Industry
FinTech
Payments, banking, and trading systems where correctness and latency are both non-negotiable and the regulator is a stakeholder.
Capabilities
How we approach it
We start by establishing what is measurable today. Financial systems accumulate performance and correctness problems that everyone can feel and nobody can attribute, so instrumentation comes before optimisation on every engagement. From there the work is ordinary engineering discipline applied where the stakes make it worth paying for.
- 01
Payment processing and routing
Authorisation paths, acquirer routing, retry and circuit-breaking behaviour, and the reconciliation that has to agree with it.
- 02
Regulatory and compliance engineering
Audit trails, data residency, retention boundaries, and reporting interfaces built as first-class features rather than retrofitted before an examination.
- 03
Trading and market data systems
Low-latency paths where the performance budget is part of the acceptance criteria and measured continuously.
- 04
Digital banking interfaces
Onboarding, identity verification, and account servicing across web and mobile, including the older devices that make up more of the customer base than anyone expects.
Regulatory context
The constraints that shape the build
- PCI DSS
- We design to keep cardholder data inside the existing compliance boundary. Expanding scope is a decision with an annual cost, not an implementation detail, and we treat it as one.
- PSD2 and strong customer authentication
- Authentication flows built to the regulation's actual requirements, including the exemption cases, rather than the strictest possible reading that costs conversion unnecessarily.
- Operational resilience expectations
- Tested failover and documented recovery objectives, because supervisors increasingly ask to see the rehearsal records rather than the policy document.
In their words
They spent the first month measuring instead of building, which we found frustrating at the time and correct in hindsight. When the latency work landed we could prove it worked, because we had agreed what the baseline was before anyone touched the code.
Proof
Work in FinTech
Zafarin
Closing the daily reconciliation break queue at Zafarin
Zafarin's daily safeguarding reconciliation produced a queue of breaks that finance operations cleared by hand every evening, and the queue grew with transaction volume. We rebuilt the partner feeds, the ledger and the break workbench underneath it.
Vertigem
Making offline receipt capture reliable in Vertigem's expense platform
Receipts captured outside mobile coverage were dropped without anyone noticing, on shared handsets that killed the app mid-upload. Our engineers worked inside Vertigem's squads on the capture path and the reconciliation queue.
In practice
Why instrumentation comes first here
Financial platforms tend to arrive with a shared belief about what is slow or unreliable, held confidently and supported by nothing measurable. The first deliverable on most of these engagements is attribution: tracing across every hop, so the next conversation is about evidence rather than intuition.
It is unglamorous, it consumes the first few weeks, and it is the reason the numbers on our case studies have methodologies attached to them.
Questions
What FinTech clients ask
01Have your engineers worked inside a regulated environment before?
Engagement staffing for financial clients is filtered on prior regulated experience, because the difference between an engineer who has been through an audit and one who has not shows up in design decisions long before it shows up in a review.
02How do you handle our data during the engagement?
Production data does not leave your environment. Where we need realistic data for development we use synthetic or masked datasets generated inside your boundary. The specifics go in the data processing agreement before work starts.
