In 2022, we tried to map out the future of banking. Four years later, it’s clear that those predictions were largely correct. But they also underestimated something fundamental. Not the direction of change, but the speed of it.
We spoke about process optimisation, ESG, and digitalisation as the forces that would shape the industry. At the time, these were forward-looking themes and areas where banks needed to invest to remain competitive. Four years later, it’s clear that those predictions were largely correct. But they also underestimated something fundamental.
While banks were improving their processes and systems, the environment itself evolved faster than expected. AI moved from experimentation to application. According to the World Economic Forum, AI is now becoming a core capability across financial services, particularly in areas such as risk, fraud detection, and customer interaction. Regulation became more continuous and complex, with expanding frameworks such as ESG reporting and operational resilience (e.g. DORA in the EU). Customer expectations are increasingly shaped by digital platforms rather than traditional financial institutions, as highlighted in the World Retail Banking Report 2024.
And in that reality, something shifted.
“The challenge is no longer how to improve the bank you have, but how to adapt when the context keeps changing.”
Optimisation worked, until it didn’t
Over the past years, banks have made significant progress. KYC, onboarding, and compliance workflows have been key focus areas for digitisation. Some banks allocate up to 60% of their compliance budgets to KYC-related activities, according to PwC. Digital onboarding solutions have reduced processing times and operational costs by up to 70% in some cases, according to Signicat. According to the World Retail Banking Report 2024, over 70% of banking executives increased their digital transformation investments, despite ongoing cost pressures.
But these improvements also revealed something less visible before. As processes became more structured and systems more integrated, it became harder to change them. We’ve seen this in practice in our work with Rabobank International Direct Banking. Optimisation made banks stronger, but not necessarily more flexible.
“What used to be flexible because it was manual, became rigid because it was digital.”
A new layer: decision-making is changing
Where previous investments focused on automating workflows, AI is now starting to influence decisions. KYC analysts supported by AI-generated insights. Customer interactions increasingly augmented by generative AI. Risk assessments enriched with predictive models.
According to the World Economic Forum (2025), AI adoption in financial services is accelerating rapidly. When AI begins shaping decisions, questions of ownership, accountability, and governance become increasingly important. In several of our projects, including AI-driven working capital solutions and reporting assistants, we’ve applied data and models to actively support decision-making, rather than just execute predefined workflows.
“From optimising work to rethinking how decisions are made.”
ESG: from ambition to execution
ESG followed a similar pattern. What started as a strategic ambition became an operational requirement. Regulatory frameworks such as the EU Taxonomy and expanded disclosure requirements further accelerated this shift, as documented by Deloitte. But translating ESG into consistent, daily decision-making proved more difficult. ESG data is less standardised, often dependent on third-party sources, and harder to validate and compare.
While banks have invested heavily in ESG reporting and analytics, many still struggle to turn this into actionable insights. In our work with Rabobank on sustainability-related initiatives, the challenge was not only collecting ESG data, but structuring it in a way that could support both rep
“ESG is no longer about defining goals. It is about making them actionable.”
Digitalisation: progress, with a trade-off
Digitalisation accelerated everything. New applications were introduced, workflows became more data-driven, collaboration between business and IT improved. At the same time, as the number of systems and solutions grew, so did the complexity of managing them.
Questions around Total Cost of Ownership became more prominent: which applications still add value, where do functionalities overlap, how do we keep systems maintainable? According to Capgemini (2024), cost efficiency and operational resilience are now among the top priorities for banking executives, alongside innovation. The focus gradually shifted from building more to building more consciously.
“Not from digitalisation to less digitalisation, but from building more to building more consciously.”
What this period really taught us
Looking back, the individual themes still hold. Process optimisation matters, ESG remains relevant and digitalisation is essential. But the way they interact has changed: they are no longer separate initiatives. They are part of a system that needs to move together across business, technology, and data.
And that leads to a different kind of question than we asked in 2022. Not “what should we invest in?” But “how do we make sure we can adapt, regardless of what comes next?”
Rethinking what “future-proof” really means
For many years, the ambition in banking was to become future-proof. But in a world where change is continuous, future-proof no longer means building something that doesn’t need to change.
It means building something that can change, without starting over.
This has implications across the organisation. For IT, it means designing architectures that can evolve over time. For business teams, it means aligning strategy with execution speed. For data, it means creating a foundation that enables consistent and reliable decision-making.
“The future of banking is not defined by the right strategy. But by the ability to evolve when that strategy needs to change.”
A final reflection
The past four years have shown that predicting the future is only part of the challenge. What matters more is how organisations respond when those predictions meet reality. The biggest difference between organisations is not what they predicted correctly. It is how quickly they were able to adjust.
Where this becomes practical
For organisations making this shift, the question is not whether to adapt, but where to start. Often, the answer lies in understanding where change is currently slow, where complexity is increasing, and where decisions rely on fragmented information.
At Finaps, this is where most conversations start. Not with solutions, but with understanding how organisations can move forward, step by step, in a way that fits their reality.
In our experience, these conversations often start with a simple question: where does change currently take the most effort?