In 2018, if you sat down with any leading financial institution in the UK and asked for their thoughts on open banking, they would immediately respond with curiosity and excitement.
They could see the technology’s potential to be a game-changing force in financial services by empowering customers, enhancing competition, and driving innovation. The UK was at the forefront of this change with regulatory frameworks encouraging data sharing and unlocking new opportunities for financial institutions.
Over the last year, I’ve had the same conversation with leading financial institutions, and the response has been entirely different despite technological advancements. They talk about the barriers to success and the struggle to create a meaningful impact from mounds of consumer data. They struggle to show the resulting return on investment behind investing in open banking data and to identify customer or commercial value.
But the conversation around open banking is already shifting again. AI is transforming open banking, turning it from a slow-moving experiment into a powerful competitive edge. The barriers that once hindered consumer adoption are fading, and the potential is greater than ever.
The opportunity is clear. Financial institutions that manage to behave like disruptors, innovate quickly, and leverage open banking data will be winners in the AI economy. However, financial institutions that hesitate then risk being left behind. They need to embark on a radical rethink of their open banking strategies if they are to become the companies that usher in the next era of finance.
At the heart of this opportunity is customer data, which has become the most valuable asset in the fintech sector. Open banking made vast amounts of financial data available, but the challenge has always been turning that data into meaningful actions and business impact.
Despite this immense potential, many organisations still struggle to capitalise on it. The complexity of accessing, interpreting, and integrating open banking data remains a major hurdle. The data exists, but too often, it’s disconnected from real business needs.
The key to unlocking the potential of this data lies within AI. When financial institutions combine unique customer data with the power of LLMs, they can offer hyper-personalised financial products, driving deeper customer engagement. The more engaged customers are, the richer and more valuable the data becomes—creating a flywheel effect that fuels both business growth and customer satisfaction.
