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arXiv · 2509.17395

FinDebate: Multi-Agent Collaborative Intelligence for Financial Analysis

Tianshi Cai·Guanxu Li·Nijia Han·Ce Huang·Zimu Wang·Changyu Zeng·Yuqi Wang·Jingshi Zhou·Haiyang Zhang·Qi Chen·Yushan Pan·Shuihua Wang·Wei Wang
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Abstract

We introduce FinDebate, a multi-agent framework for financial analysis, integrating collaborative debate with domain-specific Retrieval-Augmented Generation (RAG). Five specialized agents, covering earnings, market, sentiment, valuation, and risk, run in parallel to synthesize evidence into multi-dimensional insights. To mitigate overconfidence and improve reliability, we introduce a safe debate protocol that enables agents to challenge and refine initial conclusions while preserving coherent recommendations. Experimental results, based on both LLM-based and human evaluations, demonstrate the framework's efficacy in producing high-quality analysis with calibrated confidence levels and actionable investment strategies across multiple time horizons.

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Tianshi Cai, Guanxu Li, Nijia Han, Ce Huang, Zimu Wang, Changyu Zeng, Yuqi Wang, Jingshi Zhou, Haiyang Zhang, Qi Chen, Yushan Pan, Shuihua Wang, Wei Wang. 2025-09-22. FinDebate: Multi-Agent Collaborative Intelligence for Financial Analysis. https://arxiv.org/abs/2509.17395

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