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Business process compliance checking – applying and evaluating a generic pattern matching approach for conceptual models in the financial sector

Author

Listed:
  • Jörg Becker

    (University of Münster)

  • Patrick Delfmann

    (University of Münster)

  • Hanns-Alexander Dietrich

    (University of Münster)

  • Matthias Steinhorst

    (University of Münster)

  • Mathias Eggert

    (University of Münster)

Abstract

Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.

Suggested Citation

  • Jörg Becker & Patrick Delfmann & Hanns-Alexander Dietrich & Matthias Steinhorst & Mathias Eggert, 2016. "Business process compliance checking – applying and evaluating a generic pattern matching approach for conceptual models in the financial sector," Information Systems Frontiers, Springer, vol. 18(2), pages 359-405, April.
    • Handle: RePEc:spr:infosf:v:18:y:2016:i:2:d:10.1007_s10796-014-9529-y
    DOI: 10.1007/s10796-014-9529-y
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    References listed on IDEAS

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    3. Samer Elhajjar & Laurent Yacoub & Hala Yaacoub, 2023. "Automation in business research: systematic literature review," Information Systems and e-Business Management, Springer, vol. 21(3), pages 675-698, September.
    4. Amit V. Deokar & Jie Tao, 2021. "OrgMiner: A Framework for Discovering User-Related Process Intelligence from Event Logs," Information Systems Frontiers, Springer, vol. 23(3), pages 753-772, June.
    5. Jan Mendling & Jan Recker & Hajo A. Reijers & Henrik Leopold, 2019. "An Empirical Review of the Connection Between Model Viewer Characteristics and the Comprehension of Conceptual Process Models," Information Systems Frontiers, Springer, vol. 21(5), pages 1111-1135, October.
    6. Agung Wahyudi & George Kuk & Marijn Janssen, 2018. "A Process Pattern Model for Tackling and Improving Big Data Quality," Information Systems Frontiers, Springer, vol. 20(3), pages 457-469, June.
    7. Sophie Cockcroft & Mark Russell, 2018. "Big Data Opportunities for Accounting and Finance Practice and Research," Australian Accounting Review, CPA Australia, vol. 28(3), pages 323-333, September.

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