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Attempts to Dodge Drowning in Data: Rule- and Risk-Based Anti Money Laundering Policies Compared

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  • B. Unger
  • F. van Waarden

Abstract

Both in the US and in Europe anti money laundering policy switched from a rule-to a risk-based reporting system in order to avoid over-reporting by the private sector. However, reporting increased in most countries, while the quality of information decreased. Governments drowned in data because private agents feared sanctions for not reporting. This ‘‘crying wolf’ problem’ (Takats 2007) did not happen in the Netherlands, where the number of reports diminished but information quality improved. Reasons for this can be found in differences in legal institutions and legal culture, notably the contrast between US adversarial legalism and Dutch cooperative informalism. The established legal systems also provide for resistance to change. Thus lowering sanctions in order to reduce over-reporting may not be a realistic option in a legal system which traditionally uses deterrence by fierce criminal and private legal sanctions. Furthermore, a risk-based approach may not be sustainable in the long run, as litigation may eventually replace a risk-based approach again by a rule-based one, now with precise rules set by the courts.

Suggested Citation

  • B. Unger & F. van Waarden, 2009. "Attempts to Dodge Drowning in Data: Rule- and Risk-Based Anti Money Laundering Policies Compared," Working Papers 09-19, Utrecht School of Economics.
  • Handle: RePEc:use:tkiwps:0919
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    File URL: https://dspace.library.uu.nl/bitstream/handle/1874/309920/09_19_2.pdf
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    References listed on IDEAS

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    Cited by:

    1. Loayza, Norman & Villa, Edgar & Misas, Martha, 2019. "Illicit activity and money laundering from an economic growth perspective: A model and an application to Colombia," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 442-487.
    2. Stefan Haigner & Friedrich Schneider & Florian Wakolbinger, 2012. "Combating Money Laundering and the Financing of Terrorism: A Survey," Economics of Security Working Paper Series 65, DIW Berlin, German Institute for Economic Research.
    3. Rasmus Ingemann Tuffveson Jensen & Joras Ferwerda & Christian Remi Wewer, 2023. "Searching for Smurfs: Testing if Money Launderers Know Alert Thresholds," Papers 2309.12704, arXiv.org.
    4. Raffaella Barone & Donato Masciandaro, 2011. "Organized crime, money laundering and legal economy: theory and simulations," European Journal of Law and Economics, Springer, vol. 32(1), pages 115-142, August.
    5. Lucia Pellegrina & Giorgio Maio & Donato Masciandaro & Margherita Saraceno, 2023. "Are Bankers “Crying Wolf”? Type I, Type II Errors and Deterrence in Anti-Money Laundering: The Italian Case," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(2), pages 587-615, July.
    6. Mario Gara & Claudio Pauselli, 2020. "Looking at ‘Crying Wolf’ from a Different Perspective: An Attempt at Detecting Banks Under- and Over-Reporting of Suspicious Transactions," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 299-324, July.
    7. Joras Ferwerda & Ioana Sorina Deleanu & Brigitte Unger, 2019. "Strategies to avoid blacklisting: The case of statistics on money laundering," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-13, June.
    8. Carmela D’Avino, 2023. "Money laundering and AML regulatory and judicial system regimes: investigation of FinCEN files," European Journal of Law and Economics, Springer, vol. 55(2), pages 195-223, April.

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    Keywords

    money laundering; anti money laundering policy; risk based regulation; rules; standards; comparison of legal systems; tort law;
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