Economic and Legal Effectiveness of Anti-Money Laundering

510 Pages·2013·8.69 MB·English

Final Delivery to the EU
February 2013
Project ‘ECOLEF’
The Economic and Legal
Effectiveness of Anti-
Money Laundering and
Combating Terrorist
Financing Policy

Final Report

Project funded by the European Commission
DG Home Affairs
JLS/2009/ISEC/AG/087
February 2013
Project ‘ECOLEF’
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The Economic and Legal Effectiveness of Anti-Money
Laundering and Combating Terrorist Financing Policy

Research performed by Utrecht University (NL)

The ECOLEF Team

Project leader: Prof. Dr. Brigitte Unger (UU)

Prof. Dr. Henk Addink (UU)
Ass. Prof. John Walker (WU) BSc (Eon) Lond., ASM
Ass. Prof. Dr. Joras Ferwerda MSc (UU)
PhD cand. Melissa van den Broek LLM (UU)
PhD cand. Ioana Deleanu MSc (UU)

Illustration on cover:
Object made by Peter Bastiaanssen, website: http://www.artisadog.nl

© 2013 Utrecht University, the Netherlands

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Preface

Anti-Money Laundering and Combating Terrorism Financing Policy is now about 25 years
old. Many actors have been involved, many efforts have been made and much money has
been invested in this policy area. It seems time to stand still for a moment and to
investigate, whether all these efforts and costs have had a positive effect. Have the legal
efforts reached their intended goals? And have the investment in police, public
prosecution, reporting systems and supervision had a positive impact on combating
laundering and terrorist financing? The following study, ECOLEF, the Economic and Legal
Effectiveness of Anti-Money Laundering and Combating Terrorism Financing assesses anti-
money laundering policy for the 27 EU Member States.

The ECOLEF study also aimed at improving the attention given to the AML/CTF policy in
the academic world. Following this study, two PhD researches are underway and one is
just published. In December 2012 Joras Ferwerda defended his thesis named ‘The
Multidisciplinary Economics of Money Laundering’, which shows what and how an
economist can contribute in a multidisciplinary fashion to the research field of money
laundering (policy). Ioana Deleanu investigates which information transmission chains
enable the efficient cooperation of the FIUs, the law enforcement agencies and the
judiciary in the context of the AML repressive policy of the European Union. Her PhD
research is due to finish by the end of 2014. Melissa van den Broek is doing a comparative
legal study on the effectiveness of supervision and enforcement regimes in the preventive
AML/CTF policy within the European Union. The research is expected to be finished by the
end of 2014.

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Table of Contents

Preface ...................................................................................................... 3
Tables & Figures .................................................................................................... 6
Acknowledgements ............................................................................................... 10
Acronyms and Abbreviations .................................................................................. 11
Executive Summary .............................................................................................. 12
Chapter 1 INTRODUCTION .............................................................................. 29
Chapter 2 THREAT OF MONEY LAUNDERING ..................................................... 34
Chapter 3 OPERATIONALISATION OF POLICY RESPONSE .................................... 58
Chapter 4 HARMONISATION OF SUBSTANTIVE NORMS AND THE DELOITTE
STUDY .......................................................................................... 62
Chapter 5 TIME DELAYS IN IMPLEMENTING THE THIRD DIRECTIVE ..................... 95
Chapter 6 SUPERVISORY ARCHITECTURES ..................................................... 103
Chapter 7 DEFINITIONS OF MONEY LAUNDERING AND TERRORIST
FINANCING IN PRACTICE .............................................................. 127
Chapter 8 THE ROLE OF FIUs ........................................................................ 138
Chapter 9 INFORMATION FLOWS AND REPRESSIVE ENFORCEMENT ................... 164
Chapter 10 INTERNATIONAL COOPERATION ..................................................... 221
Chapter 11 COLLECTION OF STATISTICS ......................................................... 243
Chapter 12 EFFECTIVENESS: THREAT AND CORRESPONDING POLICY
RESPONSE ................................................................................... 270
Chapter 13 COST-BENEFIT ANALYSIS ............................................................. 282
Chapter 14 CONCLUSIONS AND POLICY RECOMMENDATIONS ............................ 305
Reference List .................................................................................................. 311
Glossary .................................................................................................. 322

