The Hardest Document Extraction Problem in Insurance
8 hours ago
- #Insurance Technology
- #AI Extraction
- #Document Processing
- Loss runs are crucial yet challenging documents in insurance, requiring extraction of 30+ fields per claim from highly variable formats.
- Self-correcting AI agents, using validation tools and iterative loops, improved row count accuracy from 80% to 95%, outperforming prompt engineering.
- Key challenges include joining data across multiple tables, handling missing metadata, and interpreting ambiguous blank cells or summary rows.
- The system employs tools for extraction, visual inspection, and validation, allowing agents to debug outputs and verify against document totals.
- Evaluation emphasizes row count and financial accuracy, with rigorous frameworks to handle variations in claim alignment and formatting.