摘 要
随着大数据技术的迅猛发展，会计风险管理领域面临着前所未有的机遇与挑战。传统风险管理流程往往受限于数据处理能力不足、信息孤岛效应显著以及预测精度较低等问题，难以满足现代企业对风险防控的高效性与精准性需求。本研究旨在探讨大数据技术如何优化会计风险管理流程，以提升风险识别、评估和应对的整体效能。通过整合大数据分析工具与会计风险管理框架，采用定量建模与案例分析相结合的研究方法，系统评估了大数据技术在数据采集、实时监控、预测预警及决策支持等方面的应用潜力。研究结果表明，基于大数据技术的风险管理流程能够显著提高数据处理效率，增强风险预测的准确性，并为企业提供更具前瞻性的决策依据。此外，本研究创新性地提出了一种融合机器学习算法的动态风险评估模型，有效解决了传统方法中静态分析的局限性。该模型在实际应用中展现出较强的适应性和鲁棒性，为会计风险管理提供了新的理论支撑和技术路径。总体而言，本研究不仅深化了大数据技术在会计领域的应用价值，还为未来相关研究奠定了坚实基础，具有重要的学术意义与实践指导作用。
关键词：大数据技术；会计风险管理；动态风险评估模型；预测预警；决策支持
Big Data Technology for Optimizing Accounting Risk Management Processes
Abstract: With the rapid development of big data technology, the field of accounting risk management is facing unprecedented opportunities and challenges. Traditional risk management processes are often constrained by insufficient data processing capabilities, significant information silo effects, and low prediction accuracy, making it difficult to meet modern enterprises' demands for efficiency and precision in risk prevention and control. This study aims to explore how big data technology can optimize accounting risk management processes to enhance the overall effectiveness of risk identification, assessment, and response. By integrating big data analytical tools with an accounting risk management fr amework and employing a research methodology that combines quantitative modeling with case analysis, this study systematically evaluates the application potential of big data technology in data collection, real-time monitoring, predictive warning, and decision support. The results indicate that big data-based risk management processes can significantly improve data processing efficiency, enhance the accuracy of risk prediction, and provide enterprises with more forward-looking decision-making references. Furthermore, this study innovatively proposes a dynamic risk assessment model incorporating machine learning algorithms, effectively addressing the limitations of static analysis in traditional methods. The model demonstrates strong adaptability and robustness in practical applications, offering new theoretical support and technical pathways for accounting risk management. Overall, this study not only deepens the application value of big data technology in the accounting domain but also lays a solid foundation for future related research, possessing significant academic implications and practical guiding significance.
Keywords: Big Data Technology; Accounting Risk Management; Dynamic Risk Assessment Model; Prediction And Early Warning; Decision Support
目 录
一、绪论 1
（一）大数据技术与会计风险管理的背景分析 1
（二）优化会计风险管理流程的研究意义 1
（三）国内外研究现状综述 1
二、大数据技术在会计风险管理中的应用基础 2
（一）大数据技术的核心功能概述 2
（二）会计风险管理的基本流程解析 2
（三）大数据技术对风险管理流程的支撑作用 3
（四）数据驱动的风险管理框架构建 3
三、大数据技术优化会计风险管理的具体路径 4
（一）数据采集与风险识别的优化策略 4
（二）数据分析在风险评估中的应用实践 4
（三）风险预警机制的智能化升级 5
（四）决策支持系统的设计与实施 5
四、大数据技术优化会计风险管理的案例与挑战 6
（一）实际案例分析：大数据技术的应用效果 6
（二）技术实施中的关键问题探讨 6
（三）数据安全与隐私保护的应对措施 7
（四）未来发展方向与改进建议 7
结论 8
参考文献 9
致 谢 10