Annex 0 PROGRAM FINAL CONFERENCE ...................................................... 326
Annex 1.1 SURVEYS ..................................................................................... 328
Annex 1.2 INTERVIEWS ................................................................................ 332
Annex 1.3 PARTICIPANTS ............................................................................. 337
Annex 2.1 CLASSIFICATION OF THREAT VARIABLES ........................................ 339
Annex 2.2 DESCRIPTION, SOURCES AND SIGNS OF THREAT VARIABLES ............ 341
Annex 2.3 CALCULATED BRETTL-USOV THREAT SUB-INDICES ACCORDING
TO ML OFFENCES ......................................................................... 345
Annex 2.4 IMF TA RISK MODULES ................................................................. 350
Annex 4.1 IMPROVEMENTS, UPDATES AND NUANCES TO THE DELOITTE
STUDY (PER MS) .......................................................................... 355
Annex 4.2 FULL TABLE ON AML/CTF REPORTING SYSTEMS IN THE EU ................ 362
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Annex 4.3 FULL TABLE ON LEGAL PRIVILEGE-EXEMPTIONS IN MS’ AML/CTF
LEGISLATION ............................................................................... 375
Annex 6.1 DESCRIPTIONS OF AML/CTF SUPERVISORY ARCHITECTURES PER
MEMBER STATE ............................................................................ 379
Annex 7.1 CASE STUDIES ............................................................................. 394
Annex 7.2 CRIMINALISATION OF MONEY LAUNDERING (UNOFFICIAL
TRANSLATION)............................................................................. 397
Annex 7.3 CRIMINALISATION OF TERRORIST FINANCING (UNOFFICIAL
TRANSLATIONS) ........................................................................... 426
Annex 8.1 ORGANISATIONAL PATTERNS OF THE EU FIUS ................................. 448
Annex 8.2 ADDITIONAL TASKS OF THE FIUs ................................................... 455
Annex 8.3 EU FIUs ACCES TO DATA IN DETAIL................................................ 463
Annex 8.4 DATA MINING SYSTEM AND FIU CAPACITY TO FILTER FAST IN
DETAIL ........................................................................................ 470
Annex 8.5 FEEDBACK IN DETAIL .................................................................... 475
Annex 9.1 INFORMATION FLOW CALCULATIONS .............................................. 482
Annex 9.2 CRIMINAL PUNISHMENTS FOR ML OFFENCES IN THE 27 EU MS.......... 483
Annex 9.3 CRIMINAL PUNISHMENTS FOR TF OFFENCES IN THE 27 EU MS .......... 488
Annex 9.4 CORRUPTION AND GOOD GOVERNANCE COUNTRY INDICES .............. 489
Annex 9.5 ORIGINS OF CRIMINAL LAW IN THE EU MS ...................................... 490
Annex 11.1 STATISTICS ................................................................................. 492
Annex 12.1 FACTOR ANALYSIS FOR POLICY RESPONSE TOWARDS MONEY
LAUNDERING ............................................................................... 507
Annex 12.2 DIMENSIONS OF AML/CTF POLICY RESPONSE .................................. 508
Annex 13.1 COST-BENEFIT ANALYSIS .............................................................. 509

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Tables & Figures

Figure 1.1: Building blocks of the ECOLEF Study ..................................................................... 29
Figure 1.2: Member States’ Participation at the Four Regional ECOLEF Workshops .............. 31
Figure 1.3: Improvements, updates and nuances to the Deloitte study ................................. 32

