摘 要
随着信息技术的迅猛发展，大数据技术逐渐渗透到各个领域，为审计行业带来了前所未有的机遇与挑战。传统审计方法在面对复杂多变的风险环境时存在局限性，而大数据技术以其强大的数据处理能力和智能化分析手段，能够显著提升审计风险控制的效率与精准度。本研究旨在探索大数据技术在审计风险控制中的应用潜力及其实际效果，通过构建基于大数据分析的审计风险评估模型，实现对潜在风险的实时监测与预警。研究采用定性与定量相结合的方法，首先梳理了大数据技术的核心功能及其在审计领域的适用场景，随后设计了一套融合机器学习算法和数据挖掘技术的分析框架，并以某大型企业财务数据为样本进行实证分析。结果显示，该模型能够有效识别高风险交易并显著降低误报率，同时大幅缩短审计周期，提升了审计工作的整体效能。本研究的主要创新点在于将大数据技术与传统审计流程深度融合，提出了一种动态、智能的风险控制机制，为审计行业的转型升级提供了理论支持和技术路径。这一成果不仅拓展了大数据技术的应用边界，也为审计实践提供了新的思路和工具。
关键词：大数据技术；审计风险控制；机器学习算法；数据挖掘；风险评估模型
Abstract
With the rapid development of information technology, big data technology has gradually permeated various fields, bringing unprecedented opportunities and challenges to the auditing industry. Traditional auditing methods exhibit limitations in addressing the complex and ever-changing risk environment, whereas big data technology, with its powerful data processing capabilities and intelligent analytical tools, can significantly enhance the efficiency and accuracy of audit risk control. This study aims to explore the application potential and practical effects of big data technology in audit risk control by constructing a big-data-based audit risk assessment model for real-time monitoring and early warning of potential risks. A combination of qualitative and quantitative approaches is employed; firstly, the core functions of big data technology and their applicable scenarios in auditing are systematically reviewed, followed by the design of an analytical fr amework integrating machine learning algorithms and data mining techniques. Empirical analysis is conducted using the financial data of a large enterprise as a sample. The results indicate that the model can effectively identify high-risk transactions while substantially reducing false-positive rates, and significantly shorten the audit cycle, thereby enhancing the overall effectiveness of auditing work. The primary innovation of this study lies in the deep integration of big data technology with traditional auditing processes, proposing a dynamic and intelligent risk control mechanism that provides theoretical support and technical pathways for the transformation and upgrading of the auditing industry. This achievement not only extends the application boundaries of big data technology but also offers new perspectives and tools for auditing practice.
Keywords: Big Data Technology；Audit Risk Control；Machine Learning Algorithm；Data Mining；Risk Assessment Model
目 录
摘 要 I
Abstract II
一、绪论 1
（一）大数据与审计风险控制的背景分析 1
（二）国内外研究现状综述 1
（三）研究方法与技术路线 1
二、大数据在审计风险识别中的应用 2
（一）审计风险识别的基本原理 2
（二）大数据分析技术在风险识别中的作用 2
（三）实例分析：大数据驱动的风险识别实践 3
三、大数据在审计风险评估中的应用 3
（一）风险评估的关键要素分析 3
（二）数据挖掘技术在风险评估中的应用 4
（三）案例探讨：基于大数据的风险评估模型 5
四、大数据在审计风险监控中的应用 5
（一）风险监控的核心需求与挑战 5
（二）实时数据分析技术的应用场景 6
（三）实践探索：大数据支持下的动态风险监控 6
结 论 7
致 谢 8
参考文献 9
