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13EUROC0 - PAP4 - Money Laundering and Illicit Finance
Session Type: Pre-Arranged Panel
Category: 13. Organizational Crime (ESC WG) (EUROC)
Session Details
Money Laundering and Illicit Finance
This panel includes diverse presentations that are connected to each other by the broad theme of money laundering. The panel starts with a presentation by Colin King on Non-Fungible Tokens (NFTs), which popularity and usage in various areas has increased rapidly. While the NFT sales of the first ever twitter message or a cryptopunk worth millions of dollars score headlines, NFTs are also finding practical uses in other areas such as real estate or gaming. Colin will present the findings of an empirical study exploring issues relating to NFTs as ‘art’, their use in money laundering, and challenges of compliance faced by art dealers. The second presentation is provided by Katie Benson and focusses on the concepts of ‘money laundering’ and ‘illicit finance’. These terms are often used interchangeably and with a lack of clarity around their conceptual boundaries. Katie will reflect on the history and usage of both concepts in policy documents and academic literature and critically analyse their meanings and the problems they pose. The panel will continue with a presentation by Antonio Bosisio on risk assessment of money laundering and illicit corporate behaviour of legitimate businesses. Anomalies in the characteristics of legitimate firms are suggested to signal the risk of involvement in financial crime schemes. Antonio will present a novel approach – based on machine learning techniques – for identifying and measuring these anomalies that are potentially linked to money laundering or other financial crime schemes. The fourth presentation, by Jo-Anne Kramer, focusses on money laundering networks in The Netherlands. If the stakes are high, (drug)criminals often seek help from financial facilitators to launder their money. According to the Financial Action Task Force these facilitators are operating increasingly business-like and can operate in money laundering networks. Jo-Anne will present to what extent financial facilitators in The Netherlands organize themselves in money laundering networks, the extent to which they exhibit business-like characteristics and the relationship between business-like behaviour and the position in the social network.
Authors
Colin King
Institute of Advanced Legal Studies, University of London
Saskia Hufnagel
Queen Mary, University of London
Abstract
Whether cryptocurrencies, smart contracts or non-intermediated peer-to-peer (P2P) lending, FinTech is rapidly changing the world of finance. Consequently, there is growing discussion about the role (or type) of regulation that is (or should be) applied to such developments. For example, the US Infrastructure Investment and Jobs Act 2021 contains provisions governing oversight of cryptocurrencies and brokers, and the UK Money Laundering Regulations 2019 require businesses carrying on ‘cryptoasset activity’ to register with the Financial Conduct Authority.
Another major development in FinTech is non-fungible tokens (NFTs). As unique tokens on the blockchain, NFTs are digital assets that represent real-world objects. While headline sales figures, such as $2.9m for an NFT of the first ever Twitter message, a $23m cryptopunk NFT, or a $69m Beeple NFT, garner attention, NFTs are increasingly finding practical uses in other areas, such as real estate; gaming; charitable donations; sports and music memorabilia; royalty payments; and, in one instance, even to enable brewers and farmers to preserve UNESCO beer heritage. Indeed 2021 was declared to be ‘the year of the NFT and ‘NFT’ even became the ‘word of the year’. There is, however, a darker side to NFTs, with allegations of their use in money laundering, wash trading, rug pull scams, or copyright infringements.
Against this backdrop, this presentation reports findings from an empirical study conducted in 2022, exploring issues relating to NFTs as ‘art’, their use in money laundering, and challenges of compliance faced by art dealers.
Another major development in FinTech is non-fungible tokens (NFTs). As unique tokens on the blockchain, NFTs are digital assets that represent real-world objects. While headline sales figures, such as $2.9m for an NFT of the first ever Twitter message, a $23m cryptopunk NFT, or a $69m Beeple NFT, garner attention, NFTs are increasingly finding practical uses in other areas, such as real estate; gaming; charitable donations; sports and music memorabilia; royalty payments; and, in one instance, even to enable brewers and farmers to preserve UNESCO beer heritage. Indeed 2021 was declared to be ‘the year of the NFT and ‘NFT’ even became the ‘word of the year’. There is, however, a darker side to NFTs, with allegations of their use in money laundering, wash trading, rug pull scams, or copyright infringements.
Against this backdrop, this presentation reports findings from an empirical study conducted in 2022, exploring issues relating to NFTs as ‘art’, their use in money laundering, and challenges of compliance faced by art dealers.
From Money Laundering to Illicit Finance: A Conceptual History and Analysis
Authors
Katie Benson
University of Manchester
Abstract
Since its emergence in the 1980s, the concept of ‘money laundering’ has become firmly entrenched in public, political and policy discourse. In more recent years, the concepts of ‘illicit finance’ and ‘illicit financial flows’ have become prominent. These terms are often used interchangeably and with a lack of clarity around their conceptual boundaries. While both are associated with ideas of ‘dirty’ money and with serious and organised crimes such as drug trafficking and corruption, they have some differences in origin and application. ‘Money laundering’ essentially refers to a process that happens to the proceeds of various predicate crimes and has well-established legal frameworks while ‘illicit finance’ can incorporate a broad spectrum of activity that reflects the blurred boundaries between ‘illicit’ and ‘illegal’. This paper reflects on the history and usage of the concepts of ‘money laundering’ and ‘illicit finance’ in policy documents and academic literature and critically analyses their meanings and the conceptual problems they pose.
