small and midsize banks have all their data in one core provider and it's accessible to the folks in the bank," said Lee. "Start by trying to get a good understanding of what data you already have. Call your core provider and go through it line by line to make sure you understand it." At Seacoast, Lee says their approach was to first identify what data they had and define it, then ideate how to create better value for their customers with it. Payant provided an example of how this could work. A bank could segment their checking portfolio by average balances, then identify the top ten active customers who are single-product households with high balances. "Reach out with a phone call, not to sell, but to thank them for their business and let them know you'd like to earn more of it," he advised. "You'll find many times no one from a financial institution has ever reached out to them."
Looking forward, data analytics will only become more critical to business operations as the technology improves and becomes more accessible. "This technology is becoming more pervasive, more readily available, and more affordable for banks and even small businesses," said Bashta. "Organizations who view data as a core asset and who embrace the emergence of advanced analytics technologies will be well-positioned to easily and effectively mine their own data for intelligence, predictions, and actionable insights."
Haberfeld is a WBA Associate Member.