

The client is a prominent financial institution in Central Asia, offering a full suite of retail and corporate banking services, including loans, deposits, cards, and trade finance. Recognized for its wide-reaching customer base, the company leads the market through accessible offerings, customer-first service, and a dedication to financial inclusion.
As a part of enterprise-wide digital transformation initiative, the client rapidly scaled its QA function to support growing project demands. While this expansion enabled faster development, it also introduced challenges in maintaining consistent quality standards. In certain project teams, testing had long been performed by business analysts, which, while efficient in the short term, placed additional strain on resources. As the complexity of systems increased, particularly with the shift to a microservices architecture, so did the need for more structured regression testing and expert QA practices.
Therefore, to ensure continued delivery excellence, the client sought a reliable partner.
When a1qa joined the project, the client already had SAFe-based testing workflows and an in-house QA Center of Excellence led by the Head of QA. The center included various testing experts responsible for developing, implementing, and managing company-wide processes, as well as supporting and training teams.
a1qa quickly integrated into the client’s QA landscape and performed the following activities:
As part of a multi-vendor engagement, a1qa was chosen as one of the QA consultants to ensure alignment with new development processes and modern quality standards, leading to improved delivery consistency, product reliability, and end-user satisfaction.
To help the client gauge the effectiveness of QA process implementation across the entire organization and define actionable improvements, a1qa dedicated four independent QA consultants with decades of experience in the banking sector. They swiftly adjusted to the client’s time zone and performed the following activities across 15 project teams:
This holistic approach gave the company a clear view of where quality was slipping and how to fix it fast, not just in QA, but across Dev, DevOps, and BA functions.
If the suggested metrics are implemented, they’ll gain an objective, trackable quality indicator. Improvements in release processes are expected to reduce hotfixes, end-user defects, and probable post-release rework. The proposed forecasting tool will help plan resources as the client base grows and manage load-related risks more effectively.
Most importantly, the Head of QA was empowered with clear data and compelling insights to successfully advocate for strategic quality initiatives, including robust load testing and dedicated pre-production environments. These initiatives were swiftly approved and resourced, marking a major step forward in strengthening the organization’s QA capabilities.
Additionally, QA gained more authority, with their input now considered in the release process, and there were fewer instances of development tasks bypassing QA oversight.
To help the client successfully cope with the constantly increasing volume of regression testing activities, a1qa dedicated the team of 4 QA automation engineers that was later scaled up to 11 specialists.
During testing, the experts implemented end-to-end API, mobile, and web UI test automation from scratch across a wide range of customer-facing, business, and internal IT products. The team navigated the complexities of test data and environment management by implementing an automated mechanism for generating test users (with balances, cards, loans, access rights, etc), effectively streamlining a traditionally arduous process. The automated launch of relevant test suites, established by triggers from front-end and back-end systems, helped improve the speed and consistency of regression testing and enabled earlier detection of defects across the entire software.
To provide actionable insights and a shared understanding of the software’s quality and the testing process itself across a project team and with stakeholders, a1qa’s engineers developed a Swagger report to show the actual test coverage for APIs and also set up integration with Zephyr to enable fast and clear visibility of test run results.
The team also proactively developed comprehensive training materials for the client, empowering them with the essential knowledge and skills needed to effectively maintain the automation infrastructure and ensure its long-term reliability.
This complex approach helped the client achieve 75% coverage for UI regression testing and 93% for back-end regression testing.
Additionally, to extend these gains, a1qa is finalizing a Claude AI-powered tool integrated with Zephyr for generating test cases considering set requirements. By applying different test design techniques, it takes functional and testing criteria as input and generates checks for both UI and API quality control. While the tool is still in the integration stage, it’s expected to reduce the QA team’s efforts in preparing checklists and shorten the time needed to create test cases.
The client now has the insights and confidence to make data-driven decisions and move forward with greater speed, stability, and quality.