Table 2.1: Most prevalent crime types generating launderable proceeds ............................ 34
Table 2.2: Estimates of % of Proceeds Laundered, by Crime Type ........................................ 38
Table 2.3: Estimates of Launderable Money in 2009, by Country in which Generated ......... 39
Table 2.4: EU Countries by Estimated Threat in 2009 ............................................................. 43
Figure 2.1: Mapping of threat ................................................................................................. 44
Table 2.5: EU Countries by Estimated Threat as % of GDP in 2009......................................... 45
Figure 2.2: EU Countries by Estimated Threat as % of GDP .................................................... 45
Table 2.6: Classification of threat Variables According to ML Offences ................................. 51
Figure 2.3: Algorithm of assigning Threat Scores .................................................................... 51
Figure 2.4: Overall ML Threat Indices for EU 27, 2010 ............................................................ 53
Table 2.7: Overall ML threat indexes of EU 27 for 2010 ......................................................... 53
Figure 2.5: Comparison of Walker’s and Brettl-Usov results .................................................. 55
Table 2.8: Risk level scores ...................................................................................................... 56

Figure 3.1: Building blocks of the ECOLEF Study ..................................................................... 58
Figure 3.2: Visual representation of legal and economic effectiveness .................................. 59

Table 4.1: Improvements, updates and nuances to the Deloitte study per Member State ... 62
Table 4.2: Improvements, nuances and updates per topic ..................................................... 63
Table 4.3: Top-10 Extensions to scope of obliged institutions ................................................ 65
to other high-risk institutions than required by FATF/EU ....................................................... 65
Table 4.4: AML/CTF reporting systems in the EU .................................................................... 68
Table 4.5: Legal privilege-exemptions in Member States’ AML/CTF legislation ..................... 77
Table 4.6: Legal hindrances of substantive norms in preventive AML/CTF policy .................. 86

Figure 5.1: Implementation delays .......................................................................................... 97

Table 6.1: AML/CTF supervisory architectures illustrated .................................................... 108
Figure 6.1: AML/CTF Supervisory Architectures in the EU .................................................... 109
Table 6.2: Resource tensions for FIUs ................................................................................... 112
Table 6.3: Strengths and weaknesses of the supervisory models ......................................... 125

Table 7.1: Results case study 1 – Money laundering ............................................................ 128
Table 7.2: Definitions of Money Laundering ......................................................................... 133
Table 7.3: Results of case study 1 – terrorist financing ......................................................... 135

Figure 8.1: IMF classification of the EU FIUs ......................................................................... 139
Table 8.1: IMF/Egmont classification .................................................................................... 140
Figure 8.2: EU FIU classification ............................................................................................. 141
Table 8.2: FIU budget size, independence and vulnerability to fiscal shocks ....................... 145
Table 8.3: FIU staff size, staff composition and FIU location premises ................................. 146
Table 8.4: Additional tasks of the FIU .................................................................................... 151
Table 8.5: FIUs that have undergone a significant organisational change ............................ 152
Table 8.6: EU FIU access to police, real estate, bank, social security, customs, tax and
commercial databases ........................................................................................................... 154
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Table 8.7: FIU starts an analysis/investigation based on reports, own motion,foreign FIU
requests ................................................................................................................................. 155
Table 8.8: FIU receipt of reports and first analysis ................................................................ 159
Table 8.9: FIU feedback to the reporting entities ................................................................. 161

