I’ve been through more fintech acquisitions and mergers than I care to count. Enough to know that the real complexity doesn’t start in the boardroom. It starts after the handshakes.
Sure, pre-merger is full of challenges. Especially in fintech, where regulation runs deep and international laws don’t always play nicely.
But that’s just a warm-up.
As a Lead Software Engineer, I’ve seen this unfold again and again. The deal closes, the victory lap isn’t even over, and we’re already on the clock. Product and engineering are under fire to deliver. Roadmaps clash, systems don’t sync, and the pressure builds fast. It’s go time, but often, Architecture and Engineering haven’t had a real seat at the table.
Whether it's data pipelines that don’t talk to each other, dev teams using wildly different tooling, or leadership expecting plug-and-play results overnight, it’s a familiar story.
How do you break that cycle? From working with clients across tons of Pwrteams projects, here’s what I’ve found.
Mismanaged integrations escalate business problems fast. Most times, when you don’t take the right steps early, the same issues tend to show up:
Most of it stems from one source:
Good news? These issues aren’t new. They’re predictable and in most cases, fixable, provided you act in time. Clear them out early, and you’re setting every team, project, and department up for a smoother run down the line.
When fintech companies merge, integration issues aren’t usually a one big wreck; but slow friction builds over time. What breaks isn’t the tech itself, but the misguided assumptions that stitching it all together won’t be that much work.
The challenge in fintech integration is not about Java vs .NET or React vs Angular. It’s about the shape of your inherited systems and whether your team can keep them running.
Mergers tend to trip up on the same usual suspects: brittle legacy code, zero documentation, and tangled dependencies no one flagged. If something runs on niche technology no one speaks, in most cases, it's likely safer to migrate than patch.
At Funding Circle, we rapidly built a dev team in Sofia that was aligned with their stack (Ruby, Clojure) and embedded it directly into the core staff. Because structure and ownership were clear from day one, we integrated fast and avoided rework.
Sometimes, you can wrap legacy systems with adapters. Other times, you need to start from scratch. But that should always be a conscious choice, not a default
If I had to pick the single biggest risk in fintech integration (apart from cultural fit), it’s data. Full stop.
In fintech, everything runs on information: balances, transactions, compliance logs, and risk scores. Merge that data poorly, and you could lose business, trust, or both.
Rule one is don’t cut corners.
We’ve seen teams move fast and skip audit event streams, thinking they were secondary. Months later, when regulators asked for records, they couldn’t produce them. The integration isn’t just about copying a database. It’s about syncing events, keeping context intact, and managing transform logic transparently.
Different teams bring different philosophies: microservices on one side, a monolith on the other. And while monoliths get a bad rap, they can work just fine if they’re simple and stable. KISS and DRY still matter, especially when combined with a Lean mindset.
But if multiple teams are stepping on the same codebase, friction’s unavoidable. In those cases, either merge the teams or start splitting the system. AI can help suggest boundaries for microservices, but don’t treat it as gospel. Use it to challenge assumptions, then make your own calls.
When choosing between “merge it” and “break it up,” we ask two things at Pwrteams: What’s slowing us down? And what will be a nightmare to maintain six months from now?
One nearshore team working with c-Quilibrium faced this head-on while extending their cash supply chain management platform. The dedicated Pwrteams team delivered a tailored .NET and SQL stack that plugged cleanly into their UI and business logic, while respecting the constraints of their existing systems. That kind of alignment lets you extend with confidence instead of rebuilding in a panic.
I’ll say it again: Tech is the easy part.
After a merger, engineers face unfamiliar tools, rituals, even leadership styles. If team values or delivery habits don’t click, tension builds fast, and it’s a shortcut to turmoil.
If cultural alignment is not treated seriously from day zero, teams with different agile maturity levels struggle to sync, key people might leave, and domain knowledge can vanish overnight.
That’s why early engagement matters, through retrospectives, joint planning sessions, and honest conversations about how people want to work together.
