Fin-Rag A Rag System for Financial Documents
Fin-RAG (Financial Retrieval-Augmented Generation) is an AI-powered chatbot system designed to simplify and accelerate financial data retrieval. Built on Retrieval-Augmented Generation (RAG), it enables natural language querying of financial documents, delivering accurate and context-aware responses in real time. The system supports both text-based and image-based documents, utilizing advanced NLP and image recognition capabilities. Users can extract key insights from balance sheets, profit and loss statements, and scanned invoices effortlessly. Fin-RAG leverages domain-specific embeddings via Hugging Face’s Inference API for precise and relevant search results. Key features include real-time insights, automated reporting, semantic search, and multimodal document analysis. Scalable and compliant, Fin-RAG improves financial decision-making efficiency. It is ideal for auditing, corporate finance, and strategic analysis.
Authors
- K. E. Kannammal
- Mr. Anirudh R K
- Kuzhali Tamizhiniyal P
- G Ganishkar
- C Adrinath
Publication Details
- Published
- 2025-04-30
- DOI
- https://doi.org/10.38124/ijisrt/25apr1147
- Citations
- 4
- Primary Topic
- FinTech, Crowdfunding, Digital Finance
- Type
- article
- Field-Weighted Citation Impact
- 9.14