Revolutionizing Medical Insurance Analysis with Agentic claim estimation

Overview

Scaleport AI partnered with a leading travel insurance provider processing hundreds of claims monthly. The objective was to automate the manual process of estimating claim amounts from complex medical reports submitted worldwide. These reports, often in varied formats—such as PDFs, scanned images, and handwritten documents—presented challenges for traditional OCR systems. The provider sought a scalable agentic solution to process documents, extract medical case data, and estimate claim amounts in real time.

Challenges

The provider faced several hurdles:

• Unstructured Document Formats: Claims were submitted in diverse formats, requiring significant manual effort for information extraction.
• Accuracy of OCR Processing: Precise and contextually relevant data extraction from complex documents was crucial to maintaining data integrity.
• Scalability and Automation: The growing volume of claims necessitated a robust, scalable solution capable of handling diverse data sources efficiently.

The provider needed an end-to-end system that integrated advanced OCR capabilities with AI-driven analysis.

Solution: AI-Powered Insurance Case Analysis Agent

Scaleport AI deployed an advanced Insurance Case Analysis Agent, leveraging LlamaIndex and LlamaParse to address the provider's unique needs.

Role of LlamaParse

• Advanced OCR Technology: Extracted data from various document types, including handwritten notes, scanned PDFs, and diagrams, while preserving the formatting of critical elements like tables and figures.
• Contextual Data Extraction: Mapped extracted information to predefined fields, ensuring accurate representation of diagnoses, treatments, and other medical details, even from noisy or low-quality scans.
• Scalable Processing: Enabled real-time, high-volume document parsing with asynchronous processing for urgent claims.

Features of the Bot

LlamaIndex was selected for its robust, production-ready abstractions, which massively streamlined the development of the outlined features:

• Exclusion Checking: Automated validation against predefined medical exclusion criteria.
• Adequacy Assessment: AI-driven evaluation of diagnoses and treatments for sufficiency.
• Similar Case Search: Leveraged vector search to identify comparable cases globally and locally for informed decision-making.
• Hybrid Search Functionality: Provided treatment price estimates by specific locations using hybrid search.
• Price Estimation: Predicted claim amounts using historical data for enhanced accuracy.

Results and Impact

The Insurance Case Analysis Bot, now in production, has transformed claims processing:

• Efficiency Gains: Reduced claim processing time from 20–40 minutes to just 10 minutes per claim, achieving a 50–75% improvement.
• Increased Capacity: Enabled the team to process twice as many claims without compromising accuracy.

Client Testimonial "The Insurance Copilot developed with Scaleport AI has significantly improved our claims processing speed and efficiency. We've reduced handling time by 50–75%, allowing us to process twice as many claims while maintaining high accuracy."

— Evgenii Fursov, CEO of Tripinsurance & Paramatrix

Conclusion

By partnering with Scaleport AI and integrating LlamaParse’s advanced OCR technology, the provider has set a new benchmark in medical insurance claims processing. The solution’s ability to extract, analyze, and generate actionable insights from unstructured data has streamlined operations, improved client satisfaction, and positioned the provider as an innovator in AI-powered insurance solutions.