A mobile banking and payments provider in Africa (named reference under NDA) was testing a regulated consumer money platform by hand. OpenTurf Technologies, now part of Ariviti, embedded a quality-engineering team and replaced the manual pass with automation built for that product — faster release cycles, lower cost, compliance held.
The provider runs a mobile banking and payments platform in one of the most demanding environments there is: high transaction volume, real consumer money, and strict regulatory oversight in its African markets. As the product grew, the test surface grew with it — and the team was still testing by hand.
Manual testing could not keep up. Every new feature lengthened the regression cycle, pushed up cost and slowed releases, while the regulatory bar meant nothing could ship without thorough, demonstrable coverage. The combination is a familiar trap in regulated fintech: the faster you need to move, the more manual testing holds you back, and the more tempting it becomes to cut corners you cannot afford to cut.
The core problem: a quality process that did not scale with the product, in an industry where quality is non-negotiable.
This is the posture behind the i3QA™ practice: quality engineering embedded from requirements, not appended at the end; reliability measured and reported, not assumed. There is no model in this test suite — it is a hand-designed strategy, open tooling and a pipeline.
We owned the test strategy and the automation, worked collaboratively inside the provider's delivery process, and stayed engaged across multiple projects as the relationship grew — accountable for release confidence rather than billing for hours. Quality Engineering owned the engagement: the team was embedded in the provider's process, but release confidence stayed the practice lead's to answer for.
Application quality improved with the cadence: defects are caught early in the pipeline rather than late in production, which is the whole point of moving the regression suite off human hands.
The thing worth taking from this engagement is not the tool choice. It is that the strategy was designed from the application outward — coverage placed where this product's risk sits — rather than a generic automation layer draped over an existing manual script set.
Stack — Selenium · CodeceptJS · Jira · CI/CD pipeline integration
Tell us the regression cycle and what a regulator needs to see. We will tell you what to automate first, and what is not worth automating at all.
