Normalized claim
Accuracy: 98%
Achieved 98% accuracy in document extraction and policy validation.
Zurich Insurance Group in Germany significantly improved property claims settlement by adopting Azure ML to automate customer information extraction, risk analysis, and policy validation with 98% accuracy. The solution includes an MLOps platform and Explainable AI, streamlining the claims process from days to hours. Azure ML processes customer data and documents, automates extraction from car documents and forms, analyzes policy and risk data, and delivers explainable outputs to improve human understanding. The project, completed with support from Saxon AI, focuses on regulatory compliance and better decision-making. Benefits include much faster claims turnaround, lower operational costs, and improved customer experience.
Normalized claim
Accuracy: 98%
Achieved 98% accuracy in document extraction and policy validation.
Benefits include much faster claims turnaround, lower operational costs, and improved customer experience
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The same organization appears in newer AI deployment evidence.
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