Dzmitry Lubneuski is the CIO at a1qa, a leading pure-play software testing company. He’s a tech expert with a solid 20-year background in QAgetty​Every transaction is a promise the system has to keep.As transaction volume grows and more services depend on each other, keeping those promises becomes more complicated. Failures spread further. More payments are affected. More customers feel the impacts.Transaction volume is rising while resilience and compliance expectations are getting tighter. The European Central Bank reported 77.7 billion non-cash payments in the euro area in the first half of 2025, up 7.7% year on year, with a total value of 116.0 trillion euros.​ Meanwhile, the U.K. Treasury Committee reported at least 158 banking IT failure incidents affected millions of customers between January 2023 and February 2025, with at least 803 hours of unplanned outages across nine major banks and building societies.How can a financial technology (fintech) company grow without letting transaction, recovery and dependency risks grow with it?Infrastructure matters, but it’s only part of the answer. Scaling servers isn’t enough. The business has to scale quality governance alongside it. When testing, release control and resilience checks fall behind, the business carries more risk of transaction failures, service disruption and control gaps.Why Older QA Approaches Fall ShortA lot of QA approaches were built around release readiness. That is less useful in systems that process transactions at scale and stay available around the clock. If a payment flow passes testing but fails under live load, what did the release sign-off actually prove?A feature can pass functional testing and still fail in production. Load patterns change. Retry traffic increases. A third-party service slows down.Reactive testing starts to fall short here. It can show that something works under expected conditions, but it says much less about how the service behaves under pressure, during degradation or after a partial failure. Periodic performance testing still has value, but on its own, it leaves gaps in fast-changing systems.The same issue shows up in reporting. Pass rates and defect counts still matter, but leadership also needs to understand recovery time, backlog growth, third-party dependency signals and risk tied to critical workflows.What Breaks When Quality Doesn’t Scale​In high-load financial systems, one fault can spread across the service chain.A payment flow may pass testing and still fail when peak demand changes traffic shape. An identity service may remain technically available while response time degrades enough to trigger retries, queue growth, timeout failures or missed service targets. A reconciliation process may still be completed, but happen too late to meet customer, operational or regulatory expectations.The consequences are direct. Failed or delayed transactions can reduce revenue. Service instability can increase downtime costs, support demand and SLA pressure. Recovery gaps can surge regulatory exposure when important services fall outside defined recovery or service thresholds. Repeated disruption can also damage reputation.Where Leaders Should FocusTo close the gap between growth and control, leaders should focus on four areas of quality engineering. These are the areas where weak quality can lead to revenue loss, service breaches, extra operational effort and regulatory pressure.1. High-Load And Performance EngineeringPerformance engineering should reflect business growth, not generic concurrency targets. Load models should take into account customer growth, seasonal peaks, marketing activity, product launches and other demand shifts. Stress, spike and endurance testing help show how services behave under surges and sustained pressure. Under load, small delays can turn into retries, queue growth, timeout failures and dropped payment flows. Capacity planning should cover the full transaction path. In fintech, realistic lower-environment testing also depends on masked or synthetic test data that preserves production-like behavior across payment and fraud flows.2. Risk-Based Quality GovernanceA risk-based model puts more testing and review effort on workflows with the highest financial, compliance or customer impact.That usually means focusing on measures such as payment completion, settlement timing, fraud-control availability, recovery time, transaction backlog and dependency latency or error behavior. Tracking indicators like mean time to detect, mean time to recovery, and transaction success rate makes this more concrete.When quality measures map to business key performance indicators and operational risk indicators, they become easier to use in release and investment decisions. They also help senior leaders see where risk is building and where more resilience or testing work is needed.In many fintech systems, risk sits in pressured service interactions, as well as code quality.3. Continuous Quality In Cloud DeliveryFast release cycles need continuous validation. A late test phase gives less protection in cloud delivery environments where change is constant.Automated regression checks, performance thresholds, SLO checks and rollback gates can be built into delivery pipelines. This pushes defect detection earlier in the cycle. Observability improves detection, diagnosis and release monitoring.4. Resilience And Failover ValidationRecovery plans need proof behind them. Backup design, disaster recovery arrangements and cloud redundancy matter most when they are tested under realistic failure conditions.Resilience validation should include failover exercises, disaster recovery checks, third-party disruption scenarios and multi-region failover tests that measure failover time, data consistency, replay handling and backlog drain.This matters in fintech because many firms depend on shared providers. That is why firms need a clear view of which third parties sit on the critical path for payments, identity, fraud checks, customer communications and core services​.What Quality Practices Protect As Fintech Grows​Uptime Institute’s 2025 outage analysis found that 54% of respondents said their most recent outage cost more than $100,000, while one in five put the cost above $1 million. Quality engineering, then, protects businesses' bottom line. ​When quality practices scale with growth, the business gets better protection against avoidable disruption. These practices can help reduce production incidents, limit downtime costs, and support faster and safer releases. They also improve compliance readiness.Quality engineering works as a control mechanism by testing capacity, validating recovery and tightening release decisions. Fintech companies that expand it alongside the business are in a stronger position to manage operational risk and support growth without weakening control.​Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?