indeed suspects. These suspects can than be
subjected to more detailed investigation. Rather than
profiling all customers, this approach focuses on a
small percentage of customers that is relevant. Early
2007, the Dutch government started a pilot using this
approach regarding their surveillance on legal
persons (Dutch Ministry of Justice, 2006).
Obviously it is very important to use very
sophisticated profiles to prevent particular terrorist
funds from being out of scope. Furthermore, the risk
profiles should be handled with care, because they
may be very stigmatising for particular groups in
society (Harvey, 1990).
Note that this targeted approach requires changes
in the current KYC legislation. Most KYC
requirements stem from US legislation, but it is
important to note that several European countries
have already implemented similar legislation that
makes it mandatory for financial institutions to
identify and profile their clients. Since most of this
legislation is less than a year old, it is neither likely
nor desirable to implement changes immediately.
However, careful evaluation of the current legal
framework and best practices may be useful to
reveal further lessons to be learned.
Obviously, the current approach raises many
issues related to privacy and data protection.
Collecting and processing data of all clients involves
the use of personal data of innocent people, often
without informing data subjects and without their
consent. Using a targeted approach, much less
personal data is required, i.e., only personal data of
the people involved initially showing increased risk.
This may result in fewer violations of (European)
data protection laws (Bygrave, 2002).
Whatever method is used, tracking money
laundering and terrorism funding is ultimately based
on human intuition for a significant part. There are
all kinds of technological possibilities to gain insight
into large amounts of data stored in databases, for
instance, searching for patterns and relations in
databases, often referred to as KDD, ‘Knowledge
Discovery in Databases’ (Piatetsky-Shapiro and
Frawley, 1993). Creating risk profiles may also be
automated to some extent. However, it remains
difficult to get a good understanding of who an
individual is and what his intentions are if only data
in databases is used. Since data can be manipulated
too easily, tracing money laundering and terrorism
funding has to rely on clever searching combined
with some intuition and experience.
REFERENCES
Anderson, R.J., 2001, Security Engineering; a guide to
building dependable distributed systems. New York:
John Wiley & Sons, Inc.
Baker, S., Kuilwijk, K., Chang, W., and Mah, D., 2003,
Anonymization, Data-Matching and Privacy: A Case
Study. Washington DC: Steptoe & Johnson LLP,
Attorneys at Law.
BSA, 1970, US Banking Secrecy Act, 1970,
<http://www.federalreserve.gov/boarddocs/supmanual
/bsa/7-00bsaman.pdf>
Bygrave, L.A., 2002, Data protection law; approaching
its rationale, logic and limits, Information Law Series
10, The Hague, London, New York: Kluwer Law
International.
Comptrollers Handbook, 2000, Bank Secrecy Act/Anti-
Money Laundering, Comptroller of the Currency,
Administrator of National Banks, US Department of
the Treasury.
<http://www.occ.treas.gov/handbook/bsa.pdf>
Custers, B.H.M., 2003, Effects of Unreliable Group
Profiling by Means of Data Mining. In: G. Grieser, Y.
Tanaka and A. Yamamoto (eds.) Lecture Notes in
Artificial Intelligence, Proceedings of the 6th
International Conference on Discovery Science (DS
2003) Sapporo, Japan. Berlin, Heidelberg, New York:
Springer-Verlag, Vol. 2843, p. 290-295.
Custers, B.H.M., 2004, The Power of Knowledge; Ethical,
Legal and Technological Aspects of Data Mining and
Group Profiling in Epidemiology, Tilburg: Wolf Legal
Publishers.
Custers, B.H.M., Risicoprofilering en identificatie van
terreurfondsen, Banking Review, October 2006, p. 28-
33.
Dutch Ministry of Justice, 2006, Snel en Secuur Toetsen;
het alternatief voor de verklaring van geen bezwaar.
Bijlage bij het eindrapport interdepartementale
werkgroep Toezicht Rechtspersonen, Niet-dossierstuk
just050263.
Harvey, J., 1990, Stereotypes and Group-claims;
epistemological and moral issues, and their
implications for multi-culturalism in education,
Journal of Philosophy of Education, Vol. 24, No. 1, p.
39-50.
OFAC List, 2006 <http://www.ustreas.gov/
offices/enforcement/ofac/sdn/t11sdn.pdf>
Patriot Act, 2006 <http://www.epic.org/
privacy/terrorism/hr3162.html>
Piatetsky-Shapiro, G., and Frawley. W.J., 1993,
Knowledge Discovery in Databases, Menlo Park,
California: AAAI Press/The MIT Press.
Simpson, G.R., How Top Dutch Bank Plunged into World
of Shadowy Money, Wall Street Journal, 30th
December 2005, p. A1.
Schneier, B., 2000, Secrets and Lies; digital security in a
networked world, New York: Wiley Computer
Publishing.
US Sanctions list, 2006 <http://www.ustreas.gov/
offices/enforcement/ofac/programs/>
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