Profiling Event Logs to Configure Risk Indicators for Process Delays

  • Anastasiia Pika
  • Wil M. P. van der Aalst
  • Colin J. Fidge
  • Arthur H. M. ter Hofstede
  • Moe T. Wynn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7908)


Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators (PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.


process risk indicators process mining risk identification 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Anastasiia Pika
    • 1
  • Wil M. P. van der Aalst
    • 2
    • 1
  • Colin J. Fidge
    • 1
  • Arthur H. M. ter Hofstede
    • 1
    • 2
  • Moe T. Wynn
    • 1
  1. 1.Queensland University of TechnologyBrisbaneAustralia
  2. 2.Eindhoven University of TechnologyEindhovenThe Netherlands

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