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Estimating the Illicit Flows – Asking the Right Questions

Estimating the Illicit Flows – Asking the Right Questions. John Walker CEO, John Walker Crime Trends Analysis Principal Research Fellow, Centre for Transnational Crime Prevention, University of Wollongong, Australia. Illicit Financial Flows .

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Estimating the Illicit Flows – Asking the Right Questions

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  1. Estimating the Illicit Flows – Asking the Right Questions John Walker CEO, John Walker Crime Trends Analysis Principal Research Fellow, Centre for Transnational Crime Prevention, University of Wollongong, Australia

  2. Illicit Financial Flows • Put simply, Illicit Financial Flows from Developing Countries consist of quantities of money derived from crimes committed in those countries. • Official definitions of crime vary between countries, although there is consensus about most forms of crime. • Contentious areas include business practices considered as fraudulent in some countries but not in others (e.g. payments of bribes and false invoicing), and some areas of excise avoidance (e.g. cigarette smuggling). • This paper takes a broad view that acts that would be crimes or illegal business practices in countries with sophisticated legal systems must also be regarded as crimes or illegal business practices in developing countries. • Illicit Financial Flows from Developing Countries are, therefore, part of the broader issue of transnational crime and moneylaundering.

  3. Asking the Right Questions about Transnational Crime and Moneylaundering • It is difficult to explain the importance of a problem without quantifying it. (Neil Jensen, Director, AUSTRAC, 2005) • FinCen’s “overriding objective” under the strategic plan is the development of a “viable model for measuring the magnitude of moneylaundering.” “No assessment of an agency’s or government’s anti-moneylaundering programs can be a true gauge of its effectiveness, unless it is based on an understanding of the breadth of the problem being addressed”. (FinCEN Strategic Plan, 2000) • “The government are very keen on amassing statistics. They collect them, add them, raise them to the nth power, take the cube root, and prepare wonderful diagrams. But you must never forget that every one of these figures comes, in the first instance, from the village watchman, who just puts down what he damn pleases”. (English economist Sir Josiah Stamp, 1929) • "Striving for perfection is the greatest stopper there is... It's your excuse to yourself for not doing anything. Instead, strive for excellence, doing your best." (British actor, Sir Laurence Olivier) • “…..blending dodgy data and heroic assumption and turning them into something particularly useful” (Dutch criminologist, Max Kommer) • “Accuracy is meaningless – credibility is everything”. (Me)

  4. How Much Profit is there in the Crime ? What Proportion of the Profits is Laundered ? Where does it go for Laundering ? How does it impact on Society ? The Right Questions about Transnational Crime and Moneylaundering How Much Crime is there ?

  5. These are Veryimportant Questions • 1. How much crime is there around the world, and where is it based? • 2. How big are crime profits around the world, and where are they generated? • 3. What factors make crime more profitable in some countries than others? • 4. What factors make some countries more attractive to ML than others? • 5. How much money is laundered each year around the world? • 6. How much harm is caused by crime and ML, and who suffers most?

  6. So who is asking them? Up to the 1980s • Most countries compile crime statistics. Only measures recorded crime. Accuracy doubts; rigging by police, politicians; counting rules. • Interpol collects crime data from member countries – no consistency, no analysis, not even computerised until the late 1990s. Only measures recorded crime. • Crime Victims Surveys developed in the 1970s (USA, UK) to capture data on a common set of definitions and on unrecorded crime. Limited crime types, costly, political risk, little interest in other countries. • In the 1980s, the U.N. attempted to compile international crime and justice statistics on a common set of definitions – very problematic, poor response, little consistency, poorly resourced. • Transnational crime analysis mostly country-specific, offence specific or confined to studies of mafia, yakuza, drug gangs etc • Transparency International experimenting with corruption and bribery indexes.

