Back at the start of WWII, Grace Hopper was too old at 34 and too small at 105 pounds to be accepted into the Navy. She eventually got in and her expertise in the emerging field of computer science made her a seminal figure in the government’s development of a new computer language called COBOL, which was introduced in 1959. That language became the standard for computing in business generally and banking in particular — and it never really left.
Look inside a bank legacy operating system today and what you’re likely to find is COBOL or something similar. About 43% of bank core systems still run on COBOL. What’s more, 95% of ATM transactions and 80% of in-person transactions still rely on COBOL.
These systems are often 30 to 40 years old, increasingly hard to maintain, and supported by a workforce whose specialized knowledge is quietly retiring. Meanwhile, digital-native banks operate on modern, cloud-based platforms built for speed and flexibility. In one survey, 55% of banks identified their core systems as their biggest roadblock to transformation.
That pressure is real. But so is the cost of doing something about it.
Modernization doesn't have to mean replacement
Legacy banking systems present a familiar challenge. Many are decades old, increasingly difficult to enhance, and weren't designed for today's digital expectations. Yet replacing a core system remains one of the largest technology investments a financial institution can make, putting a full replacement out of reach for many CFIs.
More institutions are finding that modernization doesn't have to begin with a core conversion. By combining AI, APIs, and stronger data management, CFIs can extend the value of existing technology and introduce new capabilities over time — without waiting for a full system overhaul.
AI is making modernization more practical
It's worth being specific about how AI fits into this picture, because the role it plays for most CFIs isn't what you might expect. Financial institutions typically don't write or maintain their own core code; that work belongs to their core providers and technology vendors. When those vendors use AI to modernize legacy systems, the benefits flow through to CFIs in the form of improved functionality, faster implementation timelines, and new features delivered through software updates rather than system replacements.
That distinction matters. AI is helping core providers analyze decades of complex legacy code, identify where new integrations can be added safely, and accelerate the delivery of new capabilities to the institutions they serve. What once required months of manual analysis can now be accomplished far more quickly and with greater accuracy, which means the enhancements CFIs have been waiting for can reach them sooner.
But institutions don't have to wait for their next core update to benefit from AI. Many are already using AI to simplify modernization projects and improve day-to-day operations. Examples include:
- Implementation preparation — AI can document business processes and summarize technical requirements before new systems or integrations are introduced, reducing the groundwork burden on staff.
- Data quality — Before migrations or API integrations, AI tools can identify duplicate, incomplete, or inconsistent customer and operational data, giving institutions a cleaner foundation to build on.
- Back-office automation — Report generation, document classification, exception handling, and other repetitive tasks can be automated, freeing staff for higher-value work.
- Fraud detection — AI can identify unusual transaction patterns and surface potential risks more quickly than traditional monitoring allows.
- Growth opportunities — Customer behavior analysis can uncover treasury management, lending, or cross-sell opportunities that might otherwise go unnoticed.
- Employee support — AI assistants can help staff locate policies, answer questions, summarize procedures, and accelerate onboarding and training.
These practical applications won't replace legacy systems, but they can make them easier to work with. For institutions with limited IT resources, AI can reduce manual effort, speed implementation projects, and help staff get more value from existing technology while laying the groundwork for future modernization.
APIs bridge old and new
If AI is accelerating the work behind the scenes, application programming interfaces (APIs) are the mechanism that makes modernization visible to customers and staff. An API is essentially a structured connection that allows two different software systems to share information and work together. For CFIs, that means the ability to add new capabilities without replacing the system underneath them.
Think of it as adding rooms to a house rather than tearing it down and rebuilding from scratch. The existing structure stays in place, and new functionality gets connected to it through a defined interface. Each addition is self-contained, which limits risk and keeps the scope of any single project manageable.
In practice, APIs are already enabling CFIs to move quickly in areas that matter most to their customers and members:
- Fraud prevention — Third-party fraud detection and authentication tools can analyze suspicious activity in real time, drawing on transaction data without requiring changes to underlying systems.
- Digital banking enhancements — Online and mobile banking experiences can be refreshed independently of the core, giving customers a modern interface without a core replacement.
- Treasury management — Commercial banking capabilities can expand through integrations covering ACH origination, positive pay, account reporting, and payment initiation.
- Fintech partnerships — Lending platforms, financial wellness tools, and small business solutions can connect to existing systems through API integrations, giving CFIs a practical path to expanding their product set.
- Digital account opening — API-connected onboarding solutions allow institutions to streamline the new account process and reduce friction for customers without replacing existing banking systems.
The cumulative effect is significant. An institution that adds API-connected capabilities can build a meaningfully modernized technology environment over time — without a single disruptive project that puts a strain on operations.
Start with the data
Before any of those integrations can deliver their full value, there's foundational work to be done. AI tools, analytics, fraud detection systems, and API-connected applications all depend on one thing: clean, accessible, reliable data. For some CFIs, that piece can quietly holding everything else back.
Data in legacy environments is often fragmented — stored in siloed systems, inconsistently formatted, and difficult to move between platforms. That fragmentation limits what technology can do with it. An AI tool trained on incomplete or inconsistent data produces unreliable outputs. A fraud detection system that can't access real-time transaction data can't catch real-time fraud.
United Community Bank, a 3,000-employee institution with more than 200 branches across six Southeast states, didn't begin modernizing with a core replacement. It started with data. The bank rebuilt its fragmented legacy data pipelines on a modern data stack, cutting the time to model complex data from four weeks to one and achieving four times faster data processing overall. With clean, unified data flowing through the system, every subsequent technology investment became more valuable.
That sequencing is instructive. Data modernization isn't glamorous, but it's often the work that makes everything else possible. CFIs that invest in understanding what data they have, where it lives, and how to move it reliably will find themselves in a much stronger position to take advantage of API integrations, AI-assisted tools, and whatever capabilities their core providers roll out next.
Incremental decisions, not all-or-nothing
Legacy systems in banking extend well beyond the core, and modernization doesn't require addressing all of them at once. The more practical question for most CFIs is where to start and how to sequence the work in a way that fits their strategy, budget, and capacity.
AI, APIs, and a strong data foundation are making that path more accessible than ever. AI is helping institutions work more efficiently while enabling technology providers to deliver new capabilities faster. APIs are making it easier to connect specialized solutions without replacing existing systems. And clean, well-organized data is giving those technologies the reliable foundation they need to deliver meaningful results.
Modernization is becoming an ongoing process rather than a once-in-a-generation technology project. By building on existing investments, CFIs can continue expanding their capabilities at a pace that fits their strategy, budget, and customers' expectations.
