The existing testing used by a leading BFSI organisation relied heavily on manual effort.
Change and feature requests documented in Jira tickets required detailed human analysis, great domain expertise or access to complex technical documentation. This process was time‑intensive, dependent on individual expertise, and difficult to scale as change volumes increased.
Key figures
Full test coverage
The challenge
Although test automation was already part of the testing landscape, it did not deliver the desired acceleration. Translating manual test cases into automated tests required additional effort, and maintaining consistency and quality across multiple testing cycles remained challenging.
At the same time, existing tooling, including early AI‑based capabilities, proved insufficiently flexible. The tools were not fully aligned with the organisation’s established testing practices and workflows, limiting their effectiveness and adoption.
The organisation therefore sought a more flexible, scalable and intelligent testing approach – one that could significantly reduce manual effort, accelerate both manual and automated test creation, and integrate seamlessly into existing processes, without disrupting their current workflows.
The solution
An initial analysis demonstrated the potential of AI‑supported testing to significantly reduce manual effort and accelerate test activities across the lifecycle. However, it also became clear early on that a standard, off‑the‑shelf solution would not fully meet the client’s specific requirements.
To ensure maximum value, Expleo designed and implemented a fully customised solution inspired by its AI testing framework and tailored precisely to the client’s existing processes, tooling and quality standards. Rather than forcing change, the solution was built to integrate seamlessly into the customer’s established workflows, ensuring high acceptance, reduced risk and fast time to value.
The outcome
The testing framework supports the full testing lifecycle through a modular, AI‑driven pipeline.
- Context ingestion
Existing documentation, such as Confluence pages and test concepts, is captured and structured into a central knowledge base, creating a consistent foundation for all testing activities. - Jira ticket processing
Change and feature requests are automatically classified and analysed, with relevant information extracted. - Manual test case generation
AI generates human readable, structured manual test cases with clear preconditions, actions and expected results. Customisable prompts enable the customer to fine-tune the output to their needs. - Analytics and quality checks
Integrated analytics support quality assurance through gap analysis, duplicate detection and review support, helping teams improve coverage and consistency. - Automation readiness and generation
An advanced agentic solution is designed to autonomously navigate the client’s application, systematically mapping its interface and functionalities. It takes into account existing test cases and efficiently translates newly created manual test cases into executable automated test scripts for Playwright or Selenium.
Client benefits
The solution delivered immediate and measurable value to the business by accelerating testing activities and improving overall test quality and efficiency:
- Significantly faster creation of manual test cases through AI‑assisted generation
- Substantial efficiency gains enabled by the generation of ready-to-execute automated tests resulting in shorter time‑to‑test for new changes
- The manually created test cases provide a high level of control over content, coverage, and adherence to the testing strategy, while the development of Selenium or Playwright test scripts enables reproducible and automated test execution.
- Reduced cognitive load for testers, shifting effort from test creation to focused review and validation
- Improved consistency and test coverage across frequent change cycles
- Scalable use across banking, insurance, and other BFSI and software centric industries
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