Can you explain what your role as a QA Engineer involves?
I’m part of the Strategy Team for SBP Core Amplitude, focusing on improving testing processes and maintaining high-quality standards. I collaborate with Test Managers and QA teams to refine strategies, enhance test design with advanced techniques, and ensure comprehensive coverage. I also train developers and QA professionals to sharpen their skills and review test plans to align with requirements, optimizing efforts for smarter, more efficient testing.
What are the biggest challenges in your mission?
The biggest challenge is balancing complexity and adaptability. Banking systems must handle diverse financial processes, comply with strict regulations, and process high transaction volumes securely. At the same time, our core banking platform must remain flexible enough to adapt to market changes and technological advancements without compromising stability or performance.
What does a typical QA process look like for a new feature?
It all starts with a deep dive into the new functionality to fully understand its scope. From there, we design a test strategy that covers every level: validating individual components, ensuring all use cases work together at the system level, and verifying the feature within the broader EPIC. This includes non-regression, technical, and exploratory testing.
Risk analysis and prioritization guide our approach. We then set up the test phase—defining test cases, preparing environments, and creating relevant datasets. During execution, we collaborate with developers, run system and acceptance tests, and validate fixes to ensure everything meets quality standards before deployment.
What tools and technologies do you use for testing SBP Core Amplitude?
We leverage a range of tools to ensure efficiency and comprehensive coverage. For test management, we use ALM and Xray, while automation is handled through specialized frameworks and tools. In test design, we apply various techniques, including ACTS (which implements the IPOG algorithm) for combinatorial testing, optimizing coverage and efficiency. Additionally, we’re exploring generative AI to enhance test design, refine methodologies, and improve overall effectiveness.
Can you share an example of a bug that testing helped catch before it went live?
Sure! We were developing a new payment flow where data was transformed into different formats and processed across multiple services. During end-to-end testing, we spotted an issue with how BIC codes were handled. If a BIC had only eight characters, one of the services automatically added three extra ones. The problem? A valid BIC can be either 8 or 11 characters long—no modifications needed. This meant the system was generating invalid BICs, which could have led to transaction failures. Catching it early saved us from compliance issues and potential payment disruptions.
Given the regulatory constraints in banking, how does QA contribute to ensuring compliance?
We analyse and understand the regulatory constraints and build tests to ensure compliance not only at each new feature scope but within the whole system. This includes end-to-end testing and non-regression testing, where we assess impacts and risks to prevent unintended violations. By continuously monitoring and adapting our test strategies, we help maintain regulatory compliance and ensure the stability and reliability of the system.
How has quality assurance in core banking evolved in recent years?
I think we’ve had to become more adaptable and responsive to change. With increasing regulatory requirements and the adoption of Agile practices, we need to continuously adjust to new technologies, methodologies, and customer expectations. Our testing strategies now focus more on automation and risk-based testing, optimizing coverage to ensure compliance and system reliability in an ever-evolving environment.
What trends do you see shaping QA in banking technology?
Generative AI is making a big impact on quality assurance, helping streamline test case generation, defect detection, and optimization. But while AI boosts efficiency and coverage, it works best as an assistant—not a replacement—for human expertise. There’s still a need for critical thinking and domain knowledge to ensure quality in complex banking systems.
Another major shift is the move toward shift-left testing and Agile methodologies. Quality assurance is no longer just a final checkpoint—it’s embedded throughout the development lifecycle. By working more closely with developers and business teams from the start, we can catch issues earlier, speed up delivery, and improve overall software quality.
If you could improve one aspect of quality assurance in your area, what would it be?
If I had to improve one aspect of quality assurance in the banking sector, it would be collaboration. It’s essential that everyone feels comfortable reaching out to QA for support during testing phases. QA integration throughout the development process is already progressing well, which is a great step forward. After all, quality isn’t the responsibility of a single team—it’s a collective effort. It’s the diversity of profiles and the complementarity of expertise that make our solutions stronger and more reliable.
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