About | HeinOnline Law Journal Library | HeinOnline Law Journal Library | HeinOnline

1 RAIL 175 (2018)
Enhancing Regulatory Compliance by Using Artificial Intelligence Text Mining to Identify Penalty Clauses in Legislation

handle is hein.journals/rail1 and id is 182 raw text is: 





Enhancing Regulatory

Compliance by Using

Artificial Intelligence Text

Mining to Identify Penalty

Clauses in Legislation

Nachshon  Goltz and Michael Mayo*


    This article provides the theoretical basis of machine learning for text clas-
    sification 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.


    As regulatory compliance (or compliance governance) becomes
ever more challenging, attempts to engage IT solutions and espe-
cially artificial intelligence (Al) are on the rise. This article sug-
gests that regulatory compliance can be enhanced by employing an
Al model trained to identify penalty clauses in the regulations. The
article 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 penal-
ties API suggests further development is needed.


Introduction

   Challenges in regulatory compliance are closely associated with
the increased business opportunities resulting from globalization and
Information Communication  Technology. There is a drastic increase
in the regulatory requirements with which businesses must comply,
not only in sheer number but also in complexity, confronting busi-
nesses with the need to adapt to a complex and evolving regulatory
environment.2 In such an environment, organizations are finding
compliance with the numerous regulations to be very expensive, with
an estimated $1 trillion spent worldwide on regulatory compliance.
                   Robotics, Artificial Intelligence & Law I May-June 2018, Vol. 1, No. 3, pp. 175-191.
                                     @ 2018 Full Court Press. All rights reserved.
                                   ISSN 2575-5633 (print)/ISSN 2575-5617 (online)

What Is HeinOnline?

HeinOnline is a subscription-based resource containing nearly 3,000 academic and legal journals from inception; complete coverage of government documents such as U.S. Statutes at Large, U.S. Code, Federal Register, Code of Federal Regulations, U.S. Reports, and much more. Documents are image-based, fully searchable PDFs with the authority of print combined with the accessibility of a user-friendly and powerful database. For more information, request a quote or trial for your organization below.



Short-term subscription options include 24 hours, 48 hours, or 1 week to HeinOnline with pricing starting as low as $29.95

Contact us for annual subscription options:

Already a HeinOnline Subscriber?

profiles profiles most