Mainframes Are Not Dead — They Are Becoming the Engine of Modern Banking

Posted by: Zaheer Abbas March 11, 2026 No Comments

Insights from the European Digital Finance Conference

Amsterdam — At the recent European Digital Finance Conference, a panel of senior banking and technology leaders challenged one of the most persistent myths in financial services: that innovation requires replacing legacy systems.

Instead, the discussion revealed a more nuanced reality. Banks across Europe are discovering that modernization does not necessarily mean ripping out mainframes. With the right architecture, tooling, and strategy, institutions can combine the reliability of legacy systems with the agility required for modern digital banking.

The panel brought together Nathan Snyder (DXC GrowthX), Peter Heijblom (ABN AMRO), Alexander Wiener (Element), Michał Niszwiecki (mBank), and Henk van Dasler (Rabobank) to discuss modernization strategies, AI’s growing role, and lessons learned from large-scale transformation programs.

The Myth of “Rip and Replace”

For decades, the banking industry has debated whether innovation requires replacing core systems. The panelists largely rejected that assumption.

According to Nathan Snyder, the real question is not whether modernization is possible, but what a bank ultimately wants to achieve.

“Everything is possible — modernize in place, modernize off platform, or enable new services around the core. The real question is: what business value are you trying to achieve?”

Mainframes continue to power many of the world’s largest financial institutions precisely because they are extraordinarily reliable. Snyder noted that many banks still run their entire operation on these platforms without outages, which explains why replacing them outright is rarely the most pragmatic option.

Instead, modernization often focuses on layering modern services around the core system — enabling real-time interactions and digital channels while preserving the stability of the underlying infrastructure.

The Real Problem: Knowledge, Not Technology

A striking theme across the discussion was that the biggest modernization challenge is not the technology itself.

Henk van Dasler from Rabobank argued that the real obstacle lies elsewhere.

“The problem is not COBOL and it’s not the mainframe. The real problem is application knowledge — understanding how decades of code actually work.”

Many banking systems have evolved over decades, built by developers who have long since retired. As a result, institutions face a growing knowledge gap. Modernization initiatives increasingly focus on documenting and understanding existing systems before attempting any transformation.

At ABN AMRO, Peter Heijblom echoed this perspective. The bank is modernizing its mainframe environment while keeping the platform itself intact.

“Modernizing is not about the platform or the language — it’s about the functional knowledge inside the applications.”

This shift in thinking is driving investments in developer tooling, documentation systems, and automated analysis of legacy codebases.

Building Modern Services on Mainframes

Another misconception addressed during the panel is that mainframes cannot support modern digital services.

According to Peter Heijblom, today’s mainframe environments are very different from the machines of decades past.

ABN AMRO now runs Java applications, containerized workloads, and REST APIs directly on its mainframe infrastructure while integrating with cloud platforms.

“These are not machines from the 1960s anymore. It’s modern hardware with enormous compute power. We use DevOps, automation, and APIs to open mainframe data to the cloud.”

This hybrid architecture allows banks to expose real-time services — mobile banking, payments, and new digital products — without destabilizing the systems that run the core ledger.

AI Is Transforming Legacy System Understanding

One of the most significant accelerators in modernization efforts is artificial intelligence.

Across the panel, leaders emphasized that AI is dramatically improving the ability to understand complex legacy systems.

Alexander Wiener, CEO of Munich-based modernization firm Element, described how AI is making decades-old systems accessible to a new generation of engineers.

“For the first time we can actually understand systems that evolved over decades. Generative AI makes it possible to explain and visualize them across the entire organization.”

AI-driven tooling can now analyze massive codebases, generate documentation, and identify dependencies that previously required months of manual work.

However, panelists also cautioned against assuming AI is a universal solution. Snyder noted that traditional deterministic tools can sometimes outperform AI for specific migration tasks.

Practical Modernization: Small Steps, Big Impact

While strategies differ between banks, many modernization programs share a common principle: incremental change rather than large-scale replacement.

At mBank, Michał Niszwiecki described how his team reduced operational costs significantly by adding architectural layers rather than replacing the entire system.

“We introduced a caching layer and reduced mainframe operating costs by about 40 percent.”

By replicating data externally and adding modular services, banks can improve performance, reduce costs, and introduce new capabilities without risking outages.

This modular approach also allows organizations to test new architectures gradually while
maintaining operational stability.

The Critical Role of Leadership

Beyond technology, modernization initiatives depend heavily on governance and long-term commitment.

Large banking transformation programs often run for years, and maintaining momentum requires consistent executive support.

Rabobank’s Henk van Dasler emphasized that modernization must be backed by senior leadership from the start.

“The board of directors must stand behind it. These programs are not measured in weeks or sprints — they are measured in years.”

Without sustained sponsorship, modernization efforts risk stalling or becoming prohibitively expensive.

Lessons from Large-Scale Banking Transformation

Across all speakers, several key lessons emerged from real-world modernization programs:

  1. Start with a clear business objective.
    Modernization must be driven by measurable outcomes such as faster product launches, lower costs, or improved customer experience.
  2. Understand the existing system first.
    AI and automated tooling can dramatically accelerate system analysis and documentation.
  3. Favor iterative transformation.
    Replacing entire systems rarely works; layered architectures and modular services reduce risk.
  4. Maintain executive sponsorship.
    Modernization programs often span multiple leadership cycles and require consistent governance.
  5. Protect the institutional knowledge embedded in core systems.
    As Michał Niszwiecki explained:

“Inside your core banking system is your history — your DNA. That’s why it’s worth modernizing what you already have.”

A New Era of Banking Modernization

The conversation at the European Digital Finance Conference highlighted a major shift in how banks approach transformation.

Rather than abandoning legacy systems, institutions are increasingly combining the resilience of mainframes with the flexibility of cloud, APIs, and AI-driven tooling.

Modernization is no longer about replacing the past — it is about unlocking the value embedded
within it.