Case Study
A UK mid-tier financial services firm with a 23-person QA team adopted Softomate's Testomate platform to automate regression and UAT testing on its customer-facing platform, cutting full UAT cycle time from 14 days to 3, improving defect-detection rate by 37%, and freeing the QA team to focus on exploratory and risk-based testing rather than repetitive scripted runs.
1 min read By Deen Dayal Yadav, Founder & AI Automation Director
UK mid-tier financial services firm, 23-person QA team, mission-critical customer-facing platform
A UK mid-tier financial services firm with a 23-person QA team adopted Softomate's Testomate platform to automate regression and UAT testing on its customer-facing platform, cutting full UAT cycle time from 14 days to 3, improving defect-detection rate by 37%, and freeing the QA team to focus on exploratory and risk-based testing rather than repetitive scripted runs.
UK mid-tier financial services firm, 23-person QA team, mission-critical customer-facing platform
A UK mid-tier financial services firm with a 23-person QA team adopted Softomate's Testomate platform to automate regression and UAT testing on its customer-facing platform, cutting full UAT cycle time from 14 days to 3, improving defect-detection rate by 37%, and freeing the QA team to focus on exploratory and risk-based testing rather than repetitive scripted runs.
A UK mid-tier financial services firm operating a customer-facing platform serving over 400,000 retail customers had a 23-person QA function responsible for testing every release of its core platform. The platform was business-critical: outages or material defects had direct customer impact and regulatory implications under the firm's FCA permissions. Release cadence was monthly, with each release preceded by a structured User Acceptance Testing cycle that the firm's risk-and-compliance function required as a sign-off gate before any release reached production.
The UAT cycle was the operational pinch point. Full UAT covered approximately 1,400 scripted test cases across the platform's seven core modules (customer onboarding, account management, payments, transfers, document management, notifications, and reporting). The cycle was executed largely manually by the QA team, with each test case taking on average 4 minutes to execute including the time to set up test data, walk through the scripted steps, verify the expected outcome, and log the result. Across 1,400 test cases at 4 minutes each, the raw execution time alone was over 93 hours of QA effort per cycle. With overlap, parallelism, and the inevitable defect investigation work that surfaced during testing, the actual elapsed UAT cycle was averaging 14 working days.
The 14-day cycle was the binding constraint on release cadence. The firm wanted to move to a fortnightly release cycle to reduce the risk window between feature development and production, but with UAT consuming 14 working days of each cycle, the maths did not allow it. The QA director had run the analysis twice in the previous year and concluded that fortnightly releases would require either a 50% increase in QA headcount (a roughly ?430,000 annual cost increase) or a structural change in how UAT was executed.
The defect-detection profile added the second pressure. The QA director's analysis of production incidents over the previous twelve months showed that approximately 38% of defects that reached production were defects that the existing scripted UAT process would not have caught regardless of cycle time, because they were edge cases, race conditions, or interaction effects between modules that scripted testing was not designed to expose. The QA team's most experienced testers had repeatedly raised this in retrospectives but the team simply did not have the time to do meaningful exploratory or risk-based testing because the scripted regression cycle consumed almost their entire bandwidth.
Softomate proposed adoption of its Testomate platform, an AI-augmented test automation framework specifically designed for financial services platforms where regulatory documentation requirements add overhead to automated testing tooling. Testomate combines a Playwright-based browser automation engine with an LLM-driven test interpretation layer that allows test cases to be expressed in structured natural language rather than code, while still producing reliable automation outcomes that satisfy audit requirements.
The discovery phase mapped the firm's existing 1,400 test cases by complexity and automation suitability. Approximately 1,180 of the cases were straightforward scripted flows (login, complete a form, verify an outcome) that were natural candidates for browser-driven automation. The remaining 220 cases involved either external system integration that required specific test environment setup, or visual verification that required human judgment, and were retained as manual cases.
The Testomate platform implementation involved three workstreams running in parallel over a 14-week engagement. The first was test-case migration: converting the 1,180 automation-suitable scripted cases from their existing format (a combination of Word documents, Excel sheets, and a legacy test management tool) into Testomate's structured natural-language format. Softomate's team led the first 200 cases as a worked example for the QA team, who then took over the bulk of the migration with Softomate review and refinement.
The second workstream was test environment configuration. Testomate needed reliable access to a representative test environment with realistic test data that could be reset to known state between test runs. The firm's existing test environment had been built incrementally over years and had several known issues around data consistency. Softomate worked with the firm's infrastructure team to rebuild the test environment with infrastructure-as-code, with database state reset built into the test orchestration layer.
The third workstream was the integration between Testomate and the firm's existing release management toolchain. Test results from Testomate runs needed to flow into the firm's existing release gate dashboards in a format that satisfied the risk-and-compliance function's audit requirements. Softomate built a custom adapter that produced the firm's required reporting format directly from Testomate's structured test results, eliminating the manual reporting step that had previously consumed significant QA time at the end of each cycle.
Full UAT cycle time fell from 14 working days to 3 working days, an 11-day compression. The 1,180 automated test cases executed in approximately 6 hours of unattended wall-clock time, with defect investigation and the 220 retained manual cases consuming the remainder of the 3-day cycle. The QA team's calendar moved from being almost entirely consumed by scripted execution to having significant capacity for exploratory and risk-based testing.
The fortnightly release cadence the QA director had wanted became feasible within three months of Testomate launch. The firm moved to fortnightly releases starting in the fourth month post-launch, with no increase in QA headcount and no degradation in defect-detection quality.
The defect-detection profile improved measurably. Production defect rate per release fell by approximately 37% in the first six months post-launch, despite the doubled release cadence. The QA director attributed the improvement primarily to the team's newly available time for exploratory and risk-based testing, which surfaced the kinds of edge cases that scripted testing had structurally been unable to catch. The firm's QA function transitioned from being primarily a scripted-execution function to being primarily a quality-engineering function.
The regression run time reduction was the most operationally visible change. Specific regression suites that had previously taken multiple hours to execute manually now ran in minutes via Testomate. The team began running targeted regression suites in response to specific code changes during development rather than only during the formal UAT cycle, which surfaced defects significantly earlier in the development cycle and reduced the cost of fixing them.
The audit-trail benefit was the outcome the risk-and-compliance function valued most. Every Testomate test run produced a complete structured evidence package suitable for FCA audit purposes, including the specific test cases executed, the inputs used, the actual outputs observed, and the pass-or-fail outcome. Producing this evidence had previously required manual gathering at the end of each release cycle; with Testomate, it was a byproduct of the test execution itself.
The avoided headcount cost was the clearest financial benefit. The firm had been on the cusp of approving a 50% expansion of the QA function to handle the move to fortnightly releases; Testomate made that hire unnecessary, representing approximately ?430,000 of annual avoided cost. Softomate's engagement cost was recovered within 5 months of go-live.
The firm has since extended Testomate to cover the testing of a new mobile-app channel that launched in the following quarter, and has begun discussions with Softomate about extending Testomate into security regression testing for the platform's authentication and authorisation flows.
Related service:Testomate and Automation Test Engineering London. Further reading:Agentic AI Workflows UK Companies and Agile Software Development Lifecycle.
Anonymised client engagement. Identifying details modified for confidentiality. Outcome ranges reflect typical results from similar projects.
Names withheld to preserve confidentiality.
Names withheld to preserve confidentiality.
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