Auditing 2.0: Using Process Mining to Support Tomorrow's Auditor

被引:78
作者
van der Aalst, Wil M. P. [1 ,2 ]
van Hee, Kees M.
van der Werf, Jan Martijn
Verdonk, Marc
机构
[1] Eindhoven Univ Technol, Dept Math & Comp Sci, AIS Grp, NL-5600 MB Eindhoven, Netherlands
[2] Queensland Univ Technol, Brisbane, Qld 4001, Australia
关键词
Auditing; 2.0; Information technology; IT systems; Process mining;
D O I
10.1109/MC.2010.61
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Auditors can use process mining techniques to evaluate all events in a business process, and do so while it is still running. The goal of process mining is to discover, monitor, and improve real (not assumed) processes by extracting knowledge from event logs. Process mining starts with the event log: a sequentially recorded collection of events, each of which refers to an activity (well-defined step) and is related to a particular case (process instance). The systematic, reliable, and trustworthy recording of events, known as business provenance, is essential to auditing. By analyzing frequent patterns, process mining techniques can extract from event logs models that describe the processes at hand. Auditors can also extend an a priori model with a new aspect based on event log data. Auditors can also use a process model based on historic data to make predictions about running cases. Auditors can use historic data to filter out irrelevant situations or scope the event log for a particular process or group of customers.
引用
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页码:90 / 93
页数:4
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