Finastra: Why AI Is Accelerating Bank Modernisation

For banks, modernisation has long been a priority — but often a slow-moving one.

In this conversation, Radha Suvarna, Chief Product Officer for Payments at Finastra, explains why that is beginning to change. The catalyst is not just new infrastructure or changing customer expectations, but the growing impact of artificial intelligence.

According to Finastra’s latest findings, 96% of institutions are already using or planning to use AI, reinforcing just how central it has become to banking strategy. But what stands out is not simply adoption — it is how AI is interacting with existing transformation agendas.

Modernisation and AI are no longer separate initiatives.

Traditionally, banks have focused on modernising their technology stack through cloud-native, microservices-based, and API-enabled platforms. These investments are designed to make systems more flexible and future-ready. At the same time, AI has been explored as a way to enhance data analysis, improve decision-making, and personalise customer experiences.

What is different now is the way these two trends are converging.

AI is accelerating modernisation by enabling faster experimentation. With the help of AI-driven coding tools and testing agents, banks can develop and iterate on new solutions more quickly than before. This reduces the time and cost associated with innovation, allowing institutions to test ideas, learn from failures, and refine approaches at speed.

At the same time, modern platforms are what make AI experimentation possible in the first place.

Without flexible, scalable infrastructure, deploying and scaling AI use cases becomes significantly more difficult. Cloud-native architectures and API-driven systems provide the foundation needed to integrate AI into core operations and customer-facing services.

The result is a reinforcing cycle.

AI drives faster modernisation. Modernisation enables more effective use of AI. Together, they create a multiplying effect that enhances both internal efficiency and customer experience.

This shift is also changing how banks approach innovation.

Experimentation is becoming a central theme. Institutions are recognising that not every AI use case will succeed, but the ability to test, fail, and iterate quickly is itself a competitive advantage. The organisations that can do this effectively — supported by modern infrastructure — are better positioned to capture the value of emerging technologies.

In that sense, the story is not just about AI adoption. It is about how banks are reshaping their entire approach to technology transformation.

The convergence of AI and modernisation is no longer theoretical. It is already underway — and it is redefining how banks build for the future.

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