摘 要
随着信息技术的迅猛发展，大数据技术逐渐渗透到企业管理的各个领域，为企业内部会计监管提供了全新的方法和工具。传统会计监管模式在数据处理能力、实时监控效率以及风险预警方面存在诸多局限性，难以满足现代企业复杂多变的管理需求。本研究旨在探讨大数据技术在企业内部会计监管中的应用潜力及其实际效果，通过构建基于大数据分析的会计监管框架，提升企业财务信息的质量与透明度。研究采用文献分析、案例研究及实证分析相结合的方法，选取多家典型企业作为样本，深入剖析大数据技术在数据采集、存储、分析及可视化等环节的具体应用。研究结果表明，大数据技术能够显著提高会计监管的效率和精准度，实现对财务异常行为的实时监测与预警，并为管理层提供更具价值的决策支持。此外，本研究创新性地提出了一种融合机器学习算法的智能监管模型，该模型能够自动识别潜在的财务风险并生成动态评估报告，从而有效降低人为干预的可能性。总体而言，本研究不仅验证了大数据技术在企业内部会计监管中的可行性，还为相关领域的理论发展和实践应用提供了重要参考，其主要贡献在于推动了会计监管从静态向动态、从人工向智能化的转型，为企业风险管理与内部控制体系的完善奠定了坚实基础。
关键词：大数据技术；会计监管；机器学习；财务风险预警；智能化转型
Abstract
With the rapid development of information technology, big data technology has gradually permeated various fields of enterprise management, providing new methods and tools for internal accounting supervision within enterprises. The traditional accounting supervision model suffers from numerous limitations in data processing capability, real-time monitoring efficiency, and risk warning functions, making it difficult to meet the complex and ever-changing management needs of modern enterprises. This study aims to explore the application potential and practical effects of big data technology in enterprise internal accounting supervision by constructing a big-data-based accounting supervision fr amework to enhance the quality and transparency of financial information. A combination of literature analysis, case studies, and empirical analysis was employed, selecting multiple representative enterprises as samples to thoroughly examine the specific applications of big data technology in data collection, storage, analysis, and visualization. The results indicate that big data technology can significantly improve the efficiency and accuracy of accounting supervision, enabling real-time monitoring and early warning of financial anomalies while providing more valuable decision support for management. Furthermore, this study innovatively proposes an intelligent supervision model integrated with machine learning algorithms, which can automatically identify potential financial risks and generate dynamic evaluation reports, effectively reducing the possibility of human intervention. Overall, this study not only verifies the feasibility of big data technology in enterprise internal accounting supervision but also provides significant references for theoretical development and practical applications in related fields. Its primary contribution lies in promoting the transformation of accounting supervision from static to dynamic and from manual to intelligent, laying a solid foundation for the improvement of enterprise risk management and internal control systems.
Keywords: Big Data Technology; Accounting Supervision; Machine Learning; Financial Risk Warning; Intelligent Transformation
目 录
1绪论 1
1.1企业内部会计监管的背景与挑战 1
1.2大数据技术在会计监管中的意义 1
1.3国内外研究现状综述 1
1.4研究方法与技术路线 2
2大数据在会计监管中的理论基础 2
2.1会计监管的基本概念与框架 2
2.2大数据技术的核心原理 3
2.3数据驱动的会计监管模式分析 3
2.4大数据与传统会计监管的对比 4
2.5理论框架构建与验证 4
3大数据在企业内部会计监管中的应用实践 5
3.1数据采集与预处理技术的应用 5
3.2风险识别与预警机制的设计 5
3.3内部控制优化的实现路径 6
3.4审计证据获取的技术支持 6
3.5实践案例分析与经验总结 7
4大数据应用的挑战与对策研究 7
4.1数据安全与隐私保护问题 7
4.2技术实施中的成本与效率权衡 8
4.3人员能力与组织文化的适应性 8
4.4法律法规对大数据应用的影响 9
4.5对策建议与未来发展方向 9
结论 11
参考文献 12
致 谢 13
