Automating claims processing at nib

nib is a health and medical insurance provider in Australia with approximately 1,500 employees and over 1.6 million members

Key results delivered


~$1M savings in manual handling costs over 12 months


90% accuracy for key fields from medical receipts


50% touchless claims


25% further reduction in manual handling time on non-automated claims

Business challenge

  • The nib mobile app allows members to easily make claims by submitting a photo of a receipt from their mobile device
  • Relevant information from submitted receipt photos was manually entered into the nib claims system
  • Significant time was spent on manual data entry on top of assessing the claim. As the app gained popularity nib realised this approach was not scalable

Success critera

  • Integrate an automated solution to assist nib employees with the manual entry of key fields from the receipts
  • Seamlessly fit into nib’s current business processes and technology
  • Sensitive receipt data must remain within nib’s secure AWS environment at all times
  • Reduce the turnaround time for each member by enabling the claims team to process assessments faster


  • Amazon Textract was selected for its accuracy and ability to determine the document structure while extracting text. Geometric de-skewing and key-value pair recognition were particularly effective in handling claims receipts
  • Eliiza created a image processing pipeline to:
    • Find and extract relevant fields from receipt photographs
    • Analyse the extracted text and identify information required for the claims process
    • Pre-populate the claims processing system,
      ready for employee review
    • Provide nib with automated monitoring to validate
      accuracy of the solution

nib customer takes photo of receipt

Photo is uploaded to nib’s AWS environment

Textract retrieves the relevant fields from the photo

nib team review and process the claim 

nib customer receives claim amount  


  • Eliiza created an end-to-end solution that integrated with the existing claims system
  • 88% – 95% accuracy for extraction and classification of key fields such as date, amount and type of claim
  • The claims team can focus on assessment rather than data entry by reviewing the receipt fields directly within the claims system
  • Notable decrease in time taken to assess and complete claims due to less manual processing
  • nib saved approx. $1 million AUD in automating their document processing

Contact Us

We’re always keen to start conversations on how AI can help solve real-world problems, or opportunities for technology to impact people in a positive way.

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