Technology and Anti-Money Laundering

Technology and Anti-Money Laundering

A Systems Theory and Risk-Based Approach

Dionysios S. Demetis

This insightful book examines the influence of information systems on anti-money laundering (AML). It builds on systems theory in order to develop a coherent theoretical framework that can be used for AML research.

Chapter 3: On Systems Theory

Dionysios S. Demetis

Subjects: economics and finance, economic crime and corruption, money and banking, innovation and technology, technology and ict, law - academic, corruption and economic crime, internet and technology law, terrorism and security law, politics and public policy, terrorism and security


INTRODUCTION This chapter essentially constitutes a first step in presenting a coherent theoretical framework that can be applied to anti-money laundering research. Even though some key ideas are presented here, systems theoretical inferences and further theoretical development takes place in Chapter 5. This work is based on a number of research papers the author has published on the application of systems theory to the problem domain of AML (Angell and Demetis, 2005, Demetis and Angell, 2006, Demetis, 2009, Demetis and Angell, 2007). However, it is only in the scope of a book that the theoretical background can be laid down in more detail and the concepts surrounding systems theory further elaborated. Anti-money laundering is a demanding research domain that is interdisciplinary in its core. As a research area, it draws researchers from a wide number of fields. Researchers that have a legal background examine the interferences and consequences of law on AML across various nations, as well as bilateral and multilateral treaties. Researchers that have a social sciences and/or economics background usually attempt to examine the provenances and effects of AML or draw its micro- and macro-economic implications. Researchers that come from the natural sciences (for example physics or mathematics) participate in the formulation of mathematical models that can be computationally integrated for the modelling of ML activities (that is profiling) or investigate – numerically – the size of the ML market through statistical analyses and mathematical modelling. But while it is apparent that AML draws a wide number of researchers from...

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