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Generating High Quality Samples of Process Cases in Internal Audit

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Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 427)

Abstract

Business Process Mining (BPM) has become an essential tool in internal audit (IA), which helps auditors analyze potential risks in clients’ core business processes. After finishing the risk analysis task for the target business process with BPM, auditors need to sample a small set of representative process cases from event log, based on which clients will verify the analysis results and analyze the triggers for the risks in the target business process. This process case sampling (PCS) step is important because it is difficult to check each single case from a large event log. Therefore, the quality of the set of case samples (SCS) from PCS is regarded as one of the success factors in IA project. Manual PCS and simple random PCS are two basic methods for executing PCS. However, both methods cannot assure the quality of the generated SCS. In this paper, we propose an advanced PCS method. It first defines the risk of process cases as well as the factors that affect the quality of SCS, before dynamically optimizing the quality of SCS during PCS. Our experimental evaluation highlights that our approach yields higher quality SCS than manual PCS and simple random PCS.

Keywords

  • Business process mining
  • Business process management
  • Process case sampling
  • Process risk management
  • Internal auditing

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Notes

  1. 1.

    As introduced in Sect. 2, risk-diversity is affected by both risk-level and risk-dissimilarity. Therefore, QS indirectly takes risk-diversity into account.

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Sun, Y., AI-Khazrage, L., Özümerzifon, Ö. (2021). Generating High Quality Samples of Process Cases in Internal Audit. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds) Business Process Management Forum. BPM 2021. Lecture Notes in Business Information Processing, vol 427. Springer, Cham. https://doi.org/10.1007/978-3-030-85440-9_16

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  • DOI: https://doi.org/10.1007/978-3-030-85440-9_16

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