Technical Report for Financial Deep Document (FinDDR) Competition @ ACM ICAIF 2025

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Fengbin Zhu, Chao Wang, Chang Liu, Shuo Zhang, Ke-Wei Huang, Huanbo Luan, Tat-Seng Chua

Published: 09 Jan 2026, Last Modified: 14 Jan 2026CrossrefEveryoneRevisionsCC BY-SA 4.0
Abstract: Financial analysis is crucial for informed decision-making among stakeholders of public companies. Yet extracting insight from lengthy and complex annual reports remains a significant challenge. Mirroring the proven capabilities of Deep Research Agents, we propose the Financial Deep Document Research (FinDDR) Challenge to motivate the development of AI agents that adopt methodologies similar to Deep Research. The FinDDR Challenge introduces a richly structured, industry-diverse dataset and requires participants to generate comprehensive, sectioned research reports. This is accomplished through a hierarchical, stepwise reasoning framework that closely emulates the analytical methodologies employed by professional financial analysts. In conclusion, the FinDDR Challenge seeks to establish new benchmarks for complex document-based deep research in financial AI applications, fostering progress and collaboration across both academic and industry communities. The benchmark is publicly available at https://OpenFinArena.com/.