Modelling of money laundering and terrorism financing typologies
| DOI | https://doi.org/10.1108/13685201211238061 |
| Pages | 316-335 |
| Date | 06 July 2012 |
| Published date | 06 July 2012 |
| Author | Angela Samantha Maitland Irwin,Kim‐Kwang Raymond Choo,Lin Liu |
| Subject Matter | Accounting & finance |
Modelling of money laundering
and terrorism financing
typologies
Angela Samantha Maitland Irwin and Kim-Kwang Raymond Choo
Information Assurance Group and Forensic Computing Lab,
University of South Australia, Adelaide, Australia, and
Lin Liu
School of Computer and Information Science, University of South Australia,
Adelaide, Australia
Abstract
Purpose – The purpose of this paper is to show how modelling can be used to provide an
easy-to-follow, visual representation of the important characteristics and aspects of money laundering
behaviours extracted from real-world money laundering and terrorism financing typologies.
Design/methodology/approach – In total, 184 typologies were obtained from a number of
anti-money laundering and counter-terrorism financing (AML/CTF) bodies to determine the common
patterns and themes present in the cases involved. Financial flows, transactions and interactions
between entities were extracted from each of the typologies and modelled using the Unified Modelling
Language (UML) features within Microsoft Visio.
Findings – The paper demonstrates how complex transactional flows and interactions between the
different entities involved in a money laundering and terrorism financing case can be shown in an
easy-to-follow graphical representation, allowing practitioners to more easily and quickly extract the
relevant information from the typology, as opposed to reading a full text-based description. In addition,
these models make it easier to discover trends and patterns present within and across Types and allow
money laundering and terrorism financing typologies to be updated and published to the wider
international AML/CTF community, as and when new trends and behaviours become apparent.
Originality/value – A set of models have been produced that can be extended every time a new
scenario, typology or Type arises. These models can be held in a central repository that can be added to
and updated by AML/CTF practitioners and can be referred to by practitioners to help them identify
whether the case that they are dealing with fits already predefined money laundering and terrorism
financing behaviours, or whether a new behaviour has been discovered. These models may also be
useful for the development of money laundering and terrorism financing detection tools and the training
of new analysts or practitioners. The authors believe that their work goes some way to addressing the
current lack of formal methods and techniques for identifying and developing uniform procedures for
describing, classifying and sharing new money laundering and terrorism financing with the
international AML/CTF community, as and when they happen, in a simple but effective manner.
Keywords Terrorism, Financing, Money laundering,Modelling, Knowledge management,
Anti-moneylaundering/counterterrorismfinancing, Virtualenvironments, Entityrelationship modelling,
Collaborative informa tion sharing
Paper type Research paper
1. Introduction
In the late 1990s, the chairman of the Organisation for Economic Co-operation and
Development’s Financial Action Task Force (FATF) Working Group on Statistics
and Methods stated that there was a “need to estimate the size of money laundering
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1368-5201.htm
JMLC
15,3
316
Journal of Money Laundering Control
Vol. 15 No. 3, 2012
pp. 316-335
qEmerald Group Publishing Limited
1368-5201
DOI 10.1108/13685201211238061
and quantify its constituent parts”. At least four areas were highlighted for further
quantitative measures, including: understanding the magnitude of the crime,
understanding the effectiveness of counter-money laundering efforts, understan ding
the macro-economic effects of money laundering and understanding money laundering
(Walker, 1998).
Today there is an abundance of data on global trends in financial crime, money
laundering and terrorism financing and much work has been done in an attempt to
produce accurateestimates of money laundering and terrorism financing flows, however,
although a number of largely varied estimates have been offered, none of them can be
irrefutably proven. Also, the quantitative issues that have been raised by anti-money
laundering and the fight against terrorismfinancing have yet to be definitively answered
(Biagioli, 2008) and no broadly approved measurement methodology has yet been
developed (Fleming, 2009).
Quantifying money laundering and terrorism financing is a very necessary and
worthwhile exercise, however, identifying and developing uniform procedures and
techniques for quickly and easily describing, classifying and sharing new money
laundering and terrorism financing techniques and behaviours with the wider
international AML/CTF community is equally, if not more important, especially when
the platforms, techniques and methods employed by adversaries change rapidly and
are becoming more complex (Nardo, 2006).
A number of programmes are already in existence for sharing information on money
laundering and terrorism financing typologies. For example, annual typologies and case
study reports are published by many AML/CTF agencies to assist reporting entities to
meet their AML/CTF obligations. These reports contain details of sanitised, successfully
detected money laundering and terrorism financing cases and provide a wealth of
information on current threats and trends, techniques employed and, in many cases, the
amount of funds involved. However, since these reports are published annually,
a potential vacuum is created where new money laundering or terrorism financing
schemes may go undetected until the next batch of typology reports is published. In
addition, these typology reports only provide a limited snapshot of some of the types of
money laundering and terrorism financing activity detected in individual jurisdictions
in that year and often only include cases where large sums of money have been detected,
thereby potentially omitting a number of significant or new money laundering and
terrorism financing behaviours or techniques. The format that the typology reports take
can also pose problems due to their over-descriptive and case-specific nature.
What is required is a collaborative, synergistic reporting system that can be updated
in real-time; thereby informing AML/CTF experts and investigators immediately or
soon after a new technique or method has been discovered.
This view is supported by a number of authors who believe that high-level
collaboration (Liu and Zhang, 2007), synergistic information sharing and knowledge
management (Biagioli, 2006; Biagioli and Nardo, 2007; Global Justice Information
Sharing Initiative, 2006; Hardouin, 2009; Mueller, 2006; O’Connell, 2008) are important
aspects of a successful AML/CTF system.
Much can be learned through the exchange of non-classified data and increased levels
of communication and exchange of ideas between intelligence and law enforcement
agencies, financial investigation units, researchers and the private sector at nat ional
Modelling ML
and terrorism
financing
317
To continue reading
Request your trial