FinSight: Towards Real-World Financial Deep Research

Jiajie Jin, Yuyao Zhang, Yimeng Xu, Hongjin Qian, Yutao Zhu, Zhicheng Dou


Abstract
Professional financial reports serve as the cornerstone of investment decisions, demanding deep reasoning and multimodal synthesis. While recent deep research systems excel in open-domain search, they struggle with financial reporting, specifically in handling financial data, ensuring analytical depth, and integrating professional visualizations. To address this, we introduce FinSight , the first multi-agent framework for automate end-to-end professional, multimodal financial report. At its core, we propose the Code Agent with Variable Memory architecture, which unifies data, tools, and agents into a programmable variable space, enabling flexible data manipulation and reasoning through executable code. To guarantee report quality, FinSight incorporates a Two-Stage Writing Framework with Generative Retrieval. This mechanism first distills raw data into structured Chain-of-Analysis segments, and then progressively synthesizes them into a coherent, citation-aware, and multimodal narrative. Additionally, an Iterative Vision-Enhanced Mechanism leverages visual feedback to refine code-generated charts to expert standards. Experiments on company and industry-level tasks demonstrate that FinSight significantly outperforms leading deep research systems in factual accuracy, analytical depth, and presentation quality, demonstrating a clear path toward generating professional financial reports. Our code is available at https://anonymous.4open.science/r/FinSight-5841.
Anthology ID:
2026.acl-long.265
Volume:
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2026
Address:
San Diego, California, United States
Editors:
Maria Liakata, Viviane P. Moreira, Jiajun Zhang, David Jurgens
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5868–5894
Language:
URL:
https://preview.aclanthology.org/ingest-acl/2026.acl-long.265/
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Cite (ACL):
Jiajie Jin, Yuyao Zhang, Yimeng Xu, Hongjin Qian, Yutao Zhu, and Zhicheng Dou. 2026. FinSight: Towards Real-World Financial Deep Research. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5868–5894, San Diego, California, United States. Association for Computational Linguistics.
Cite (Informal):
FinSight: Towards Real-World Financial Deep Research (Jin et al., ACL 2026)
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https://preview.aclanthology.org/ingest-acl/2026.acl-long.265.pdf
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