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论文编号：	15045
作者编号：	2320224187
上传时间：	2024/12/9 19:42:22
中文题目：	类金融企业基于大数据的内部审计研究
英文题目：	Research on Internal Audit of Financial Enterprises Based on Big Data
指导老师：	程新生
中文关键字：	内部审计；大数据；类金融企业
英文关键字：	Internal Audit；Big Data；Class Of Financial Enterprises
中文摘要：	近些年，大数据分析、云计算、人工智能等信息科学技术飞速发展，不仅极大地提高了工作效率，更是形成了全新的商业模式和服务形态。信息技术的发展，使得数据在获取、整理、存储、分析和应用等方面取得了巨大进步。企业能够运用大数据分析技术从海量数据中提取有价值的信息，通过处理、分析，优化决策过程，提高运营效率和效果。云计算平台的构建，为数据存储和计算提供了几乎无限的扩展能力，使得资源的利用更加高效和灵活。近两年人工智能技术的突破和应用，对信息技术加速发展，突破现有技术注入了新鲜血液。机器学习、深度学习的应用，让机器能够模拟人类的学习过程，处理复杂的任务，甚至在某些领域达到或超越人类的能力。因此，研究类金融企业在内部审计中运用大数据技术开展工作的现状及应用情况，对促进类金融企业审计工作技术创新、提质增效等方面具有重要意义。 本文以A担保公司为例，从理论和应用两方面对类金融企业基于大数据技术开展审计的应用现状进行研究。文中对研究用到的理论进行了详细梳理，阐述了内部审计和大数据技术的基本理论和特征，大数据审计与传统审计方法存在着相辅相成的联系，也存在着较大区别；通过列举业务拓展与效率效果审计、风险管理审计等多个内部审计项目，从多个维度论述在基于大数据审计方法中，类金融企业能够较好的通过数据获取、清洗、分析等操作，全面深入的分析业务中存在的风险，有效提升了类金融企业审计工作质量，但是大数据技术为内部审计工作带来的机遇和挑战的同时，也存在着诸多不足。 研究发现，A担保公司在运用大数据审计方法开展内部审计工作时，能够全面、深入揭示存在的问题，识别风险隐患，但由于企业内部对大数据技术的认知偏差、数据治理工作不到位、技术人才匮乏、缺乏对信息技术的研究探索等问题，导致运用的大数据技术还处于探索、发展阶段，尚未实现运用数据挖掘技术和工具、建立审计模型等方法提升审计工作效率、丰富审计成果的目标，基于上述问题提出了改进思路和建议，对促进A担保公司进一步运用大数据方法实现提质增效具有重要意义，也为类金融企业开展审计工作提供参考。
英文摘要：	In recent years, the rapid development of information science and technology such as big data analysis, cloud computing, and artificial intelligence has not only greatly improved work efficiency, but also formed new business models and service forms. The development of information technology has made tremendous progress in data acquisition, organization, storage, analysis, and application. Enterprises can use big data analysis technology to extract valuable information from massive data, process, analyze, optimize decision-making processes, and improve operational efficiency and effectiveness. The construction of cloud computing platforms provides almost unlimited scalability for data storage and computing, making resource utilization more efficient and flexible. The breakthroughs and applications of artificial intelligence technology in the past two years have accelerated the development of information technology and injected fresh blood into breaking through existing technologies. The application of algorithms such as machine learning and deep learning enables machines to simulate human learning processes, handle complex tasks, and even achieve or exceed human capabilities in certain fields. Therefore, studying the current situation and application of big data technology in internal auditing of financial enterprises is of great significance for promoting technological innovation, improving quality and efficiency in auditing work of financial enterprises. This article takes the internal audit project carried out by A Guarantee Company as an example to study the application status of big data technology based internal audit in financial enterprises from both theoretical and practical perspectives. The article provides a detailed review of the theories used in the research, elaborating on the basic theories and characteristics of internal auditing and big data auditing. Big data auditing and traditional auditing methods have complementary connections and significant differences; By listing multiple internal audit projects such as business expansion and efficiency audit, risk management audit, etc., this paper discusses from multiple dimensions that in big data based audit methods, financial enterprises can effectively improve the quality of audit work by comprehensively and deeply analyzing the risks in their business through data acquisition, cleaning, analysis, and other operations. However, while big data technology brings opportunities and challenges to internal audit work, there are also many shortcomings. Research has found that when A Guarantee Company uses big data audit methods to conduct internal audit work, it can comprehensively and deeply reveal existing problems, identify risks and hidden dangers. However, due to internal cognitive biases towards big data technology, inadequate data governance, lack of technical talent, and a lack of research and exploration of information technology, the big data technology used is still in the exploratory and developmental stage, and has not yet achieved the goal of using data mining techniques and tools, establishing audit models and other methods to improve audit work efficiency and enrich audit results. Based on the above issues, improvement ideas and suggestions are proposed, which are of great significance for promoting A Guarantee Company to further use big data methods to achieve quality and efficiency improvement, and also provide reference for similar financial enterprises to carry out audit work.
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