Normalized claim
Member queries handled: 4,000,000 queries increase
“has handled over four-million-member queries”
nib Group uses Amazon Bedrock and Amazon Textract to automate health insurance service and claims workflows
Use case typeCustomer service automationUpdated Mar 18, 2025
nib Group is an Australian health insurer that uses Amazon Bedrock across customer service, claims processing, and personalized member communications. The company also combines Amazon Bedrock with Amazon Textract to automate reading and processing of member claims and invoices. Its AI assistant supports voice and text interactions and helps reduce manual support and post-call work.
Reported outcomes
−60%
chat support interactions reducedOther quantified impact
4,000,000 queriesmember queries handled−15%voice call support reduced−20%post-call work reduced−8%average call time reduced4,000,000 invoicesanniversary invoice volume processed
Strategic outcomes
Customer experience & trustImproved personalization and faster resolution for membersOther strategic outcomeFreed agents to focus on more complex and empathetic workCost efficiencyAutomated claims and invoice processingCustomer experience & trustCreated personalized travel insurance offers
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Chat support interactions reduced: 60% decrease
“has lowered chat-based interaction support by 60%”
Normalized claim
Voice call support reduced: 15% decrease
“voice call support by 15%”
Normalized claim
Post-call work reduced: 20% decrease
“reducing post-call work by up to 20%”
Normalized claim
Average call time reduced: 8% decrease
“resulting in an 8% reduction in average call times”
Normalized claim
Anniversary invoice volume processed: 4,000,000 invoices increase
“process over four million invoices annually”
Normalized claim
Savings: 22,000,000 USD decrease
“delivering more than $22 million in savings”
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- nib Group
- Provider
- AWS
- Maturity
- Scaled Production
- Linked source
- AWS Press Release
Improve call-center productivity and customer experience at scale
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Customer service automation
- 2Claims automation
- 3Document processing automation
- Reduce manual customer support and post-call work.
- Automate processing of member claims and invoices.
- Improve call-center productivity and customer experience at scale.
- nib uses Amazon Bedrock to augment and automate customer-facing interactions with generative AI.
- The company generates and summarizes notes from customer chats and calls, and it summarizes knowledge articles to improve responses in the contact center.
- nib combines Amazon Bedrock with Amazon Textract to automatically read and process documents for claims and invoices.
- The solution is integrated with Amazon Connect and is built on Claude 3.5 Sonnet for most generative AI workloads.
- nib's AI assistant has handled over four million member queries.
- Chat-based support interactions were reduced by 60%.
- Voice call support was reduced by 15%.
- Post-call work was reduced by up to 20%.
- Average call times were reduced by 8%.
- The company reports more than $22 million in savings.
- nib processes over four million invoices annually via the automation.
Architecture
nib uses Amazon Bedrock as the generative AI layer for customer service and personalization, with Amazon Connect for contact center integration. The assistant handles voice and text interactions, produces call summaries and notes, and summarizes knowledge articles. Amazon Textract is used to read and process invoice and claims documents, supporting high-volume automation.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
Type: Press ReleasePublished: Mar 18, 2025Publisher: AWSEvidence: VendorConfidence: Medium
AI-generated summary. Verify important details with the linked sources before relying on this case.
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