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In digital property and casualty insurance platforms, end-to-end test automation has assumed a strategic role as customer journeys, broker interactions, underwriting workflows, policy servicing, billing touchpoints, and document delivery increasingly depend on distributed web-based services. Portal defects in such environments can propagate far beyond the user interface, affecting rating accuracy, transaction integrity, compliance artifacts, and customer experience. This review examines academic literature relevant to the design of an end-to-end test automation framework for digital P&C insurance web portals. Key topics are web application testing, model-based testing, regression optimization, service virtualization, continuous integration and delivery, process-conscious quality assurance, test architecture maintainability, and the implications of insurance digitalization to test architecture. The literature suggests that durable automation depends on layered design rather than script accumulation; stable abstractions, domain-aware scenario modeling, risk-based prioritization, robust data management, and tight feedback from test execution are all essential. There are still gaps in insurance-specific empirical data, cross-channel lifecycle coverage, explainable risk-based orchestration, and frameworks to evaluate and relate automation metrics to regulated business results. The field is important because portal quality increasingly shapes operational trust, release velocity, and competitive responsiveness within digital insurance ecosystems.
Keywords:
digital insurance; end-to-end testing; property and casualty insurance; test automation; web portals
Cite Article:
"End-to-End Test Automation Framework for Web Portals in Digital P&C Insurance Platforms ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a510-a525, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605063.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator