Many financial institutions struggle not with technology, but with execution. While MVPs are common, few scale into measurable results. The gap between strategy and implementation remains the core issue.
Key takeaways
- The core challenge is execution: institutions can build MVPs, but lack the structure and ownership to scale them into production and measurable value
- The gap between strategy and implementation is systemic: separate teams, timelines, and incentives create misalignment and slow delivery
- AI adoption is increasing, but impact lags: most organizations experiment successfully, yet fail to translate pilots into operational workflows
- Measurable results require an end-to-end approach: integrating strategy, development, and deployment with shared accountability across the lifecycle
- Proven outcomes are achievable: faster processes, lower costs, and higher decision quality emerge when execution is treated as a continuous, integrated discipline
After more than 20 years in IT, I’m heading to Interlaken in early May for the Richmond Financial Industry Forum, one of the most high-profile gatherings of senior decision-makers from Swiss banks, insurance companies, and fintech firms.
For me personally, this is an opportunity to delve even deeper into a question that’s currently on my mind: What does the financial industry really need from IT partners like Mimacom, and where does measurable impact arise?
There are plenty of MVPs – what banks really lack is the next step
Anyone who regularly works with banks and insurance companies – whether replacing outdated e-banking systems, digitizing mortgage processes, or building customer portals for financial services – quickly realizes that the technology decision isn’t the hardest part.
Nor is regulation. Banks are the foremost experts on regulations themselves; they are well-equipped to handle them and generally have no trouble implementing new requirements, whether in Switzerland, the EU, or the U.S. What is truly missing is something else: the ability to bridge the gap between strategic vision and concrete implementation.
This gap is universal. It does not arise from a lack of goodwill or resources, but because strategy and implementation are too often in different hands, and the transition between the two rarely goes as smoothly as it should. Those who fail to bridge this gap end up in pilot mode and remain there without any measurable impact. This is exactly where my work begins.
AI adoption is rising, but only 5% of MVPs actually scale
What we now see very clearly in the example of AI, we also experience daily in relation to pure digitalization. And these figures are sobering. An MIT study from July 2025 shows that only 5% of integrated AI MVPs in companies have actually achieved significant added value and been scaled into productive workflows. At the same time, a study by S&P Global Market Intelligence/451 Research from the same year shows that 54% of financial service providers already have AI in productive use, compared to 40% just one year earlier.
Matthias Köhler, VP Sales & Marketing, Mimacom
Adoption is clearly on the rise. However, the ability to achieve real impact is lagging, not only with AI, but also with other digital initiatives. The will is there, and pressure from end customers is mounting, yet the results of AI or transformation projects are often disappointing.
This is not a criticism of individual institutions. It reflects a structural challenge: such initiatives are complex, regulatory-sensitive, and the transition from a functioning MVP to a scalable solution requires a different mindset than the development of the MVP itself. In contrast to the major institutions, fintechs are catching up, starting precisely where established institutions still hesitate. This means these fintechs are succeeding in translating visions into scalable solutions, while traditional financial institutions remain stuck in deliberations.
It's what I hear time and again in conversations with financial leaders: The problem is rarely a lack of ambition. It is a lack of confidence in their own ability to bring projects into productive operation quickly and securely.
Yet the data also shows that those who succeed are rewarded. According to McKinsey’s Global Banking Annual Review 2025, banks that consistently implement AI can achieve cost reductions of up to 20%. In its report “For Banks, the AI Reckoning Has Arrived” (May 2025), BCG notes that institutions relying on specialized teams and external partners achieve efficiency gains of up to 60% and cost reductions of up to 40% in areas such as onboarding, compliance, and settlement. And in specific use cases such as fraud detection – where, according to AllAboutAI (2025), AI is already in use at 87% of global financial institutions – AI systems achieve a detection accuracy of 92 to 98%, compared to an average of 37% for rule-based legacy systems. These are no longer promises; these are results.
At Mimacom, we’ve realized that the only way to bridge the gap between pilot and scaling is to treat AI not as an add-on, but as an integral part of every development step, from the initial requirements analysis to deployment. This has enabled us to deliver working prototypes in 10 days and MVPs in 12 weeks, while maintaining higher quality standards. This is true even – and especially – in regulated environments such as banking and insurance.
What does this mean specifically for financial institutions? Just like digitalization, artificial intelligence can not only accelerate processes such as KYC, fraud detection, or onboarding, it can also improve the quality of the decisions made in the process. But this can only be achieved with an end-to-end approach.
Why strategy and implementation should not be separated
Many digital transformation programs do not fail because of the choice of technology. They fail because strategy and implementation are managed by different stakeholders – one team for the concept, another for implementation. In the end, the two do not align, or the strategic framework is already outdated by the time implementation begins.
This effect is particularly noticeable in the financial sector. Regulatory pressure –DORA, the AI Act, the Instant Payments Regulation – is changing the framework faster than traditional project phases allow. Those who then keep strategy and implementation in two separate hands lose valuable time coordinating.
What measurable results actually mean
I know that such arguments can sound abstract. That’s why I’d rather give three concrete examples of what happens when strategy and implementation are truly considered together, and what specific steps were taken to make it work.
Migros Bank wanted to become Switzerland’s most digital bank, not just as a slogan, but as a measurable goal. The challenge was that e-banking and mobile banking systems had grown over the years and were becoming increasingly inconsistent. Customers complained that features available in the mobile app were missing from desktop banking, leading to frustration and rising support costs.
Instead of an isolated system migration, we involved customers from the very beginning, with a proof of concept that integrated real user feedback into the development process. The result is a consistent, cross-platform digital banking solution that is now visible across all of the bank’s touchpoints.
Volksbank Filder managed its financing processes for property developers and land developers in up to 130 separate Excel spreadsheets, without automation, without version control, and with a high risk of errors. We implemented a customized process automation platform based on Flowable that consolidates document management, communication, and compliance requirements into a single interface. Since, the speed of financing processes has increased sixfold, with the same teams, but radically simplified workflows.
In 2023, Siemens Financial Services processed over 7,000 invoices exclusively manually, via PDF and email, with no visibility into credit limits or open items. What was done: Together, we developed a central customer portal that digitizes the entire EPT process and is directly connected to Siemens’ backend systems with a real-time overview, intuitive user guidance, and a deliberate avoidance of over-engineering. The result: A financing request now takes minutes, not days.
These three examples come from completely different contexts – retail banking, a cooperative bank, and a global industrial financial services provider. But they have one thing in common: it wasn’t the technology that made the difference. It was the decision not to separate strategy from implementation.
Bridging the gap between strategy and implementation
So, to answer my question from earlier: what the financial industry really needs from IT partners and where measurable impact is created. It’s not about a partner who promises success. It’s about a partner who helps structurally bridge the gap between strategy and implementation: through shared responsibility throughout the entire journey, through AI as an integral part of every development step, and through a consistent focus on the problem, not the solution.
Those who take this into account will have a lead in three to five years that will be hard to catch up with.
