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Behind the Scenes of a Bank Merger: A Systems Integration Playbook

Get a practical guide to planning core banking system integration during mergers, with insights, risks, and tech strategies.

Gary Class
Gary Class
2025年8月25日 3 分で読める

In the U.S., banks have gone through several waves of mergers and consolidations—sometimes driven by regulatory changes like the removal of interstate branching restrictions, and other times by economic pressures, such as those seen during the Great Recession. These mergers can be horizontal (expanding into new regions) or vertical (branching into new services like wealth management).

While most post-merger system integrations are carefully planned and executed, when things go wrong, the consequences can be serious. Take the U.K. in 2018, for example: A failed core banking integration left customers of the acquired bank locked out of their digital accounts for a week. Some even saw other people’s account balances. The fallout included hefty fines, compensation payouts, and the resignation of the acquiring bank’s CEO.

Selecting the right core banking applications   

Once the excitement of the deal fades and the new leadership is in place, one of the first big decisions is figuring out which core banking systems—like those handling deposits and credit cards—can handle the combined customer base. 

“The IT team should be involved very early in M&A deals,” says Jan Verplancke, former global chief information officer at Standard Chartered Bank. “When we engaged in acquisitions at Standard Chartered, I was involved from day one. You have to be part of the team that goes and looks at the documents; part of that is to look at the data architecture and the systems architecture.” 

The acquiring bank has two main options: run both systems side by side or migrate everyone to a single platform. While keeping both systems might seem like the easier route, it only delays the inevitable and limits the bank’s ability to roll out new features. It also means maintaining duplicate support teams, like contact centers. 

A full, one-time conversion sounds efficient but carries high risk if anything goes wrong. A smarter approach is to test the waters—convert a small group of accounts first, maybe by region (like one U.S. state at a time), and leave enough time between waves to fix any issues that pop up.

How Teradata can support integration decisions 

Teradata’s Master Data Management (MDM) can ensure that customer data—like contact info—is accurate and consistent across both banks. This is especially important for merger-related communications. Merging two sets of customer records can be tricky, especially when there are outdated or duplicate entries. 

One of the first things to figure out is how many customers the two banks have in common. This is particularly tough when it comes to business and institutional clients. Teradata’s entity resolution tools, powered by language models, go beyond basic string-matching to identify overlapping customers more effectively. Celebrus adds another layer by analyzing digital behavior across devices to help resolve “digital identities”—a key asset for targeted digital marketing. 

Deciding which products stay 

Banking products are essentially bundles of services designed to meet specific financial needs. A big part of integration planning is deciding which products the new bank will continue to offer. This means comparing the two banks’ offerings to spot overlaps and unique features. 

Sometimes, management is hesitant to retire unique products for fear of upsetting customers. But keeping too many legacy products can lead to “grandfathered” offerings that become a major source of technical debt. 

One of the toughest parts of integration is managing the internal politics between leaders from the two merging banks. Teradata’s Financial Services Data Model can help here by offering a global reference architecture that can serve as “neutral territory” to evaluate the competing approaches to database architecture of the target and acquirer banks. The model integrates operational information about customers, products, and channels into one data warehouse, setting the stage for a single view of your customers.

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Gary Class について

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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