With over two decades of experience in enterprise architecture and digital banking, Nenad Crncec is one of the leading regional voices in transforming how banks and fintechs approach technology. As a seasoned software architect and founder of a consulting firm specializing in digital transformation, Nenad has played a pivotal role in reshaping the architectural foundations of major European financial institutions.
From leading the rollout of Event-Driven Architecture across a multinational banking group to embedding agile methodologies across development squads, his work bridges strategic vision with on-the-ground implementation. He’s not only helped define architecture principles and governance at scale, but also pushed for cultural and mindset shifts within deeply traditional sectors.
IT Logs caught up with Nenad during Money Motion 2025 in Zagreb to explore what strategy architecture really means, why AI agents are more than just hype, and what’s holding banks back from fully embracing transformation.
IT Logs: Nenad, could you start by explaining what strategy architecture means and why it’s important for companies in the banking and fintech sectors?
Nenad Crncec: We’re a company focused on IT strategy architecture, particularly enterprise data and solution architecture, with a strong focus on banking and fintech. We have offices in Zagreb and Vienna and mostly employ experienced architects with years of background in banking. We provide consulting and implementation services, co-development, and more.
We started two or three years ago supporting digital transformation projects by embedding our people—product owners, Scrum Masters—into teams to help banks adopt Agile culture and a new way of thinking. As an extension of that, we built an AI assistant that helps people write user stories, create backlogs, and more. It started as a tool to support Agile delivery and has grown significantly in capabilities and integrations.
We see it as an AI that operates in the background—something that helps turn a business vision into an actionable backlog so teams can start building right away. We’ve added features like agents that can pull user stories, start coding, bring in boilerplate code, update documentation, write executive summaries, generate reports, and more. It’s especially useful in large organizations with multiple teams because it helps track dependencies and blockers.
We aim to make it as seamless and unobtrusive as possible—nobody wants to use yet another app. Everyone has their own AI tools now, and it becomes a burden. That’s why, when speaking to clients, we often hear that they invest in AI tools, but no one uses them—because they just feel like another task. If using the tool is an effort, people will avoid it.
We’re trying to simplify the entire development process. Nobody likes writing functional specifications, business requirements, or technical documentation. This tool gets you about 80% of the way there. Of course, a person is still needed to validate things. But it’s not just helpful for humans—it also builds a knowledge base that makes our AI agents smarter over time.
From your perspective, are AI agents the next big thing in digital transformation?
NC: They’re definitely the new thing. This space is moving incredibly fast—what you knew a year ago is already obsolete. If you invested in a technology a year ago, chances are you’re already redoing it now.
As architects, we’ve designed our AI assistant to be future-proof. It’s built on a composable architecture: small components that work together. If one part changes, we can isolate the impact, which makes it easy to scale and maintain.
This is something we always emphasize to our clients: it’s not just about AI—it’s about adopting an architectural mindset that ensures what you’re building is sustainable and cost-effective in the long run.
Given your experience in digital transformation and banking, where do you think the industry currently stands in this process?
NC: I’d say we’re about halfway there. Digital transformation often starts at the user interface—changing the app or the front end—but not the underlying processes. There’s an expectation that keeping internal operations the same will magically become more efficient. That’s not how it works.
It’s like saying, “We installed Jira, now we’re Agile,” without changing anything else. Real transformation requires a mindset and cultural shift, which is particularly difficult in banking. Banks are conservative and risk-averse. Any change needs to be well thought out, with risk analysis and planning.
Banks are investing heavily in technology and trying to push boundaries, but often only on the surface—it doesn’t go deep enough to impact the full value chain.
How would you describe the current relationship between banks and fintechs? Are they coexisting, competing, or collaborating?
NC: It depends on the use case. For core banking products—like loans, deposits, and mortgages—you still need a banking license. Fintechs often handle payments or user interfaces, but they can’t offer the full spectrum without partnering with banks.
Open banking initiatives are one way banks are trying to expose their data and capabilities so others can build better user experiences. But banks themselves are also trying to innovate. So it becomes competitive—everyone wants a slice of the same pie.
In my view, banking should become an integrated part of life. If I’m buying a car, I shouldn’t have to visit a branch or sign papers. The bank and dealership should be seamlessly connected. That requires both technical capability and a willingness to rethink how products are delivered.
Beyond AI, what other trends do you foresee shaping the future of banking and fintech?
NC: Hyper-personalization is a big one—making banking feel tailored to the individual. For example, dynamically generated UIs based on your behavior, showing only what you typically look for. AI can do that in real time.
Another example is anticipating customer behavior. If I’m looking at cars for a few weeks, the bank should pick up on that and offer a pre-approved loan before I even ask. Imagine a scenario where your bank tells you that a dealership is having a sale and you’re already approved to buy. That kind of proactive integration is the future.
Of course, that raises questions about data: How it’s acquired, stored, and used. Are we okay with banks knowing we’re shopping for a car? Maybe some people don’t care, but it’s still personal information. And we’re not yet fully compliant with data protection regulations like GDPR. That becomes a blocker to innovation.
Do you see compliance and regulation as a challenge or a potential advantage for innovation?
NC: It depends who you ask. For companies, it’s definitely a challenge—it adds cost. Just meeting EU reporting requirements for data processing or training large language models is a headache. Running an LLM-based company in the EU today is tough.
But regulations are there for a reason: to make sure data is used responsibly. Still, when you compare the EU to places like the U.S. or China—where regulations are more relaxed—those regions are moving faster and innovating more freely.
The reality is, they already know everything about us. And when it comes to technological dependencies—from cloud infrastructure to chip manufacturers—the EU is still catching up.
