大语言模型之审计场景应用探讨——由DeepSeek现象引发的思考  

Research on Construction and Application of Audit Knowledge Graph Driven by DeepSeek Large Models--Take the Special Verification Audit of Enterprise's Public Information as an Example

作　　者：张苏 金根元 朱芸 

机构地区：[1]苏州众勤会计师事务所 [2]苏州天瑞迅腾信息科技有限公司 [3]合携数据科技(苏州)有限公司

出　　处：《中国注册会计师》2025年第4期31-37,F0002,5,共9页The Chinese Certified Public Accountant

摘　　要：本文结合行业DeepSeek应用热潮,介绍了人工智能自然语言处理技术的演进和大语言模型的数理机制,并探讨了注册会计师审计场景如何应用大语言模型(LLM),包括:基于LLM的领域知识库搭建;利用LLM辅助审计证据过程的构想;审计推理模型训练数据的构造。本文旨在与同行分享新知心得,一起认知LLM的能力和能力边界,科学探讨LLM及相关技术的审计场景落地,合理定位LLM审计应用预期。In the digital age,enterprises face dual challenges in integrating multi-source heterogeneous data and adapting to dynamic regulatory rules when conducting specialized audits of public information.Taking the enterprise's information verification project undertaken by ND Accounting Firm for the Municipal Market Supervision Bureau as an example,this paper proposes an audit knowledge graph construction method driven by DeepSeek large models.The aim is to enhance verification efficiency and accuracy through structured knowledge representation and dynamic reasoning mechanisms.The study first analyzes limitations of traditional verification methods in terms of data heterogeneity,rule complexity,and interpretability,then designs a technical framework that integrates knowledge graphs with large models.This framework converts legal provisions into computable logic through ontology modeling and rule engines,supports semantic alignment and dynamic updates of multi-source data,and leverages DeepSeek large models to enhance semantic understanding and reasoning capabilities in complex scenarios.This research provides a reusable methodology for the intelligent transformation of auditing,which has significant practical value for enhancing the digital capabilities of accounting firms and improving the effectiveness of market regulation services.

关 键 词：大语言模型 审计场景 应用探讨 注册会计师 

分 类 号：F239[经济管理—会计学]