RegMiner: Taming the complexity of regulatory documents for digitalized compliance management

Karolin Winter, Manuel Gall, Stefanie Rinderle-Ma

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

Business process compliance has become a crucial aspect for companies due to severe fines that can be imposed if constraints and rules emerging from regulatory documents are violated. Regulatory docu- ments are often written in natural language and analyzing them is mainly done manually since only limited tool support is available. Therefore, we present RegMiner, a web service for discovering and visualizing con- straints from regulatory documents. By employing NLP and data min- ing techniques, compliance constraints can be automatically extracted, grouped, and visualized leading to a separation of relevant and non- relevant document parts and insights into, e.g., duties of stakeholders. A case study based on a current document from the European parliament regarding the financial domain demonstrates RegMiner's maturity.

Original languageEnglish
Pages (from-to)112-116
Number of pages5
JournalCEUR Workshop Proceedings
Volume2673
StatePublished - 2020
Externally publishedYes
Event2020 Best Dissertation Award, Doctoral Consortium, and Demonstration and Resources Track at BPM, BPM-D 2020 - Sevilla, Spain
Duration: 13 Sep 202018 Sep 2020

Keywords

  • Business Process Compliance
  • Natural Language Processing
  • Regulatory Documents

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