Author: Hans Tesselaar, Executive Director, BIAN
Traditional financial institutions are under increasing pressure to modernise, from improving efficiency to enhancing security. For many, transformation is already underway: a recent Bank of England survey found that 75% of organisations are currently using AI, with another 10% planning to adopt it within the next three years.
However, 55% of financial institutions acknowledge that legacy systems are hindering their transformation efforts. To succeed, they must align IT architecture—covering everything from design to hardware, software, and data—with business goals while remaining adaptable to ongoing change.
An evolving ecosystem
AI is no longer just a buzzword; it’s central to shaping the future of technology. As AI continues to dominate the headlines and impact consumer devices, its full potential in financial services will unfold over the next few decades.
The World Economic Forum highlights that “as AI becomes central to technology strategies, executives must continually evaluate technology ecosystems to capture emerging opportunities, ensuring that AI investments are thoughtfully integrated into broader initiatives.”
For IT Leaders and architects, this may seem daunting. However, they must consider how these emerging technologies will affect their businesses long-term. By establishing an adaptable strategy now, banks can better position themselves to harness the benefits of new technologies, both today and in the future.
What does this look like in practice?
One example of this future-forward thinking is our Coreless Banking concept. This model proposed that banks move away from rigid, outdated systems and adopt smaller, specialised components that can be easily swapped or integrated. By utilising open standards and API-driven ecosystems, banks could achieve greater flexibility and adaptability.
Since the initial concept, we’ve developed three additional models, with our latest concept incorporating AI and machine learning to tackle customer churn. In this proof of concept, AI detected competitive pressure, designed a better competitive offering, identified potential customers, and offered personalised promotions. This feedback loop allowed for continuous improvement, demonstrating how AI can be integrated seamlessly into a coreless model for improved customer experience and business outcomes.
Tackling Legacy Infrastructure Obstacles
Banks that fail to embrace the coreless approach risk being left behind, as outdated legacy infrastructure creates significant barriers to innovation. Research shows that half of IT leaders face constraints with their legacy core systems, slowing their progress toward achieving business objectives. In addition, 44% of banks cite the time it takes to bring new services to market as one of the biggest obstacles.
The costs and delays associated with outdated core systems make banks less competitive and less capable of meeting the evolving needs of their customers. For those still relying on legacy systems, the solution lies in adopting a more agile approach—one that can support both current and future technological advancements.
The time to act is now
As technology continues to evolve and the landscape becomes increasingly fragmented, the need for flexible, agile solutions becomes more urgent. The coreless banking model, which emphasises open standards and API-driven ecosystems, offers a way forward. It addresses current challenges and positions banks to capitalise on the opportunities presented by AI and beyond.
Those who resist change will find themselves outpaced by more innovative competitors. The time to act is now, and the future of banking depends on an institution’s ability to integrate and evolve with new technologies in an ever-changing world.
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