📄 Claim Summarization AI

AI-powered summarization of insurance claim documents

Features ✨

• Single & Multi-Document Summarization
• AI-Powered Key Point Extraction
• 10,000+ Synthetic Claims Dataset
• Downloadable Reports (TXT/ZIP)

📌 Claim Summarization AI — Case Study

Problem

Insurance adjusters spend significant time reading long claim documents, leading to delays, inconsistent summaries, and operational inefficiencies.

Goal

Reduce adjuster review time and improve consistency by generating concise, structured summaries using LLMs.

My Role

Defined requirements, designed the summarization workflow, evaluated LLM outputs, and aligned the solution with responsible AI and risk considerations.

Approach

• Identified key summary components (incident, parties, damages, next steps).
• Designed prompt templates and evaluation criteria.
• Tested multiple LLMs for accuracy, hallucination rate, and latency.
• Integrated feedback loops for adjusters to refine outputs.

AI/ML Considerations

• Hallucination mitigation through structured prompts.
• Evaluation using ROUGE and human review.
• Privacy and PII handling aligned with governance standards.

Outcome

Simulated 40–60% reduction in review time and improved consistency across adjusters.

What I’d improve next

Add RAG with policy documents and integrate into a claims workflow UI