Transforming Quality Engineering for a Modern Lending Platform: How Testrig Combined Playwright, AI & Automation to Accelerate Releases

• Establish comprehensive test coverage across all core loan origination and management workflows. 

• Achieve full CRUD (Create, Read, Update, Delete) operation coverage across all fields of the loan application form, ensuring data integrity at every interaction point. 

• Validate the reliability and accuracy of all REST APIs powering the lending platform. 

• Detect UI regressions and visual inconsistencies across dashboards, forms, and reports. 

• Support frequent product releases with a scalable, automated regression suite. 

• Reduce reliance on manual testing and accelerate the QA feedback loop for the development team. 

• Enable parallel execution of test suites to significantly reduce regression time and support faster release cycles. 

• Maintain long-running test scripts for complex, multi-step loan form flows without flakiness or performance degradation. 

• Ensure consistent behaviour across browsers and environments for all end users. 

• The client had an existing Cypress-based automation suite, but Cypress struggled to maintain long-running, complex test flows across the loan form — deep multi-step scenarios became brittle and increasingly difficult to manage at scale. 

• Cypress lacked reliable native parallel execution support, which significantly slowed down regression cycles as the test suite grew alongside the platform. 

• Complex financial workflows spanning multiple modules — application, underwriting, document management, and reporting — required thorough end-to-end test coverage. 

• Data accuracy was critical — any discrepancies in loan calculations, status updates, or borrower records could carry significant financial and compliance implications. 

• Validating CRUD operations across every field of the loan form demanded meticulous data-driven testing to ensure no field-level behaviour was missed or broken across releases. 

• Frequent feature deployments introduced risk of regression across tightly coupled lending workflows. 

• Implementing a gated and dependent CI/CD pipeline — where downstream stages execute only upon upstream success — while maintaining a persistent historical trend of test results for every build, added significant pipeline design complexity. 

• API layer complexity involved numerous interconnected endpoints for borrower data, loan status, document uploads, and third-party integrations. 

• Visual integrity of forms, dashboards, and document views needed consistent validation to maintain a professional user experience for lenders. 

• The client approached Testrig with a clear need — their existing Cypress suite was failing to handle the scale and complexity of loan form flows. Testrig recommended and led a full migration from Cypress to Playwright with TypeScript, providing a more robust foundation for long-running tests. 

• Rebuilt the entire automation framework from the ground up using Playwright’s Page Object Model (POM) architecture, ensuring modularity, reusability, and long-term maintainability. 

• Achieved comprehensive CRUD coverage across all 4,800 loan form fields — validating create, read, update, and delete operations through data-driven test scripts at a scale previously unachievable in Cypress. 

• Leveraged Playwright’s native parallel execution to run multiple test suites simultaneously, dramatically reducing overall regression time and unblocking the team’s release cadence. 

• Eliminated hardcoding by introducing parameterization and reusable TypeScript utilities, making long-running test flows stable and easy to maintain. 

• Organised test cases into smoke and regression suites for streamlined execution and stakeholder review. 

• Built a structured API test suite in Postman covering all critical endpoints — borrower data, loan origination, document management, and status updates. 

• Implemented request chaining and dynamic variables to simulate real-world multi-step lending transactions. 

• Validated response schemas, status codes, error handling, and data accuracy across all API contracts. 

• Created reusable Postman collections organised by module for easy maintenance and team collaboration. 

• Introduced visual regression testing, capturing and comparing screenshots to quickly detect UI discrepancies. 

• Focused on validating loan dashboards, application forms, and document views, ensuring accuracy in visual presentation of lending data. 

• Reduced reliance on manual UI checks and accelerated release validation. 

• Designed and implemented a gated, dependent Jenkins pipeline where each stage — API tests, UI regression, and visual checks — is conditionally triggered only upon successful completion of its upstream stage, preventing flawed builds from propagating. 

• Configured persistent build history retention in Jenkins, enabling the team to track quality trends, compare pass/fail rates across builds, and identify flaky tests or recurring failure patterns. 

• Integrated Allure Reports to generate interactive HTML reports with step-level results, failure screenshots, and historical trend graphs visible directly within the Jenkins dashboard. 

• Deployed the entire pipeline on AWS remote machine infrastructure, ensuring scalable, environment-consistent test execution independent of local developer machines. 

• Enabled real-time visibility into test health for QA, Dev, and Product stakeholders — reducing the feedback loop from days to hours. 

• Established a structured smoke suite for rapid post-deployment validation and a full regression suite as a pre-release quality gate. 

• Integrated ClickUp for defect lifecycle management — every test failure maps to a ClickUp task with severity, steps to reproduce, and build reference, keeping Dev and QA teams aligned. 

• Continuously expanded automation coverage as new features were added, keeping manual testing effort minimal. 

• Maintained a defect reporting process with clear severity classification to prioritise critical financial workflow bugs for immediate resolution. 

• Introduced Claude Code as a development aid for writing and maintaining test code, including ongoing improvements to the Playwright automation framework (page objects, utilities, and test scripts). 

• Built an integration with the Jenkins API to programmatically fetch build and Allure report data after each pipeline run. 

• Used Claude to review fetched report data — surfacing failure patterns, flaky tests, and regression trends without requiring a person to manually parse Allure output first. 

• Automated posting of review findings into ClickUp via the ClickUp MCP, driven through Claude Code, so defect tickets are created or updated directly from the reviewed report data rather than through manual entry. 

• Reduces the manual step between “build finishes” and “defect is logged with context,” tightening the feedback loop described in Phase 4. 

• Playwright & TypeScript — Type-safe end-to-end web UI automation framework for loan workflows and cross-browser testing. 

• Postman — API testing, request chaining, and automated API contract validation across all lending endpoints. 

• Jenkins — Gated, dependent CI/CD pipeline with stage-level execution control and persistent build history tracking. 

• Allure Reports — Rich, interactive test reporting with step-level visibility, failure screenshots/videos, and historical trend graphs. 

• AWS (Remote Machine) — Cloud-hosted remote execution infrastructure for scalable, environment-consistent test runs. 

• ClickUp — Project and defect tracking — linking test failures to actionable work items for the development team. 

• Visual Testing Tools — Automated screenshot capture and comparison for dashboards, forms, and document views. 

• Git — Version control for test scripts, suites, and pipeline configuration management. 

• Claude and claude-code – Used for writing the playwright tests and also review and analyse the allure report  

• Clickup MCP – Used for Reporting and accessing the bugs tickets from click up  

• Complete CRUD coverage: All loan form fields validated across create, read, update, and delete operations — ensuring zero data integrity gaps across releases. 

• Reliable API coverage: All critical lending APIs validated for accuracy, contract compliance, and edge case handling across every release. 

• Faster release cycles: Gated Jenkins pipeline with smoke and regression suite separation significantly shortened feedback loops. 

• Visual consistency: Automated visual regression testing eliminated UI-related defects reaching production on dashboards and loan forms. 

• Build trend visibility: Persistent build history in Jenkins with Allure trend graphs gave teams full visibility into quality patterns across every deployment. 

• Early defect detection: Regression issues were identified within hours of a build, lowering production bug rates. 

• Aligned Dev & QA teams: ClickUp integration linked every failing test to a tracked work item, keeping both teams in sync throughout the release cycle. 

• Future-ready framework: Modular Playwright + TypeScript architecture allows easy expansion as the platform adds new modules and features, ensuring long-term QA scalability. 

Testrig’s end-to-end QA services empowered the client to ship confidently — ensuring every loan workflow, API, and user interface met the high standards demanded by financial professionals, backed by a robust gated pipeline and full build transparency.