Figure 9.1: Punishments imposed in each MS in relationship to ML and TF in years of prison
detention ............................................................................................................................... 167
Figure 9.2: Information flow chains – 4 main typologies ...................................................... 169
Table 9.1: Comparing information flow chain types in terms of the network information
values ..................................................................................................................................... 173
Figure 9.3: AML/CTF Information flows in Austria ................................................................ 175
Figure 9.4: AML/CTF Information flows in Belgium .............................................................. 177
Figure 9.5: AML/CTF Information flows in Bulgaria .............................................................. 178
Figure 9.6: AML/CTF Information flows in Cyprus ................................................................ 180
Figure 9.7: AML/CTF Information flows in the Czech Republic ............................................. 181
Figure 9.8: AML/CTF Information flows in Denmark ............................................................. 183
Figure 9.9: AML/CTF Information flows in Estonia ................................................................ 183
Figure 9.10: AML/CTF Information flows in Finland .............................................................. 184
Figure 9.11: AML/CTF Information flows in France ............................................................... 186
Figure 9.12: AML/CTF Information flows in Germany ........................................................... 188
Figure 9.13: AML/CTF information flows in Greece .............................................................. 190
Figure 9.14: AML/CTF Information flows in Hungary ............................................................ 191
Figure 9.15: AML/CTF Information flows in Ireland .............................................................. 193
Figure 9.16: AML/CTF Information flows in Italy................................................................... 195
Figure 9.17:AML/CTF Information flows in Latvia ................................................................. 196
Figure 9.18: AML/CTF Information flows in Lithuania ........................................................... 197
Figure 9.19: AML/CTF Information flows in Luxembourg ..................................................... 198
Figure 9.20: AML/CTF Information flow in Malta .................................................................. 199
Figure 9.21: AML/CTF Information flows in the Netherlands ............................................... 201
Figure 9.22: AML/CTF information flows in Poland .............................................................. 203
Figure 9.23: AML/CTF Information flows in Portugal ............................................................ 205
Figure 9.24: AML/CTF information flows in Romania ........................................................... 206
Figure 9.25: AML/CTF information flows in Slovenia ............................................................ 208
Figure 9.26: AML/CTF information flows in the Slovak Republic .......................................... 210
Figure 9.27: AML/CTF Information flows in Spain ................................................................. 211
Figure 9.28: AML/CTF Information flows in Sweden ............................................................. 212
Figure 9.29: AML/CTF Information flows in the United Kingdom ......................................... 213
Figure 9.30: Information flows across the EU ....................................................................... 215
Figure 9.31: Effective repression scores across the EU ......................................................... 216

Table 10.1: Principal international Conventions ................................................................... 223
Figure 10.1: International cooperation channels .................................................................. 232
Table 10.2: Response times indicated by FIUs themselves ................................................... 236
Table 10.3: Countries to which FIUS send most requests and receive most requests from. 239
Figure 10.2: Patterns of international cooperation among the EU FIUs ............................... 241

Table 11.1: Average number of reports per year sent to the FIU ......................................... 244
Table 11.2: Number of persons and amount of money related to the reports sent to the FIU
............................................................................................................................................... 249
Table 11.3: Number of (false) cash declarations and the amount of money involved. ........ 250
Table 11.4: Average number of prosecutions and convictions for money laundering and
terrorist financing .................................................................................................................. 252
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Table 11.5: The conviction rates classified by broadness of the ML definition .................... 254
Table 11.6: Number of staff and budget of the FIU .............................................................. 258
Table 11.7: Budget FIU .......................................................................................................... 260
Table 11.8: Number of staff and budget of the FIU .............................................................. 261
Table 11.9: The selected variables for cluster analysis ........................................................ 263
Figure 11.1: The result of the cluster analysis depicted in a dendrogram ............................ 265
Table 11.10: Identified groups by the statistical cluster analysis .......................................... 265
Figure 11.2: Identified groups by the statistical cluster analysis........................................... 266
Table 11.11: Characteristics of the countries within the groups .......................................... 267

Figure 12.1: Exploratory approach to compare ML threat with policy response ................ 271
Figure 12.2: Visual representation of threat vs. FATF Compliance Score ............................. 272
Figure 12.3: Visual representation of threat vs. Legal effectiveness .................................... 274
Figure 12.4: Visual representation of threat vs. Implementation timeliness ....................... 275
Figure 12.5: Visual representation of threat vs. FIU response score .................................... 276
Figure 12.6: Visual representation of threat vs. International cooperation ......................... 277
Figure 12.7: Visual representation of threat vs. Information flow score .............................. 278
Figure 12.8: Visual representation of threat vs. Number of ML convictions ........................ 279
Table 12.1: Overview of the extent to which the policy response of EU Member States is
proportional to the threat ..................................................................................................... 280

