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Enhancing regulatory compliance by using artificial intelligence text mining to identify penalty clauses in legislation

Abstract
As regulatory compliance (or compliance governance) becomes ever more challenging, attempts to engage IT solutions and especially artificial intelligence (AI) are on the rise. This paper suggest that regulatory compliance can be enhanced by employing an AI model trained to identify penalty clauses in the regulations. The paper provides the theoretical basis of machine learning for text classification and presents a two stage experiment of (1) training multiple models and selecting the best one; and (2) employing a sliding window detection in order to identify penalty clauses in regulation. Results benchmarked using an algorithm based penalties API suggests further development is needed.
Type
Journal Article
Type of thesis
Series
Citation
Date
2018
Publisher
Full Court Press
Degree
Supervisors
Rights
© 2018 Full Court Press. Used with permission