Banking on Big Data and Analytics to Improve Customer Loyalty

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Shifting market forces are shaking up the retail banking industry from new payment platforms – including those from big players like Amazon – to mobile banking, peer-to-peer lending to regulatory constraints and a persistently tough interest rate climate.

Furthermore, banks are under-leveraging their existing customer bases and missing out on cross-selling opportunities.

That’s according to a survey of 991 banks that notes that consumers today use 6.05 banking services on average but they only use 3.37 of these services from their primary banks where they keep their checking accounts.

Many banks are trying to tailor customer experiences that are consistent for every customer across every channel. However, they should be leveraging big data and advanced analytics to provide a personalized experience that fits different customer segments, notes Dean Nicolacakis, a partner at PricewaterhouseCoopers’ banking and capital markets practice, in an article in Bank Systems & Technology.

Smart banks are using analytics to navigate this changing landscape to segment customers based on what they value in products and services. A wealth of existing customer data can be merged with online and social media, transactional and geo-analytical data to better anticipate customer behaviors and needs.

Traditional demographic-based customer segmentation is evolving to reflect:

  • Which customers are truly the most profitable
  • What mix of channels is most appropriate to reach them
  • What types of products they need and want
  • Who is likely to switch banks

For example, Nicolacakis notes that banks have traditionally assumed that all customers want free checking or monthly checking accounts. But PwC research has shown that about 25 percent of customers are interested in an a la carte model of paying for fees for additional services associated with their accounts.

At the same time, big data and analytics can improve business processes to enhance the customer experience in various ways, including:

  • Speeding up loan approvals
  • Optimizing branch and ATM locations and activity
  • Improving marketing campaign targeting, timing and effectiveness

“People [in banking] have a blanketed approach to customer experience. Of course, you need a foundation based on good maintenance, not making mistakes in customers’ accounts, etc. But once you provide that minimal level you need to provide some nuance to the experience,” Nicolacakis explains. “You need to ask what differences there are in what customers want?”

And while banks assume that all customers want free access to mobile banking services, PwC research has found that about 24 percent of customers are “very biased toward a convenient experience” and would be willing to pay for mobile banking services.

Finally, Nicolacakis notes that big data and analytics can be used to help banks cut costs by understanding channel usage.

Many customers have not adopted online or mobile channels and still use the branch or call the service center for daily banking needs, he points out.

“Many banks are already starting to record all of their customer interactions in the call center for compliance purposes, and by analyzing those call recordings they can identify the customers who are calling about their balances,” according to Nicolacakis. “The bank can then move those customers to online and mobile banking, and it becomes much cheaper to serve them.”

The bottom line is customer loyalty is no longer being driven by which banks offer free checking or which banks are nearby, but rather by which banks offer the best mobile banking experiences, the best interest rates and real-time updates via various channels.

That means banks need to turn to big data and analytics to understand what their customers want so they can offer them the convenience they expect.