Supporting our clients through that, we’ve used Team Topologies to reshape team structure and Agile coaches to realign delivery rhythms. Just getting teams to share metrics and friction points can reset the tone completely. But it has to be done.
Even the best-prepared teams run into gaps during integration. They hit the wall with cloud migration, event-driven architecture trips people up, and API designs don’t line up. Sometimes the know-how just isn’t there in-house. Without shared domain knowledge, even well-built systems can become hard to run and expand.
In that case, where do you start?
My recommendation is to figure out where the blank spots are first, and then fill them in fast. Use glossaries, business rule docs, domain models, and workflows, whatever helps people get up to speed quickly and with confidence. Then, build a dedicated integration team focused on foundational work. Also, get Engineering and Architecture leads involved early, to guide that stage.
At Pwrteams, we often jump in at exactly this point, designing integration pipelines, rewriting legacy services, helping different business units talk tech with each other. Sometimes that outside perspective is the missing piece to fill the integration gaps.
Mergers are intense. Nobody gets a perfect playbook because variations occur.
But after steering plenty of integrations across the finish line, I’ve picked up some invaluable lessons that can only be learned on a living organism. Feel free to build on that:
Sometimes things look fine until you zoom out. So, if you’re wondering whether your integration is on shaky ground, there are a few patterns that show up again and again. These are the early warning signs that something in your architecture, planning, or coordination needs attention.
Here’s what I look for.
When your teams consistently complete fewer story points over several sprints, it’s often a sign of hidden complexity. Maybe the integration is messier than expected. Maybe old services are harder to work with than anyone thought. Or perhaps nobody has full context on the domain. Either way, velocity dipping without explanation means it’s time to reassess.
If requirements shift 15–20% (or more) from one sprint to the next, something upstream’s off. I see it all the time when teams start merging KYC, fraud, or scoring systems. You start building with assumptions; mid-sprint, someone flags a missing compliance rule or a critical piece of business logic. Suddenly, the whole thing’s in flux.
Teams working under pressure sometimes “just get it working.” That’s fine once or twice. But if cutting corners becomes a pattern, you’re stacking up debt that will slow you down later. Watch for workarounds replacing solid architecture. If teams are avoiding writing tests or skipping schema validation just to ship, you’ve got a problem.
Unit tests don’t tell the full story in integrated fintech platforms. If end-to-end tests for loan workflows, transaction paths, or onboarding flows start failing, especially ones that used to pass, that’s a regression you can’t ignore. It often points to misaligned API contracts or business rules shifting underfoot.
When one team constantly waits for another to deliver an API, fix a bug, or clarify a contract, your dependencies aren’t clear enough. We use issue tracker tags to flag blocks. If that list grows sprint to sprint, it’s a signal: integration friction is stalling delivery.
(Quick checks that tell you where things stand)
| System health | Error rates, CPU/memory spikes, slow response times |
| Business metrics | Loan approval time, application-to-offer duration, conversion rates, false positive/negative rates in fraud detection |
| Integration metrics | API success/fail rates, message latency, retries |
| User experience | Page load time, app responsiveness, drop-off during workflows |
| Deployment metrics | How often you deploy, how fast changes hit production, and rollback rates |
Not all signals are bad. If your fintech integration’s working, you’ll start to feel it even before the dashboards confirm it.
Teams begin to move with more confidence. Questions shift from “Who owns this?” to “How do we extend it?” You don’t need emergency meetings to ship features. That’s when you know things are settling in the right direction.
Signs of real progress in a fintech integration:
Integration is rarely smooth. But it doesn’t have to be upside-down either.
I’ve seen teams use a fintech merger as an opportunity to simplify systems, rethink workflows, and even test out new tools like generative AI for rapid prototyping. If you’re deep in it now, don’t just survive it, use it.
And if you need a hand, whether that’s architectural help, extra engineering support, or someone to carry the load while your core team focuses, we’ve been there. Just ask, we’re here.