In modern banking and financial services, software releases no longer end at deployment. They extend into regulatory scrutiny, audit trails and ongoing accountability.
Every change to a payment flow, onboarding journey or fraud detection system carries embedded compliance obligations, and the expectation that these can be proven at any moment.
That shift is fundamentally changing the role of QA and software testing teams. It is no longer enough to validate functionality or performance in isolation.
Teams are now expected to demonstrate, continuously and with evidence, that critical controls are working as intended across increasingly complex, interconnected systems.
The challenge is that this proof is often only tested after the fact, when auditors, regulators or partners come knocking. And by then, the margin for error is gone.
As Dzmitry Lubneuski, CIO at a1qa, a pure-play software testing company, put it: “A release is launched and everything seems fine. But weeks later, a regulator, auditor, partner, insurer or customer asks questions. What controls were in place? Did they work? Where’s the proof?”
That moment, he explained, is where QA either protects the business, or exposes it. “Then the issue becomes commercial, legal and reputational,” Lubneuski notes. “And when the answer is fuzzy, the cost climbs fast.”
Costs of weak testing
Recent regulatory actions underline how quickly gaps in testing and assurance can translate into financial and operational damage.
“Recent examples demonstrate the speed at which these costs show up,” Lubneuski explained, pointing to fines, settlements and breach costs that now run into millions.
Against this backdrop, the core challenge for QA teams is becoming sharper and more urgent. “The business question comes down to this: How can organisations deliver digital services quickly while keeping every release compliant, minimizing risk to the business?” he wrote in a recent Forbes Council analysis.
In banking environments shaped by frameworks such as PCI DSS, GDPR and the EU’s DORA, the answer increasingly sits with QA.
The ability to prove that controls are working, consistently and continuously, is now a regulatory expectation, not a nice-to-have.
“Testing and assurance matter. They lower regulatory risk by demonstrating that key controls are functioning.”
– Dzmitry Lubneuski
Modern financial systems are deeply interconnected, spanning mobile apps, APIs, fraud engines, payment processors and third-party services. That complexity is exactly where QA becomes critical.
“Fintech and eHealth systems are rarely simple,” Lubneuski pointed out. “A payment journey can move through a mobile app, API, fraud tool, bank and third-party services before a transaction is approved.”
For QA teams, this creates a multi-layered testing challenge: validating not just functionality, but the integrity of controls across distributed architectures.
“That is where testing and assurance start to matter,” he explained. “They lower regulatory risk by demonstrating that key controls are functioning and leaving behind evidence.”
The emphasis on “evidence” is key. In regulatory environments, testing without traceability is effectively testing without value.
The evidence gap
One of the most persistent weaknesses Lubneuski highlighted is not a lack of testing activity, but a lack of usable proof.
“When testing processes are weak, teams cannot easily show what was covered, what changed or whether a sensitive control was touched,” he stressed.
“Evidence gets pieced together late from screenshots, tickets, spreadsheets and one-off notes.”
For banks, that creates direct exposure. “Audits get harder to support. Launches slow down. Fixes cost more because problems are found later. Trust takes a hit because the organisation cannot prove control effectiveness with confidence,” he added.
This is exactly where QA maturity becomes a competitive differentiator. Institutions that can demonstrate control effectiveness in real time are better positioned to move faster, release with confidence and withstand regulatory scrutiny.
Continuous assurance
The shift now underway in financial services is moving QA from isolated testing cycles to continuous, evidence-driven assurance.
“Most organizations don’t need extra testing just for the sake of it,” Lubneuski said. “They need better proof that key controls keep working as the product changes.”
That shift is driving the adoption of unified quality pipelines that bring together functional, security, performance and resilience testing into a single, traceable flow.
“Testing helps reduce regulatory risk by showing whether key controls are working, what has changed and what evidence exists to support compliance,” he explained.
Automation plays a central role, but only if it produces audit-ready outputs. “Automation only helps if it produces usable, auditable evidence like time-stamped results linked to releases and controls,” Lubneuski noted.
AI is also starting to reshape testing strategies, particularly in high-change environments such as digital banking platforms.
“AI can be very practical. It supports repetitive checks, spots unusual patterns and helps teams focus on changes that might cause risk,” he said. “But if the results can’t be explained, the audit problem stays.” For QA teams, explainability is becoming as important as coverage.
Continuous monitoring
Another critical evolution is the extension of QA into production environments. “Continuous monitoring fills another gap,” Lubneuski explained.
“Scheduled tests show what passed at a specific time. Monitoring reveals what’s happening in production right now.”
This is particularly relevant for areas such as payment security, where threats evolve continuously. “Payment page protection is a good example,” he said, pointing to growing expectations under PCI DSS to prevent e-skimming and tampering.
“Manual checks don’t work well here, especially when pages change often or use outside code.”
For banks, this reinforces a broader shift: QA is no longer confined to pre-release validation. It is becoming an ongoing control mechanism embedded across the software lifecycle.
Ultimately, Lubneuski framed compliance-focused QA as a transformation in how financial institutions manage risk. “Regulatory risk reaches into launches, deals, trust and growth,” he stressed.
The implication for QA teams is significant. Testing is no longer just about defect detection, it is about control validation, evidence generation and regulatory assurance.
“When they properly support compliance, teams catch control drift earlier, keep evidence current and make audits easier to support,” Lubneuski concluded.
“Compliance-focused QA helps turn compliance from a last-minute scramble into something that is checked, visible and provable throughout delivery.”
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