In mature, global and highly regulated industries such as banking, continuous innovation is the only route to success. However, 58% of financial services leaders say innovation is delayed by foundational tech stack issues.1
Leading banks are facing an unpleasant side effect of the industry’s history of mergers and acquisitions. Both the acquiring and the acquired have often been left with complex legacy architectures that cannot adapt to the demands of modern customers and business requirements. Every year, those fragile environments become more brittle and fewer people have the skills to maintain them.
As banks consider adopting agentic AI technologies, many find the problem is even more acute than suspected: most enterprise infrastructure was never designed for machine-driven operations or tightly governed automation at scale. There are also important security considerations as increasingly powerful AI models become more widely available, with the potential to increase the frequency of attacks while lowering opportunity costs for attackers.
The business implications are too damaging to ignore. An inflexible legacy architecture leads to less agility and greater risk. This means line-of-business leaders become accustomed to hearing “no” when they attempt to innovate, discouraging creative thinking about new ways to bring value to the customer.
Banks that are not able to modernise their tech stacks to use new technologies, such as generative and agentic AI, not only miss out on improved customer experiences and innovations essential for growth. They also miss opportunities to strengthen their cybersecurity.