Zurich Insurance Group automates claims with Azure ML and Explainable AI
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.
- Organization
- Zurich Insurance Group
- Industry
- Insurance
- Location
- Germany
- Published
- November 2021
Reported outcomes
98%
accuracyQuality & accuracy
Strategic outcomes
Catalog median for quality & accuracy deployments: +90% across 282 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 2 of 2
- 1Automated Claims Processing with Azure ML
- 2Document Extraction for Property Insurance
- Long settlement times for property claims negatively impacted customer experience.
- Manual extraction and processing of documents was inefficient and error-prone.
- Need for more accurate and compliant risk analysis and policy review.
- Difficulty scaling claims processing during peak demand.
- Reduced claims settlement from days to hours.
- Achieved 98% accuracy in document extraction and policy validation.
- Improved operational efficiency and customer satisfaction.
- Strengthened compliance with automated, auditable AI.
Implementation partners1
Sources & evidence1
The same organization appears in newer AI deployment evidence.
- Same organization re-documented as recently as 2025.
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