Identifying anomalies in the characteristics of legitimate businesses to assess risks of money laundering and illicit corporate behaviour
Authors
Antonio Bosisio
Transcrime - Università Cattolica
Giovanni Niccolazzo
Transcrime - Università Cattolica
Michele Riccardi
Transcrime - Università Cattolica
Abstract
Anti-Money Laundering (AML) regulators suggest that anomalies in the characteristics of legitimate firms can signal the risk of involvement in financial crime schemes. However, few studies have proposed how to effectively measure these anomalies at company level.
The present paper, resulting from the research activities of EU-funded Project DATACROS II, proposes a novel approach - based on machine learning techniques - for identifying and measuring anomalies in the characteristics of legitimate businesses potentially linked to money laundering or other financial crime schemes. Risk indicators are identified starting from the analysis of the relevant literature, investigative evidence, AML principles and guidelines at international level. The indicators are calculated for 750,000 companies registered in Lombardy, taking into account information on: i) ownership structure; ii) territorial exposition; iii) general characteristic of the company; iv) characteristics of key individuals; v) political exposure; vi) negative events; vii) financials.
Results of the empirical analysis suggest that many of these risk factors are interrelated and tend to present themselves in recurring profiles. Furthermore, results show the presence of hot-spots at territorial and sectoral level, in which particular concentrations of risky company can be observed.
The present paper, resulting from the research activities of EU-funded Project DATACROS II, proposes a novel approach - based on machine learning techniques - for identifying and measuring anomalies in the characteristics of legitimate businesses potentially linked to money laundering or other financial crime schemes. Risk indicators are identified starting from the analysis of the relevant literature, investigative evidence, AML principles and guidelines at international level. The indicators are calculated for 750,000 companies registered in Lombardy, taking into account information on: i) ownership structure; ii) territorial exposition; iii) general characteristic of the company; iv) characteristics of key individuals; v) political exposure; vi) negative events; vii) financials.
Results of the empirical analysis suggest that many of these risk factors are interrelated and tend to present themselves in recurring profiles. Furthermore, results show the presence of hot-spots at territorial and sectoral level, in which particular concentrations of risky company can be observed.
Money laundering as a service: investigating business-like behaviour in money laundering networks in The Netherlands
Authors
Jo-Anne Kramer
VU University Amsterdam & Netherlands Institute for the Study of Crime and Law Enforcement (NSCR)
Edward Kleemans
VU University Amsterdam
Arjan Blokland
Netherlands Institute for the Study of Crime and Law Enforcement (NSCR) & Leiden University
Melvin Soudijn
National Police of The Netherlands
Abstract
In a 2018 international report the Financial Action Task Force [FATF] suggests that financial facilitators can operate in professional money laundering networks. Financial facilitators provide services to criminals that are essential for transferring large amounts of money from the illegal to the legal economy. When the stakes are high, (drug)criminals often seek help from financial facilitators to launder their money. According to the FATF, these facilitators are operating increasingly business-like, offering their services in return for a fee.
This study examines the extent to which financial facilitators in The Netherlands organize themselves in money laundering networks and the extent to which they exhibit business-like characteristics. We further examine the relationship between business-like behaviour and the position in the social network.
Using police intelligence data we were able to analyze the contacts of 198 financial facilitators who were active in The Netherlands in the period 2016-2020, all having worked for drug criminals. We performed a social network analysis to examine whether and to what extent financial facilitators in The Netherlands form money laundering networks. Further, we studied the number of cases and (returning) criminal contacts of facilitators to typify them in terms of business-like behaviour. We applied regression models to predict business-like behaviour using individual network measures.
This research shows that financial facilitators in The Netherlands can be linked in extensive money laundering networks. As part of the facilitators behave strongly business-like, this study also shows that facilitators with more central positions in the network tend to behave more business-like.
This study examines the extent to which financial facilitators in The Netherlands organize themselves in money laundering networks and the extent to which they exhibit business-like characteristics. We further examine the relationship between business-like behaviour and the position in the social network.
Using police intelligence data we were able to analyze the contacts of 198 financial facilitators who were active in The Netherlands in the period 2016-2020, all having worked for drug criminals. We performed a social network analysis to examine whether and to what extent financial facilitators in The Netherlands form money laundering networks. Further, we studied the number of cases and (returning) criminal contacts of facilitators to typify them in terms of business-like behaviour. We applied regression models to predict business-like behaviour using individual network measures.
This research shows that financial facilitators in The Netherlands can be linked in extensive money laundering networks. As part of the facilitators behave strongly business-like, this study also shows that facilitators with more central positions in the network tend to behave more business-like.
13EUROC0 - PAP4 - Money Laundering and Illicit Finance
Description
Please only choose to join as an attendee if you are NOT a speaker.Session Chair
Jo-Anne Kramer
22/9/2022, 5:30 PM — 6:45 PM