FIN-SIGHT AI: A Hybrid Multi-Agent Generative AI Framework for Automated Financial Report Analysis

FIN-SIGHT AI presents a hybrid multi-agent Generative AI framework for financial report analysis. The framework combines Retrieval-Augmented Generation (RAG), hybrid retrieval, and LangGraph-based agent orchestration to support financial document understanding and analytical workflows. The proposed architecture integrates FAISS-based vector retrieval and BM25-based keyword retrieval with specialized agents for financial research, analysis, ratio evaluation, risk assessment, validation, and report generation. This work explores the application of Generative AI and multi-agent systems to financial document analysis and structured financial insights.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-07
DOI
https://doi.org/10.5281/zenodo.24031954
Primary Topic
Topic Modeling
Type
preprint
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preprint

FIN-SIGHT AI: A Hybrid Multi-Agent Generative AI Framework for Automated Financial Report Analysis

PRIYADHARSHINI S, Sridevi S, Swathi G, Shree Abiraami M
2 links
Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
preprint

FIN-SIGHT AI: A Hybrid Multi-Agent Generative AI Framework for Automated Financial Report Analysis

PRIYADHARSHINI S, Sridevi S, Swathi G, Shree Abiraami M
preprint en

Abstract

FIN-SIGHT AI presents a hybrid multi-agent Generative AI framework for financial report analysis. The framework combines Retrieval-Augmented Generation (RAG), hybrid retrieval, and LangGraph-based agent orchestration to support financial document understanding and analytical workflows. The proposed architecture integrates FAISS-based vector retrieval and BM25-based keyword retrieval with specialized agents for financial research, analysis, ratio evaluation, risk assessment, validation, and report generation. This work explores the application of Generative AI and multi-agent systems to financial document analysis and structured financial insights.

Zenodo (CERN European Organization for Nuclear Research)
Topic Modeling
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