Industry Solution
Banking
In banking there is no acceptable error rate. Money either moves correctly or it does not, and every transaction becomes a record someone may be asked to explain years later. That is why replacing a core system is rarely a coding problem. It is a matching problem: every interest calculation, every fee and every transfer has to give exactly the same result on the new platform as on the old one. Most teams still check that by hand, in spreadsheets, sprint after sprint. RabbitQA runs that matching autonomously, every scenario, every sprint, and keeps each result as a record you can explain years later.
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Key Features
The testing capabilities that matter most for Banking.
Core and channel banking coverage
End-to-end validation across core, internet, mobile and branch, including desktop and service-oriented architectures, with custom inspection for the interfaces standard automation cannot reach.
Parity you can prove
Legacy and new platform execute the same scenario set against the same data. Divergence arrives as a report before cutover, not as an incident after it.
Regression at release speed
Scenarios run in parallel across environments, with flaky failures separated out automatically, so the suite fits the window instead of setting it.
Evidence as a by product
Every requirement links to its test cases, every run to its result, every approval to a named person. The audit chain is produced as you work, not assembled before a review.
Human approval
Agents do the preparation. A product owner approves the requirement, a QA lead signs off the coverage, an engineer decides what a failure means. Nothing is promoted because a machine was confident.
Compliance coverage
Every requirement links to its test cases and every execution links to its result, producing an unbroken evidence chain for PSD2, PCI-DSS, GDPR and KVKK obligations. Reports export on demand, with the approver recorded at every step.
Common Use Cases
Where teams put RabbitQA to work in Banking.
Core migration parity
Prove every interest calculation, fee rule and transfer scenario produces the same result on the new platform as the old one, before cutover rather than after.
Payment and statement integrity
Keep EFT, standing order, card and statement flows correct and auditable across every release, including the thick-client screens browser tools cannot reach.
Channel consistency
Validate that internet, mobile and branch enforce the same rule set, in the same run, instead of three teams proving three versions of the truth.
Key Benefits
Measurable outcomes RabbitQA delivers for Banking teams.
No additional hardware or licence investment. Existing Selenium, Playwright and Cucumber assets keep running.
Audit evidence generated on demand, replacing 2-4 weeks of manual gathering before every review.
Internet, mobile and branch validated against the same rule set, in the same execution.
Weeks to days on core banking implementations.
Frequently Asked Questions
Common questions about RabbitQA for Banking.
Yes. AutoRunner supports desktop and service-oriented architectures with custom inspection for interfaces that resist standard automation. This is the part of a core banking estate that browser-only tools cannot reach, and it is usually where manual regression accumulates year after year.
By parallel run. The legacy platform and the new one execute the same scenario set against the same data, and every divergence is reported before cutover. Nothing is switched over on the assumption that parity holds, and the differences arrive as a list rather than as an incident.
Every requirement links to its generated test cases, every execution links to its result, and every approval is recorded against a named person with a timestamp. When a regulator asks whether a specific rule was tested on a specific release, the answer is one screen rather than two to four weeks of gathering.
No. RabbitQA orchestrates the frameworks you already run, including Selenium, Playwright, Appium, Cypress, Cucumber, Gauge and Robot Framework. Existing assets keep executing while RabbitQA adds requirement governance, generation, parallel orchestration and traceability on top of them.
Deployment options include SaaS, hybrid and full on-premise. On-premise deployments can run local models, so no data and no prompt leaves your infrastructure.
No. Agents do the preparation: reading specifications, generating cases, running suites, collecting evidence. A product owner still approves the requirement, a QA lead signs off the coverage and an engineer decides what a failure means. Teams typically redirect the recovered hours into exploratory testing and parity design.
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