What challenges did global insurers face before AI implementation?

Claims process was slow and inefficient. Decisions were often not personalized, impacting customer retention. Regulatory compliance required greater transparency and traceability. Claims handlers spent significant time on manual analysis of policy documents.

What was the impact of the AI solution?

Faster claims processing led to improved customer satisfaction and retention. Reduced operating costs due to process efficiency gains. Improved accuracy and less dispute in claims outcomes. Enhanced employee satisfaction through focus on higher-value tasks.

Source

MicrosoftProductionEvidence: Low40/100

Global Insurers Streamline Claims Handling with Advanced AI

Use case typeClaims automationUpdated Jun 13, 2026

Kainos collaborated with major global insurers to enhance the insurance claims process using Azure OpenAI. The solution integrates seamlessly with enterprise infrastructure and existing claims systems, providing a generative AI proof of value (POV) demonstrator. This deployment enables claims handlers to make quicker, more accurate, and personalized decisions, while supporting transparency and regulatory compliance. The approach incorporates inclusive and ethical AI principles, ensuring both operational efficiencies and customer-centric innovations. Over an 8-12 week engagement, internal teams gain the skills and agile methodology required for rapid value realization. The implementation has improved customer satisfaction, streamlined employee workflows, and provided a scalable foundation for further digital transformation within insurers.

Organization: global insurers
Industry: Insurance
Location: Global

Reported outcomes

Strategic outcomes

Customer experience & trustImproved customer satisfaction and retentionRisk & complianceStrengthened transparency and regulatory complianceCost efficiencyReduced operating costs through process efficiencyEmployee experienceStreamlined employee workflows

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: global insurers
Provider: Microsoft
Maturity: Production
Linked source: azuremarketplace.microsoft.com

The approach incorporates inclusive and ethical AI principles, ensuring both operational efficiencies and customer-centric innovations

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1Automated Insurance Claims Decision Support
2Policy Document Insight Extraction Using Generative AI

Claims process was slow and inefficient.
Decisions were often not personalized, impacting customer retention.
Regulatory compliance required greater transparency and traceability.
Claims handlers spent significant time on manual analysis of policy documents.

Integrated Azure OpenAI to extract insights from policy documents.
Provided a generative AI demonstrator within enterprise infrastructure.
Enabled fast, accurate, and personalized claims decisions.
Used a secure, inclusive, and ethical AI design approach.

Technologies

Azure OpenAI

Faster claims processing led to improved customer satisfaction and retention.
Reduced operating costs due to process efficiency gains.
Improved accuracy and less dispute in claims outcomes.
Enhanced employee satisfaction through focus on higher-value tasks.

Architecture

Azure OpenAI is integrated with existing insurance claims systems within enterprise infrastructure, enabling policy document insights extraction that feeds into claims handling workflows. The design ensures regulatory compliance, security, and seamless operational workflows for claims handlers.

Implementation partners1

Kainos

Sources & evidence1

Evidence: Low40/100Evidence strength