Workshop: Leveraging Large Language Models for Intelligent Claim Handling: A Hands-On Industry Case Study
This workshop provides a hands-on exploration of applying Large Language Models (LLMs) to automate and enhance insurance claim handling processes. Participants will learn different approaches to build intelligent claim processing systems using state-of-the-art NLP techniques.
- Basic understanding of Python programming
- Familiarity with machine learning concepts
- Basic knowledge of natural language processing (NLP)
- Overview of insurance claim processing
- Problem statement and challenges
- Dataset introduction and exploration
- Understanding RAG architecture
- Building a RAG pipeline for claim coverage verification
- Implementation considerations and results analysis
- Introduction to graph-based approaches
- Implementation of graph retrieval system
- Performance analysis and considerations
- Fundamentals of fine-tuning LLMs
- Implementation and best practices
- Results evaluation and comparison
- Comparative analysis of approaches
- Best practices and lessons learned
- Future directions and improvements