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[2602.22273] FIRE: A Comprehensive Benchmark for Financial Intelligence and Reasoning Evaluation
Summary
The FIRE benchmark evaluates financial intelligence and reasoning in LLMs through diverse theoretical and practical assessments, providing a comprehensive framework for future research.
Why It Matters
As financial applications of AI grow, establishing robust benchmarks like FIRE is crucial for assessing the capabilities of LLMs in real-world scenarios. This benchmark not only enhances understanding of LLM performance but also aids in developing more effective financial AI tools.
Key Takeaways
- FIRE benchmark assesses LLMs on theoretical financial knowledge and practical scenarios.
- Includes 3,000 questions covering various financial domains for comprehensive evaluation.
- Results highlight the capability boundaries of current LLMs in financial applications.
Computer Science > Artificial Intelligence arXiv:2602.22273 (cs) [Submitted on 25 Feb 2026] Title:FIRE: A Comprehensive Benchmark for Financial Intelligence and Reasoning Evaluation Authors:Xiyuan Zhang, Huihang Wu, Jiayu Guo, Zhenlin Zhang, Yiwei Zhang, Liangyu Huo, Xiaoxiao Ma, Jiansong Wan, Xuewei Jiao, Yi Jing, Jian Xie View a PDF of the paper titled FIRE: A Comprehensive Benchmark for Financial Intelligence and Reasoning Evaluation, by Xiyuan Zhang and 10 other authors View PDF HTML (experimental) Abstract:We introduce FIRE, a comprehensive benchmark designed to evaluate both the theoretical financial knowledge of LLMs and their ability to handle practical business scenarios. For theoretical assessment, we curate a diverse set of examination questions drawn from widely recognized financial qualification exams, enabling evaluation of LLMs deep understanding and application of financial knowledge. In addition, to assess the practical value of LLMs in real-world financial tasks, we propose a systematic evaluation matrix that categorizes complex financial domains and ensures coverage of essential subdomains and business activities. Based on this evaluation matrix, we collect 3,000 financial scenario questions, consisting of closed-form decision questions with reference answers and open-ended questions evaluated by predefined rubrics. We conduct comprehensive evaluations of state-of-the-art LLMs on the FIRE benchmark, including XuanYuan 4.0, our latest financial-domain mod...
