Modern financial services depend on flawless digital performance. Banking apps, mobile payment systems, and trading platforms must run seamlessly, day and night, across an expanding range of devices and networks.
Customers expect instant, reliable experiences, while regulators demand strict compliance with security and operational standards. This creates an environment where QA and testing teams are under extraordinary pressure to deliver.
A new report by testing firm Applause report touches on this, explaining that “software development organisations face relentless two-sided pressure to deliver high-quality software. The business demands speed and efficiency, while customers demand seamless experiences and robust functionalities.”
The challenge is magnified in financial services, where outages, security flaws, or errors in transaction processing can trigger not just user frustration but also reputational crises and regulatory fines.
To survive in this environment, QA teams must evolve. The report argues that teams must “constantly reevaluate their work, improving processes and embracing new technologies to deliver software that meets everyone’s expectations.”
For banks, that means adopting adaptable testing strategies that can keep pace with rapid release cycles without ever compromising quality.
Adaptability as a game-changer
The Applause report set out why adaptability is central to QA today: “Modern software application development is performed at high speed with even higher quality demands from customers who can, and will, switch applications or even business systems nearly overnight.” In other words, loyalty in the digital age is fragile, and quality is the key to retaining it.
The report noted that adaptability “improves both the speed and quality of QA. Adaptable software testing enables organizations to release applications faster and with new features more continuously than in the past, even in industries that are highly regulated for compliance.”
For banks and financial firms, this balance is critical: testing strategies must allow faster delivery of innovations such as biometric login, real-time transaction monitoring, and advanced mobile features, but must also protect against breaches of strict frameworks such as DORA.
Adaptability, the report continued, “helps software testing teams tackle any project, any time without sacrificing quality for speed.”
That makes it a practical principle as well as a cultural one. QA managers must support their teams in moving away from repetitive routines that no longer provide value.
As Applause cautions: “Common testing repetitive patterns include: entering defects and waiting for fixes, retesting and then entering defects; executing the same series of tests every time; using the same test scripts repeatedly.”
For financial institutions operating with complex, fast-changing systems, clinging to these patterns is a recipe for missed defects and delayed releases.
The report encourages teams to break free: “Stop using testing techniques that aren’t working. Discover the power of experimentation and variety.” That perspective is essential for banks seeking resilience in a market where customer trust can be lost overnight.
Retiring old techniques, embracing new ones
The Applause report traces the evolution of testing techniques over decades, noting that many structured design methods from the 1980s and 1990s have outlived their usefulness.
As the report stated: “Structured test design has a long history in software testing. It provides a multitude of techniques that can be used to create a set of foundational tests based on the code design.
However, with Agile, there’s typically not enough depth of detail in the documentation for many of these techniques to be relevant today.”
It highlighted five testing practices that are now obsolete or too resource-intensive for modern cycles. These include equivalence partitioning, condition/decision coverage, state transition diagrams, static testing, and path testing.
For instance, the report observed: “Retire decision tables and test matrices. There’s simply not enough time in an iteration with constantly evolving code and acceptance criteria to create an accurate test matrix.”
Similarly, it concluded that while path testing might be useful for brand new applications, “the process likely breaks down after three or more releases. It’s simply too resource intensive to create the tests and then execute them all before the next release.”
This recognition is important for banks that often have legacy test packs running in parallel with newer automated systems.
As the report stressed: “Recognising and retiring outdated techniques is one step. To truly excel, we must embrace new, innovative methods that leverage the latest technologies.”
The implication is clear: financial QA leaders must not allow historical investments in outdated test design to become a barrier to modernisation.
The report suggested ways to adapt existing assets rather than discard them outright. “Copy and edit manual test scripts to reflect a unique test strategy or approach. Keep the original test intact, but create new ones that incorporate different test approaches.”
For automation, it advises: “Copy the working test scripts into a safe repository where no one can edit or delete them. Now, take the rest and share them out to the team. Edit the existing test scripts and expand them.” Such pragmatic steps are vital in financial contexts where documentation, auditability, and continuity matter as much as speed.
The AI and machine learning shift
The most striking section of the Applause report details the potential of AI and machine learning in transforming QA.
It noted that “artificial intelligence and machine learning technology has become more sophisticated every day, and they are poised to completely change software testing.”
This shift is already evident in the financial industry, where fraud detection and predictive analytics rely heavily on machine learning. The report makes clear that QA must follow suit: “AI fundamentally changes how QA teams think about testing and reshapes future testing tasks and roles.”
Among the techniques described, “intelligent test case generation” stands out. According to the report, “AI and ML algorithms analyse application functionality and test data, then identify patterns and use them to generate test cases focused on identifying defects.”
The report explained that this approach “can develop tests that cover more scenarios, including those that testers miss. Even experienced testers can overlook or miss complex scenarios.”
For banks, where risk often hides in edge cases, this is a powerful advantage.
“AI fundamentally changes how QA teams think about testing and reshapes future testing tasks and roles.”
– Applause report
Another example is visual testing. The report explained: “Visual regression testing validates that the visual elements within the UI remain accessible and visible in different user scenarios.”
With the variety of browsers, operating systems, and devices used for digital banking, automation of this process is crucial. As Applause noted: “Leveraging AI/ML within testing tools can automate visual testing and save testers significant time. Tests will automatically flag defects or changes to the page layout or elements within the page.”
The report also highlighted AI in test data generation, defect prediction, and automated maintenance. It stated: “Using defect prediction, testing teams reduce costs by using data to analyze where the greatest number of defects occur in the application.”
Similarly, it pointed out that “AI/ML tools significantly improve the bottleneck of automated script maintenance. Many tools can repair scripts automatically or can be used to provide suggestions for edits.” These capabilities are particularly relevant for financial QA, where systems are both complex and highly sensitive to failure.
The report cautioned, however, that trust must be built over time: “The technology is young and needs improvement before AI/ML becomes trustworthy on a wide basis. Software testing teams might become the auditors of AI/ML.”
This acknowledgement reflects the caution that financial services firms must exercise when integrating AI into regulated environments.
QA evolution
Perhaps the most important theme for banks is the report’s conclusion that testing evolution is not just a technical necessity but a source of measurable business impact.
“QA evolution comes with marked results: increased quality and enhanced efficiency for the organissation, and more secure, higher-performing digital products that promote more positive customer experiences.”
The report further stressed that “new ideas, technology and testing approaches not only shake up the status quo, but also allow for testing to improve regardless of changing requirements or tight testing schedules.”
The benefits extend beyond immediate efficiency, as Applause noted: “Evolving and adapting to new technology provides QA teams: active opportunities to learn and practice new skills; career growth externally or internally; reduction of repetitive and mundane test execution; infusion of innovative energy and flexibility in testing processes; faster but still effective testing for higher-quality applications.”
This cultural shift is vital in a banking context, where talent retention and skills development are as important as tools.
The report summarised: “When a QA team can evolve and adjust test strategies to meet the customers’ and stakeholders’ needs, the team builds business value and credibility.”
For banks, that business value is defined not only in efficiency gains but also in trust: trust from regulators, customers, and investors that digital platforms are resilient and secure.
In summary, the Applause report Adaptability and Evolution in Modern Software Testing offers a clear roadmap for QA leaders, emphasising that adaptability is essential, outdated methods must be retired, AI techniques should be embraced with care, and evolution generates business value.
Its message seems to be consistent and urgent: “Adaptability in software testing processes, strategies and practices improves both the speed and quality of QA.”
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REGULATION & COMPLIANCE
Looking for more news on regulations and compliance requirements driving developments in software quality engineering at financial firms? Visit our dedicated Regulation & Compliance page here.
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