Money laundering using
Mohammed Ahmad Naheem
Seven Foundation, Zurich, Switzerland
Purpose – This paper aims to start with the assumption that money laundering through the use of
investments will continue to occur and will become increasingly more complex to try and avoid
detection. The paper aims to explore some of the theoretical factors that would need to be considered in
any risk based framework and also to consider how an empirical model can try and prioritise the
information and intelligence gathered through existing benecial ownership and customer due
diligence (CDD) systems.
Design/methodology/approach – This paper uses an empirical example of money laundering with
investments and highlights the red ag indicators that led to its eventual discovery. The theoretical
framework considers the difculties of information overload and suggests that any empirical model of
risk-based assessment would need to be able to discern between the various types of risk information
gathered. The paper has developed one empirical model that could be used.
Findings – The paper suggests a model that breaks down benecial ownership and CDD information
into three areas: benecial ownership for all major players, transparency of transactions and
accountability of companies involved.
Practical implications – The paper has implications for the banking, regulatory and law
enforcement sectors working in Anti-Money Laundering (AML).
Originality/value – The paper analyses a particular type of money laundering activity which it terms
“investment laundering” using an empirical case study. It then develops a new theoretical and empirical
risk assessment model to illustrate how risk-based approaches need to be able to discern between the
different types of information gathered and the application to overall risk.
Keywords Money laundering, Benecial ownership, CDD, Investment laundering,
Risk based assessment
Paper type Case study
Over recent years, money laundering has become a key area of focus for risk assessment
within the banking sector (AUSTRAC, 2013). Within the area of nancial crime money
laundering (ML) is recognised as possibly the biggest major problem, and constitutes
the third largest “business” in the world (Le-Khac and Kechadi, 2014). Money laundering
has an estimated value of approximately 2-5 per cent of the world’s gross domestic
The author acknowledges being the recipient of a research grant awarded by Princess
Alae as part
of Seven Foundation’s “2020 Banking Vision – building banks of the future”, and the author
thanks her for the continued support and motivation both to himself and other students who
benet through her generosity (www.sevenfoundation.ch).
The author also thanks Professor Muhammad Jum‘ah (a leading economist of this era based in
Damascus) who has continued to provide valuable input both through his teaching of the science
of economics and for his continued guidance.
The current issue and full text archive of this journal is available on Emerald Insight at:
Journalof Money Laundering
Vol.18 No. 4, 2015
©Emerald Group Publishing Limited