Case Studies

Independent QA validation for a leading insurance firm

Client

The largest non-bank private-sector life insurer in India

Application

Life Asia Application, Customer facing Web Portals

Team Size

3 Manual Resources,2 Automation Resources

Problem Statement

UAT timelines were never met resulting in delayed product launch due to absence of clear processes, tasks, responsibilities and priority definition

Challenges

  • Miss-management of test artefacts with absence of mapping between policies and corresponding test cases.
  • Assignment of multiple ad hoc tasks to the QA resources with no prioritization basis business priorities.
  • Inadequate time and effort spent on test preparation and test case creation activities
  • Unplanned and unmanaged testing resulted in lengthy UAT testing phases with creation and execution being performed simultaneously.
  • More often than not, product launch of the product got delayed beyond IRDA guidelines

Industry

Insurance

Tech Stack

Web application & Mobile App

Resource Distribution

Onsite

What we did

  • Analyzed the current state and suggested best practices of policy mapping with test cases before initiation of UAT testing
  • Introduced automation testing over & above the traditional manual testing
  • Created re-usable scripts which helped in quick re-use and regression testing, even for new policies, before every production deployment

Duration

Ongoing

Types of Validation

  • Setup of Mature QA Processes
  • Manual Validation
  • Test Automation

Recommendations

  • Creating of more re-usable test cases and tagging of these cases. More coverage through test automation

Outcome

  • Faster UAT Testing closure before the cut of time lines ensured on-time launch
  • Test bed creation before UAT start date which helped the testing team evolve better with time resulting in 40% shorter UAT cycles
  • 30% reduction of efforts due to policy mapping done before UAT start
  • Automated scripts helped in increase in early closures of UAT and reducing the overall effort and cost
  • Better quality testing is done due to regression test scripts created to be run before production deployment