NLP — Transformer-Based Policy & Regulatory Intelligence
A transformer-based document intelligence stack that converts unstructured policy contracts and regulatory filings into a structured, searchable clause library — enabling underwriters and compliance analysts to query across large document portfolios.
BERT + GPT fine-tuned
Models
NER · clause extraction
Tasks
Elasticsearch
Index
Problem & use case
Underwriters and compliance teams manually reviewed policy wordings and regulatory filings to identify coverage gaps, endorsement conflicts, and regulatory obligations — slow and inconsistent at portfolio scale.
Solution & engineering approach
Domain fine-tuned BERT for token-level clause extraction combined with GPT-based clause normalization, indexed in Elasticsearch to support structured search and analytical querying across policy and regulatory document libraries.
Architecture & data flow
- 01
OCR + layout parsing of policy / claim PDFs
- 02
Domain fine-tuned BERT extracts entities and clauses
- 03
GPT normalizes clauses to canonical schema
- 04
Index structured output in Elasticsearch
- 05
Expose query API for downstream analytics
Technology stack
Implementation status
Implemented — domain fine-tuned transformer pipeline with Elasticsearch query API