Natural Language Processing for Risk Identification in Business Process Repositories

Avi Wasser, Maya Lincoln

Abstract

In recent years, researchers have become increasingly interested in developing methods and tools for automating the design of governance, risk and compliance (GRC) models. This work suggests a method for machine-assisted identification and design of new risks, based on business logic that is extracted from real-life process repositories using a linguistic analysis of the operational similarity between process conducts. The suggested method can assist process analysts, audit executives and risk managers in identifying new organizational risks while making use of knowledge that is encoded in existing process repositories. The suggested framework was tested on the ProcessGene process repository, showing our approach to be effective in enabling the identification and design of new risks within real-life business process models.

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Paper Citation


in Harvard Style

Wasser A. and Lincoln M. (2016). Natural Language Processing for Risk Identification in Business Process Repositories . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-187-8, pages 608-613. DOI: 10.5220/0005841006080613


in Bibtex Style

@conference{iceis16,
author={Avi Wasser and Maya Lincoln},
title={Natural Language Processing for Risk Identification in Business Process Repositories},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2016},
pages={608-613},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005841006080613},
isbn={978-989-758-187-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Natural Language Processing for Risk Identification in Business Process Repositories
SN - 978-989-758-187-8
AU - Wasser A.
AU - Lincoln M.
PY - 2016
SP - 608
EP - 613
DO - 10.5220/0005841006080613