Digital Banking Harnesses Big Data For Better In-Branch Experiences

Digital Banking Harnesses Big Data

We’re a long way from knowing what permanent changes the COVID-19 pandemic will have wrought in terms of physical attendance at events, live retail experiences, dining out – and even going to the bank. It’s a time of transformation in every industry on earth, and virtually no one saw it coming. Some verticals will thin, some operations will perish. It’s a total shock.

Nevertheless, life goes on – and along with the loss of some established and even beloved concepts, nascent industries will spring to life in ways as unprecedented as COVID-19 itself.

Digital banking is one of several emerging industries well-positioned to create that rarest of things – meaningful consumer value – out of a record-setting economic freefall. The latest PYMNTS Digital-First Banking Tracker®, done in collaboration with NCR Corporation, looks at the analytics success stories emerging from the ravaged business landscape, with use cases and specifics around harnessing the power of data analytics.

The Branch Visit After COVID-19 

Unbridled innovation was already underway in branch banking technology and related platforms offering an enhanced customer experience (CX). In the wake of COVID-19, we can expect that activity to rev up, as major players and FinTechs deploy advanced analytics to help quickly operationalize ambitious new branch banking plans.

“While customers use digital devices for the majority of their banking transactions, the branch remains a critical customer touchpoint for consumers and small businesses,” Douglas Brown,

senior vice president and general manager at NCR Corporation, told PYMNTS. “Branches present a unique and high-value opportunity to deliver personalized service to customers for complicated life decisions, such as mortgage refinancing, business lending, financial management and planning. Many banks and credit unions are advancing branch transformation initiatives to improve the customer experience and enhance the relationship.”

Noting that customer journeys are now being designed to flow seamlessly from digital inception “…to a live banker interaction in the branch for completion,” Brown added that “business customers can be served with digitally connected [in-branch] kiosks to arrange physical pick-up of cash and coins after standard lobby hours. Interactive teller machines can bring efficiency to branch locations while expanding convenience for consumers. Branches play an important role in serving customers as part of a well-orchestrated customer experience strategy across physical and digital channels.”

Big Data Building Blocks

For years, banks and financial institutions (FIs) have used transaction data to power back-of-house functions. That idea goes on steroids when digital banking uses Big Data to visualize and roadmap a new branch banking CX that includes interactive teller machines (ITMs), which now seem visionary in the age of COVID-19. And data will continue to feed background operations.

“Big Data significantly affects banks’ back-of-house operations as well as their customer-facing processes,” the report states. “It is key to risk management functions, which entail assessing the likelihood that any given transaction could be fraudulent or present a credit risk. Data analytics systems can analyze thousands of variables for each transaction, including applicants’ lending histories, past transactions associated with their credit cards or individual items in their credit histories.”

Such insights complement and empower an organization’s in-house financial talent, especially with things like “…educated predictions regarding interactions’ risk factors,” the report states.

As for digital banking, Big Data and the in-branch experience, it’s an inside job.

“Developing a data analytics system starts with assembling a team of representatives from every bank department, including corporate banking, home loans, investment banking, retail lending and more,” according to the report. “New teams must then identify core problems that data analytics can solve, such as developing targeted car financing offers. This helps teams focus on specific goals, thus preventing mission creep and determining which analytical software is needed.”