Data centers are not sterile laboratories, but crisis zones. While the customer sees a clean interface on their smartphone, there is a constant battle against entropy, latency and interface chaos in the backend.
The truth is: there is no "perfect" system behind every successful bank transfer. There is an architecture behind it that is just barely kept from collapsing. Functional testing in banking, as in other industries with complex IT, therefore rarely serves to simulate flawlessness. Its sole purpose is to manage the inevitable failure of components in such a way that the customer experience is not affected and regulations are complied with.
The idea that banking software should "never" have errors is dangerous. Hardware fails, API partners have timeouts, suppliers' systems falter, deployments fail. This is not an accident, it's a statistic.
We are therefore currently testing not only the "happy path", but also resilience:
Without these mechanisms, technical trivialities cause chaos.
Modern banking IT is no longer a monolithic block, but a highly complex network: COBOL mainframes form the foundation, cloud services the infrastructure and React frontends the interface to the customer.
In this hybrid architecture - often exacerbated by the coordination of globally distributed teams (offshore/nearshore) and ongoing cloud migrations - quality assurance is no longer a purely technical issue. It becomes strategic risk management. Three examples of why interaction is critical:
Testing everything is impossible. Anyone who promises this has no budget awareness. Resources are finite, which is why we use risk-based testingin test management - also with a view to DORA :
We prioritize mercilessly according to damage potential:
The decision is strategic: in consultation with the stakeholders, we secure the critical path (cash flow & data) with maximum rigor. We weigh up UX issues - we accept a documented, calculated residual risk as long as the core operation (the security of funds) is not jeopardized.
| Characteristic | Conventional testing (compliance focus) | Resilient testing (business continuity focus) |
| Basic assumption | "The system works as long as no error occurs." | "The system will fail - the only question is when and how." |
| Test scenarios | Happy Path: We test what is in the specification (target state). | Chaos Engineering: We test what is not in the specification (network failure, slow third-party providers). |
| Database | Synthetic: Clean "lab data" that fits the logic perfectly. | Realistic: "Dirty" production data, historical legacy, coding conflicts (legacy). |
| Success metric | Green lights: "All 500 test cases passed." (Deceptive security) | Time-to-recovery: "How quickly does the system recover after an error?" (Real stability) |
| Attitude towards errors | Errors must be prevented. | Errors must be mitigated and understood (traceability). |
Ultimately, functional testing is an insurance policy against the reputation super-GAU. Customers expect functioning transactions like electricity from the socket. When banking systems "just work", it is not by magic, but because tests were running in the background, anticipating and absorbing the chaos.
Quietly, efficiently and without applause. Just as it should be.
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