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      Application of Process Mining in Managerial Accounting : A Case Study of an Investments and Securities Firm

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      https://www.riss.kr/link?id=T12530863

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Business process mining techniques use event logs recorded from information systems to extract and discover useful process and organizational information. Over the past couple of decades, many new and powerful process mining techniques have been developed by researchers and software vendors. Although numerous case studies demonstrating the applicability of process mining have been emerging in literature, there has yet to be an application of process mining in the financial sector. In this paper, we explore the applicability of process mining of an investments and securities firm, more specifically investigating its managerial accounting processes. Using an assortment of process mining techniques available in the ProM framework, we examine and discover clear differences between the AS-IS model stated by the financial firm and the process model extracted from the event logs. This research aims to accomplish the following: a) add to the current process mining application literature by examining the applicability of process mining in the financial sector, b) utilize various process mining techniques to observe and assess process information in the specific managerial accounting case study of the monthly profit and loss computation process, c) identify the strengths of process mining and how they can supplement the weaknesses of business process reengineering, and d) address the possibility that event log data with insufficient case sizes needs to be addressed differently than past approaches with data with sufficient case sizes.
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      Business process mining techniques use event logs recorded from information systems to extract and discover useful process and organizational information. Over the past couple of decades, many new and powerful process mining techniques have been devel...

      Business process mining techniques use event logs recorded from information systems to extract and discover useful process and organizational information. Over the past couple of decades, many new and powerful process mining techniques have been developed by researchers and software vendors. Although numerous case studies demonstrating the applicability of process mining have been emerging in literature, there has yet to be an application of process mining in the financial sector. In this paper, we explore the applicability of process mining of an investments and securities firm, more specifically investigating its managerial accounting processes. Using an assortment of process mining techniques available in the ProM framework, we examine and discover clear differences between the AS-IS model stated by the financial firm and the process model extracted from the event logs. This research aims to accomplish the following: a) add to the current process mining application literature by examining the applicability of process mining in the financial sector, b) utilize various process mining techniques to observe and assess process information in the specific managerial accounting case study of the monthly profit and loss computation process, c) identify the strengths of process mining and how they can supplement the weaknesses of business process reengineering, and d) address the possibility that event log data with insufficient case sizes needs to be addressed differently than past approaches with data with sufficient case sizes.

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      목차 (Table of Contents)

      • I. Introduction 1
      • II. Related Work 4
      • 2.1 Business Process Reengineering 4
      • 2.2 Managerial Accounting 5
      • 2.3 Process Mining 5
      • I. Introduction 1
      • II. Related Work 4
      • 2.1 Business Process Reengineering 4
      • 2.2 Managerial Accounting 5
      • 2.3 Process Mining 5
      • III. Research framework 8
      • IV. Case Analysis 9
      • 4.1 Log Description 9
      • 4.2 Mining 10
      • 4.2.1 Control Flow Perspective 11
      • 4.2.2 Conformance Analysis 15
      • 4.2.3 Performance Perspective 24
      • 4.2.4 Organizational and Social Network Perspective 27
      • V. Discussion 29
      • VI. Conclusion 31
      • References 34
      • Acknowledgement 37
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