SuperCLUE-Fin: Graded Fine-Grained Analysis of Chinese LLMs on Diverse Financial Tasks and Applications
Liang Xu, Lei Zhu, Yaotong Wu, Hang Xue

TL;DR
SuperCLUE-Fin is a comprehensive benchmark evaluating Chinese financial large language models across diverse tasks, emphasizing practical applications, compliance, and reasoning to guide future development in the Chinese financial AI sector.
Contribution
It introduces a novel, multi-faceted benchmark for Chinese financial LLMs, covering theoretical and practical tasks, and provides insights into model performance and areas for improvement.
Findings
Domestic models like GLM-4 and MoonShot-v1-128k outperform others.
The benchmark highlights the importance of compliance and risk management.
Performance hierarchy established among evaluated models.
Abstract
The SuperCLUE-Fin (SC-Fin) benchmark is a pioneering evaluation framework tailored for Chinese-native financial large language models (FLMs). It assesses FLMs across six financial application domains and twenty-five specialized tasks, encompassing theoretical knowledge and practical applications such as compliance, risk management, and investment analysis. Using multi-turn, open-ended conversations that mimic real-life scenarios, SC-Fin measures models on a range of criteria, including accurate financial understanding, logical reasoning, clarity, computational efficiency, business acumen, risk perception, and compliance with Chinese regulations. In a rigorous evaluation involving over a thousand questions, SC-Fin identifies a performance hierarchy where domestic models like GLM-4 and MoonShot-v1-128k outperform others with an A-grade, highlighting the potential for further development…
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Taxonomy
TopicsFinancial Distress and Bankruptcy Prediction
