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http://dx.doi.org/10.7472/jksii.2016.17.6.123

A Study on Continuous Monitoring Reinforcement for Sales Audit Using Process Mining Under Big Data Environment  

Yoo, Young-Seok (Department of Information and Telecommunications, Hanshin University)
Park, Han-Gyu (Department of Information and Telecommunications, Hanshin University)
Back, Seung-Hoon (Department of Information and Telecommunications, Hanshin University)
Hong, Sung-Chan (Department of Information and Telecommunications, Hanshin University)
Publication Information
Journal of Internet Computing and Services / v.17, no.6, 2016 , pp. 123-131 More about this Journal
Abstract
Process mining in big data environment utilize a number of data were generated from the business process. It generates lots of knowledge and insights regarding implementation and improvement of the process through the event log of the company's enterprise resource planning (ERP) system. In recent years, various research activities engaged with the audit work of company organizations are trying actively by using the maximum strength of the mining process. However, domestic studies on applicable sales auditing system for the process mining are insufficient under big data environment. Therefore, we propose process-mining methods that can be optimally applied to online and traditional auditing system. In advance, we propose continuous monitoring information system that can early detect and prevent the risk under the big data environment by monitoring risk factors in the organizations of enterprise. The scope of the research of this paper is to design a pre-verification system for risk factor via practical examples in sales auditing. Furthermore, realizations of preventive audit, continuous monitoring for high risk, reduction of fraud, and timely action for violation of rules are enhanced by proposed sales auditing system. According to the simulation results, avoidance of financial risks, reduction of audit period, and improvement of audit quality are represented.
Keywords
Process Mining; Internal Audit; Real Time Monitoring; Big Data; Continuous Monitoring;
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