基于审计决策支持系统的抽样技术研究
发布时间：2019-01-01 13:19
【摘要】： 20世纪80年代以来,信息技术以人类历史从未有过的高速度持续发展,改变了人类社会利用信息资源的方式和能力,传统的以手工审计为主的审计模式不能适应企业会计信息电子化的需求,迅速向审计电算化、审计决策支持系统发展。 审计决策支持系统借助计算机高速精确的运算能力、大容量的记忆存储能力以及高速传输数据的互联网络,在提高审计工作效率的同时,积极改善审计效果,但并不能取代注册会计师的专业判断。审计抽样技术是风险导向型审计的重要技术和方法,也是审计决策支持系统的关键技术,其在审计决策支持系统中的应用效果直接关系到审计的效率和效果。 首先,在回顾了国内外在决策支持系统与审计抽样方面的研究成果,并对不同结构的决策支持系统进行评价后,本文采用“三库一综合部件”(数据库、模型库、知识库及其管理系统,人机交互及问题综合系统)结构决策支持系统框架。然后,将抽样技术分解为样本选取、样本审核、由样本审核结果评价总体这三个相互关联、承前启后的方面,重点分析了抽样技术在审计决策支持系统中的应用问题。根据手工审计抽样技术的基本方法与程序,将各种抽样模型拆分成若干个基本的标准化模块,再按照一定的结构重新组装成抽样模型,这样可以保证模型库内模型的一致性。抽样模型库管理系统通过调用模型库中的模型来完成样本选取。样本审核是一个结构化更差的问题,涉及到专业判断与知识推理,这需要通过建立知识库与知识推理机制来实现。审计抽样知识可以从审计专家的业务特征分析、审计案例的经验总结、相关文献的理论研究成果中获得,决策支持系统自身也会通过一定的机制进行“机器学习”。推理机制是决策支持系统实现智能化的核心部分,它模拟人类的思维推理功能来辅助解决和回答问题的计算机程序,通过直接搜索知识库,利用模式匹配的方法,确定使用哪些知识。根据样本审核结果推断总体,将总体误差同可容忍误差进行比较,以决定是否增加样本或执行替代程序,这可以通过调用模型来实现。最后,结合案例对审计抽样技术做了系统检验。
[Abstract]:Since the 1980s, information technology has developed at a high speed than ever before in human history, which has changed the way and ability of human society to make use of information resources. The traditional audit mode, which is based on manual audit, can not meet the needs of electronic accounting information of enterprises, and develops rapidly to computerization of audit and audit decision support system. The audit decision support system, with the help of the computer's high speed and precise computing power, the large memory storage capacity and the high speed data transmission network, improves the audit efficiency while improving the audit effect. But it cannot replace the professional judgment of CPA. Audit sampling technology is an important technology and method of risk-based audit, and it is also the key technology of audit decision support system. Its application effect in audit decision support system is directly related to the efficiency and effect of audit. First of all, after reviewing the research results of decision support system and audit sampling at home and abroad, and evaluating the decision support system with different structures, this paper adopts "three libraries and one integrated component" (database, model base). Knowledge base and its management system, human-computer interaction and problem synthesis system) structure decision support system framework. Then, the sampling technique is decomposed into sample selection, sample audit, and the results of sample audit are related to each other. In this paper, the application of sampling technology in audit decision support system is analyzed. According to the basic methods and procedures of manual audit sampling technology, the sampling models are divided into several basic standardized modules, and then reassembled into sampling models according to a certain structure, which can ensure the consistency of the models in the model base. The sampling model base management system completes the sample selection by calling the model in the model base. Sample audit is a worse structured problem, which involves professional judgment and knowledge reasoning, which needs to be realized by establishing knowledge base and knowledge reasoning mechanism. Audit sampling knowledge can be obtained from the analysis of audit experts' business characteristics, the experience of audit cases, the theoretical research results of relevant literature, and the decision support system itself will carry out "machine learning" through certain mechanisms. Reasoning mechanism is the core part of intelligent decision support system. It simulates human thinking reasoning function to assist computer program to solve and answer questions, by searching knowledge base directly and using pattern matching method. Determine what knowledge to use. The total error is compared with the tolerable error in order to decide whether to increase the sample or execute the substitute program, which can be achieved by calling the model. Finally, combined with the case of audit sampling technology to do a systematic test.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2006
【分类号】：F239.1
本文编号：2397623
[Abstract]:Since the 1980s, information technology has developed at a high speed than ever before in human history, which has changed the way and ability of human society to make use of information resources. The traditional audit mode, which is based on manual audit, can not meet the needs of electronic accounting information of enterprises, and develops rapidly to computerization of audit and audit decision support system. The audit decision support system, with the help of the computer's high speed and precise computing power, the large memory storage capacity and the high speed data transmission network, improves the audit efficiency while improving the audit effect. But it cannot replace the professional judgment of CPA. Audit sampling technology is an important technology and method of risk-based audit, and it is also the key technology of audit decision support system. Its application effect in audit decision support system is directly related to the efficiency and effect of audit. First of all, after reviewing the research results of decision support system and audit sampling at home and abroad, and evaluating the decision support system with different structures, this paper adopts "three libraries and one integrated component" (database, model base). Knowledge base and its management system, human-computer interaction and problem synthesis system) structure decision support system framework. Then, the sampling technique is decomposed into sample selection, sample audit, and the results of sample audit are related to each other. In this paper, the application of sampling technology in audit decision support system is analyzed. According to the basic methods and procedures of manual audit sampling technology, the sampling models are divided into several basic standardized modules, and then reassembled into sampling models according to a certain structure, which can ensure the consistency of the models in the model base. The sampling model base management system completes the sample selection by calling the model in the model base. Sample audit is a worse structured problem, which involves professional judgment and knowledge reasoning, which needs to be realized by establishing knowledge base and knowledge reasoning mechanism. Audit sampling knowledge can be obtained from the analysis of audit experts' business characteristics, the experience of audit cases, the theoretical research results of relevant literature, and the decision support system itself will carry out "machine learning" through certain mechanisms. Reasoning mechanism is the core part of intelligent decision support system. It simulates human thinking reasoning function to assist computer program to solve and answer questions, by searching knowledge base directly and using pattern matching method. Determine what knowledge to use. The total error is compared with the tolerable error in order to decide whether to increase the sample or execute the substitute program, which can be achieved by calling the model. Finally, combined with the case of audit sampling technology to do a systematic test.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2006
【分类号】：F239.1
【引证文献】
相关硕士学位论文 前1条
1 刘潇;风险导向审计下计算机审计模块的设计研究[D];广东外语外贸大学;2008年
，本文编号：2397623
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