Table 13.1: The components of a cost-benefit analysis for AML .......................................... 283
Table 13.2: Budget and staff of the relevant ministry or ministries ..................................... 285
Table 13.3: Statistics collected on the number of staff and the budget of FIU .................... 286
Table 13.4: Statistics collected on the number of employees and the budget of supervisors
............................................................................................................................................... 288
Table 13.5: Statistics collected on the number of employees and budget for LEAs and
Judiciary ................................................................................................................................. 290
Table 13.6: Statistics collected on the average imprisonment for money laundering and
terrorist financing .................................................................................................................. 292
Table 13.7: Statistics collected on the institutional costs of AML/CTF ................................. 294
Table 13.8: Fines for money launderers and terrorist financiers .......................................... 297
Table 13.9: Confiscation statistics for ML and TF .................................................................. 299
Table 13.10: The effects of money laundering as mentioned in the literature .................... 301
Table 13.11: Estimates for the annual costs and benefits of AML/CTF policy ...................... 303
Table 13.12: Estimates for the annual costs and benefits of AML/CTF policy for each country
and the whole EU .................................................................................................................. 304

Table A1.1: Surveys answered for the ECOLEF project ......................................................... 328
Table A1.2: Interviews conducted for the ECOLEF project.................................................... 332
Table A1.3: List of Participants at the Regional ECOLEF workshops ..................................... 337

Table A2.1: Classification of threat variables ........................................................................ 339
Figure A.2.3.1: Calculated Brettl-Usov ML threat index for drug crimes .............................. 345
Table A.2.3.1: Calculated Brettl-Usov ML threat index for drug crimes ............................... 345
Figure A.2.3.2: Calculated Brettl-Usov ML threat index for other blue collar crimes ........... 346
Table A.2.3.2: Calculated Brettl-Usov ML threat index for other blue collar crimes ............ 346
Figure A.2.3.3: Calculated Brettl-Usov ML threat index for bribery and corruption ............ 347
Table A.2.3.3:Calculated Brettl-Usov ML threat index for bribery and corruption ............... 347
Figure A.2.3.4: Calculated Brettl-Usov ML threat index for white collar crimes ................... 348
Table A.2.3.4: Calculated Brettl-Usov ML threat index for white collar crimes .................... 348
Figure A.2.3.5: Calculated Brettl-Usov ML threat index for terrorism .................................. 349
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Table A.2.3.5: Calculated Brettl-Usov ML threat index for terrorism ................................... 349
Table A.2.4: Preliminary risk modules of the ML threat assessment of the IMF .................. 350

Table A.4.1: Improvements, updates and nuances to the Deloitte Study ............................ 355
Table A.4.2: Full table on AML/CTF reporting systems in the EU .......................................... 362

Table A.9.1.1: Star network ................................................................................................... 482
Table A.9.1.2: Cluster Judicial network ................................................................................. 482
Table A.9.1.3: Cluster Police network ................................................................................... 482
Table A.9.1.4: Linear network ............................................................................................... 482
Table A9.4: Institutional measurements of corruption control and government effectiveness
............................................................................................................................................... 489

Table A.11.1.1: STRs .............................................................................................................. 492
Table A.11.1.2: SARs .............................................................................................................. 493
Table A.11.1.3: UTRs .............................................................................................................. 494
Table A.11.1.4: CTRs .............................................................................................................. 495
Table A.11.1.5: STRs, SARs, and UTRs together .................................................................... 496
Table A.11.1.6: Reports on Terrorist Financing ..................................................................... 497
Table A.11.1.7:Statistics collected on the institutional costs of AML/CTF ............................ 498
Table A.11.1.8: Statistics collected on the inputs for AML/CTF policy .................................. 499
Table A.11.1.9: Number of Prosecutions for Money Laundering .......................................... 501
Table A.11.1.10: Number of Prosecutions for Terrorist Financing ........................................ 502
Table A.11.1.11: Number of Persons involved in Money Laundering Prosecutions ............. 503
Table A.11.1.12: Number of Persons involved in Terrorist Financing Prosecutions ............. 504
Table A.11.1.13: Number of Convictions for Money Laundering .......................................... 505
Table A.11.1.13: Number of Convictions for Terrorist Financing .......................................... 506

Table A13.1.1: Correction factors to correct country statistics to our hypothetical country 509

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