Extended Reality (XR) technologies, including virtual, augmented and mixed reality, are no longer confined to gaming and entertainment.
Increasingly, financial institutions are exploring XR as a tool for client engagement, immersive data visualisation, and interactive training platforms. But with these new interfaces come entirely new testing demands for QA teams at banks and financial services firms.
A major new academic study has mapped out the unique software testing challenges XR presents and how QA teams in banking and financial services should respond.
The paper Software Testing for Extended Reality Applications, which was shared with QA Financial, is one of the first to systematically analyse 34 primary studies on XR testing.
The report’s lead author, Ruizhen Gu, of the University of Sheffield in England, charted the evolution of testing techniques, outlines test objectives and challenges, and identifies tools and methodologies being developed for this fast-emerging field.
Unlike traditional 2D apps, XR apps operate in 3D environments, often on head-mounted displays, using six degrees of freedom interactions.
This means user input isn’t limited to touch or mouse clicks, but involves full-body movement, rotation, and spatial awareness. In banking, that could mean walking through a virtual branch, interacting with floating financial dashboards, or manipulating virtual loan documents.
This level of immersion poses major challenges to QA teams. Testing the reliability, usability, and security of XR applications requires new approaches that go far beyond standard GUI or mobile testing frameworks.
Traditional testing falling short
For banks, where performance and compliance are critical, XR introduces variables that can’t be addressed by conventional test scripts.
“A simple task, such as moving toward and interacting with a virtual object, requires accounting for countless variations in interaction sequences,” the study explained.
Traditional mobile or desktop testing relies on finite state machines and reproducible interactions; XR apps often behave differently depending on spatial context, device configuration, or even lighting conditions.
Existing simulators like Meta XR Simulator and Unity XR Device Simulator help, but they come with limitations. While these tools allow record-and-replay style testing, even small changes to the scene or UI can break test scripts, demanding frequent updates and manual intervention.
The study categorises test activities in XR into automation, test data generation, input generation, and oracle prediction.
“Testing must evolve from traditional state-machine-based models to new paradigms.”
– Ruizhen Gu
Notably, test generation, which automates both inputs and expected outputs, remains underexplored due to technical complexity. Most financial firms engaging with XR will need to combine automated and manual testing in the near term.
Testing objectives in the reviewed studies were primarily functional, but usability and security also featured prominently.
Cybersickness, a form of motion sickness in VR environments, and user interaction errors were recurring issues. These concerns matter in banking, where client comfort and trust are paramount.
System-level testing dominated the research, reflecting the need to validate entire user journeys rather than isolated functions.
However, the study found a roughly equal balance between black-box and white-box methods, indicating that source-code level validation will also be important for fintech teams developing XR applications.
Rise of machine learning
Among the more promising techniques explored is the use of machine learning to detect XR bugs by analysing visual outputs such as screenshots.
This is especially useful for identifying misplaced virtual objects or inconsistencies in the rendering of financial interfaces.
Model-based testing, another approach, abstracts XR environments into simplified representations to systematically explore interaction possibilities.
Despite these advances, much of XR testing is still in its infancy. Of the 34 studies reviewed, the majority offered novel solutions with limited real-world validation. Only a handful included evaluations in production-like environments or with actual users.
In summary, as banks and financial service providers pilot XR applications for client advisory, fraud prevention training, or internal simulations, QA teams will need to adapt their practices, the report warned.
This means investing in new tools, upskilling testers in 3D interaction models, and participating in cross-industry knowledge sharing to develop common standards.
For now, the XR testing landscape remains highly fragmented. But as the study concluded, testing must evolve “from traditional state-machine-based models to new paradigms that account for the continuous and spatial nature of XR interactions.”
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