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论文编号：	15503
作者编号：	2320223873
上传时间：	2025/6/13 12:30:28
中文题目：	H 会计师事务所审计质量管理改进研究
英文题目：	An Empirical Study on Audit Quality Management Enhancement in H Accounting Firm
指导老师：	卿志琼
中文关键字：	H会计师事务所；大数据技术；审计质量管理
英文关键字：	Accounting Firm; Big Data Technology; Audit Quality Management
中文摘要：	近年来，本土会计师事务所频繁受到财政部、中注协、证监会等监管机构的处罚，这反映出本土会计师事务所审计质量管理存在缺陷，审计质量较低。大数据技术的快速发展深刻变革了传统审计模式。面对企业财务数据规模激增、无纸化趋势加速的挑战，传统审计手段在风险识别效率、数据分析深度和证据可靠性等方面存在不足。在此背景下，会计师事务所亟需改进审计质量以重塑核心竞争力。一方面，高质量审计是保障资本市场信息透明、维护投资者信任的基础，尤其在数据造假手段日益隐蔽的当下，提升审计质量直接关系到市场公平与风险防控效能；另一方面，以大数据技术为驱动的审计模式转型是行业发展的必然趋势，只有优化审计质量，才能满足监管机构对审计证据全面性、实时性的新要求，以及客户对精准风险预警和决策支持服务的更高期待。 论文梳理了审计质量管理等相关理论与研究，以此为基础分析了H会计师事务所审计业务的独特性，通过定性与定量的方法分析了H 会计师事务所审计质量管理的现状与问题。论文通过问卷调查与实证分析，得出 H 会计师事务所审计质量管理存在的主要问题为：技术工具滞后、流程管理失范、人员能力断层。针对这些问题论文提出了改进的策略、策略的实施与保障。首先明确审计质量管理改进的目标与原则；然后从技术工具升级、流程机制重构、人才体系重塑三个方面阐述大数据驱动的审计质量管理改进策略；论文最后阐述了审计质量改进策略的实施过程、重点与预期效果；同时，从重视人才的培养与引进、技术保障、组织与制度保障、完善相关法律法规建设等方面，为改进策略的实施提供支持保障。 论文以 H 会计师事务所为研究对象，把质量管理相关理论运用到H 会计师事务所审计质量管理中，具有一定的应用创新价值。论文通过案例分析的方式，探讨了H 会计师事务所审计质量提升的方式。同时，论文针对极具行业代表性的 H 会计师事务所的审计质量管理展开研究。这一研究不仅能够补充审计质量管理相关的学术研究成果，而且能为其他会计师事务所提供一定的参考，在一定程度上助力我国审计行业整体审计质量管理水平的提升。
英文摘要：	In recent years, domestic accounting firms in China have faced frequent penalties from regulatory bodies such as the Ministry of Finance, the Chinese Institute of Certified Public Accountants (CICPA), and the China Securities Regulatory Commission (CSRC). This reflects deficiencies in audit quality management and subpar auditing standards within these firms. The rapid advancement of big data technology has profoundly transformed traditional auditing practices. Confronted with challenges such as exponential growth in corporate financial data and accelerated digitization, conventional audit methods exhibit limitations in risk identification efficiency, data analysis depth, and evidence reliability. In this thesis, accounting firms must urgently enhance audit quality to rebuild their core competitiveness. On one hand, high-quality auditing serves as the cornerstone for ensuring information transparency in capital markets and maintaining investor trust, particularly as financial fraud techniques grow increasingly sophisticated. On the other hand, the shift toward big data-driven audit models represents an inevitable industry trend. Only by optimizing audit quality can firms meet regulators’ heightened demands for comprehensive and real-time audit evidence, as well as clients’escalating expectations for precise risk warnings and decision- support services. This thesis synthesizes theories and research on audit quality management, analyzing the unique characteristics of audit practices at H Accounting Firm through qualitative and quantitative methods. Using surveys and empirical analysis, the thesis identifies three primary issues in H Accounting Firm’s audit quality management: outdated technical tools, irregular process controls, and competency gaps among personnel. To address these challenges, the study proposes improvement strategies, implementation plans, and safeguards. First, it clarifies objectives and principles for audit quality enhancement. Next, it outlines a big data-driven strategy focusing on three dimensions: upgrading technical infrastructure, restructuring process mechanisms, and revamping talent development systems. Finally, the paper details the implementation process, key priorities, and anticipated outcomes of these strategies, supported by measures such as talent cultivation, technological investments, organizational reforms, and improvements to regulatory frameworks. Focusing on H Accounting Firm as a case study, this thesis applies quality management theories to audit practices, demonstrating practical innovation. By examining H Accounting Firm—a representative player in the industry—the thesis not only enriches academic discourse on audit quality management but also provides actionable insights for other accounting firms. This work contributes to elevating audit quality standards across China’s auditing industry, fostering systemic improvements in compliance and professional excellence.
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