case study

Automating Medical Claims Processing for a Leading Broker

Insurance Dociphi

Business Impacts

90%+

Classification and Extraction Accuracy including handwritten documents

30%

Effort Reduction

49%

Cost Saving

1.5x

Quicker Claims Resolution

Customer Key Facts

  • Region : Europe
  • Industry : Commercial Insurance Broker

Overview

The client, one of the leading insurance brokers in the world, wanted to automate the medical claims process workflow with an end-to-end intelligent document processing (IDP) solution which can process medical claims by accurately extracting relevant data from a wide range of doument formats and comparing data across medical records, invoices and internal systems.

Challenges

  • The manual reviews are slow and inefficient due to diverse document formats, necessitating system data comparison, Macro Guarantee and ICD mapping
  • Absence of a user-freindly tool for reviewers to compare invoices and medical records and flag discrepencies in key details such as user names, invoice amounts, medical center
  • Manually going through the documents of varying template and format to find the required data, makes this process is extremely error-prone
  • High operational cost and lowered customer satisfaction

Solution

Dociphi, Quantiphi’s AI-powered intelligent document processing platform, transformed claims processing, by eliminating the need for the reviewer to manually process each and every claim document

  • Dociphi seamlessly ingested and classified invoices and medical records, used proprietary best-in-class machine learning models to extract information from a wide range of document formats and templates, even from handwritten documents
  • Dociphi's proprietory models intelligently mapped the Macro Guarantees and ICD codes to each claim submission based on extracted data from the documents such as diagnosis, medical test, body part, etc
  • With Dociphi's smart comparison screens to compare the extracted data from docs with system data and highlight all the discrepancies, reviewers can close claims faster.

Results

  • Creation of a comprehensive AI-driven claims processing workflow, that supports data extraction from complex tables & hierarchical data
  • ML Powered ICD and Macro Guarantee mapping
  • Improved claims handling efficiency for accelerated claims turnaround time
  • Reduction of manual efforts for claim adjusters thereby reducing operational cost

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