The Evolution of Branch Banking in the U.S.

How banks can use advanced data analytics to keep branches relevant in the digital era.

Gary Class
Gary Class
18 juin 2024 3 min de lecture

The role played by branches in the product distribution strategy of banks is evolving rapidly. In the past, tellers, and later ATMs, facilitated monetary transactions like deposits and cash withdrawals. Although the demand for paper checks and cash is slowly declining in the U.S., these channels are still important for certain cohorts, especially affluent customers, small businesses, and consumers in communities where the cash economy is still prevalent, such as the area along the U.S. southern border.  

In addition to facilitating monetary transactions, branches have traditionally played an important role in acquiring new customers and providing relationship services for existing customers. Today, as customers increasingly migrate to digital banking channels, the strategic role of branches is evolving, with a greater focus on maintaining customer relationships. Branches are often the “channel of last resort” where customers escalate problems that are too complex to resolve in self-service channels.  

Before the digital era, banks focused on providing “spatial convenience.” At first, this meant locating branches on the most visible street corners in neighborhood shopping centers with an abundance of parking. In the early 1990s, banks took the strategy a step further, deploying ATMs en masse at locations other than branches and even opening branches inside supermarkets. This allowed a bank to be a fixture along the routine travel path of customers, located everywhere they lived, worked, or played.  

With the mass availability of digital banking, first on desktop computers and later mobile phones, banks shifted their focus to “temporal convenience,” or providing customers the ability to engage in banking activities at any time of day or night. As banks adopted e-commerce and digital payment platforms, consumer preferences shifted from spatial to temporal convenience, and banks aggressively rationalized their branch networks to reduce operating expenses.   

The Federal Deposit Insurance Corporation (FDIC) reports that the number of bank branches for member institutions declined from 88,065 in June 2018 to 77,786 in June 2023, or 11.7%. After adjusting for mergers, the number of branches at the 14 largest banks (with $250 billion or more in assets) decreased 20.6%—roughly twice the rate of banks overall. However, deposit growth for the same five-year period was only slightly lower for the largest banks than for banks overall. In summary, banks were able to materially grow deposits with fewer branch locations.  

While closing a branch decreases operating expenses, it introduces potential risks to revenue. In addition to spurring attrition among some customers, closure reduces opportunities to acquire new customers in the geographic area the branch once served. To assess these risks, a bank must be able to identify the “empirical trade area” of a focal branch, which is often defined as the polygon of census tracts that collect 65% of the branch’s regular patrons. This requires sophisticated analytic capabilities. Fortunately, ClearScape Analytics™, Teradata’s powerful engine for deploying AI/ML pipelines, provides advanced spatial data algorithms that can efficiently support this type of analysis. 

Customer attrition can be predicted based on the proximity and accessibility of alternative branch and ATMs locations for the branch’s primary patrons. Banks can repurpose transaction data to directly measure how often primary patrons of the focal branch visited alternative branches. A mitigating risk factor is the depth and breadth of digital banking channel usage for the closing branch’s regular patrons, especially their adoption of mobile remote deposit capture and digital wallets.  

To learn more about how banks can leverage the full scope of channel data to drive analytics, see the complementary white paper, “Customer Journey Analytics in Banking.” 


À propos de Gary Class

Gary is an accomplished industry strategist with extensive experience in financial services, where he has made significant contributions to advanced analytics and AI. Gary spent over three decades at Wells Fargo Bank as the Director of Advanced Analytics at the forefront of innovation during the transformational era of “anytime, anywhere” banking. His visionary leadership has shaped the landscape of financial services through innovation, data-driven insights, and strategic thinking.

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