  7. Measuring the Risks posed by Transnational Crime and Moneylaundering 1988 • United Nations Convention against illicit traffic in narcotic drugs and psychotropic substances; • EU decides to conduct Europe-wide crime survey. Australia, USA, Canada join in. Questions include “did you report it to police?” and “how much did it cost you?” 1989 • FATF Working Group on Statistics and Methods, “Narcotics ML – Assessment of the Scale of the Problem” notes the lack of reliable data to measure ML. 1990 • EU Convention on laundering, search, seizure and confiscation of the Proceeds from Crime. • FATF’s “Forty Recommendations“ on the prevention of money laundering. • U.N. Rome conference agrees to pilot Business Crime survey, including reporting and costs questions. Australia, UK, Netherlands, South Africa. 1991 • EU Directive on prevention of the use of the financial system for purpose of money laundering. 1992 • Estimates of the Costs of Crime in Australia – a model for the U.N. 1995 • Estimates of the Extent of money laundering in Australia – a model for the FATF. 1996-2000 • UN Office on Drugs and Crime • Refinement of International Crime and Justice Surveys, International Crime Victims Surveys, Business Crime Surveys • “Global Report on Crime and Justice” attempts to bring together data on economics of transnational crime • Attempts to survey the characteristics of organised crime groups in different countries

  8. Measuring the Risks posed by Transnational Crime and Moneylaundering June 1997 • FATF creates “Ad Hoc Group on Estimating the Magnitude of Money Laundering” Sept 1997 • Ad Hoc Group’s Chair agrees to draft a paper to suggest methodologies to measure ML – calls for papers from member countries. Feb 1998 • Interim report from Chairman • Identifies AUSTRAC study as a landmark study, examines four macro-economic methodologies identified by FINCEN-sponsored studies, and concludes that future studies should be • [a] confined to FATF members, [b] focused on a wide range of crimes that generate criminal proceeds. Dec 1998 • FATF International Meeting of Experts on Estimating the magnitude of ML • Disappointing level of participation • Most countries’ contributions focused on official statistics • Discussion of relationship between underground economic activity and ML • Switzerland attempts to have the work focus on ML from drug crimes, arguing that crimes involving theft, fraud and corruption are “regarded as simply transfers of wealth”. • Finland paper focuses on fraud. • Australian paper presents complete methodology. • Conclusions: • Need for greater participation from all FATF member countries • Initial focus to be on estimating “the supply and demand for illegal drugs”

  9. The Rich Countries’ Club fails to Deliver • FATF efforts to “estimate the magnitude of ML” failed on 5 key counts: • Focus on incomplete range of crime types – drugs only • Focus on incomplete range of illicit drugs - Cocaine, Marihuana, Heroin only • Focus on incomplete range of countries - rich north-Atlantic countries only • Focus on statistical “purity” • Avoidance of “proceeds of crime” logic • Intended to fail………….? • Need to provoke more constructive discussion.

  10. What next? • Need to provoke discussion, in the absence of any real progress within the UN or FATF. • Can the Australian model be used for other countries around the world?

  11. TC = Total Costs of Crime TP = Total Proceeds of Crime KP = Known Proceeds of Crime TM = Total Money Laundering TE = TotalEconomy TT = Total Terrorist Financing KM = Known Money Laundering Incoming Money Laundering KT = Known Terrorist Financing Costs of crime are part of the Economy. Proceeds of crime are a subset of costs. Some proceeds of crime are laundered, but some laundered money also comes from outside the economy. Terrorist finance may not have criminal origins and is not necessarily laundered. “Known” components are very small subsets of their respective estimated totals. [Not to scale] The 1996 Australian ModelIdentifies Upper and Lower Bounds

  12. Estimates of ML in and through Australia (1996) • Estimates based on Costs of Crime and Expert Survey

  13. Importance of Triangulating with Other Data • Estimates based on Costs of Crime and Expert Survey compared to: • Estimates based on Proceeds of Crime Monitoring • Estimates Based on Understatement of Income Data • Estimates Based on Suspect Financial Transactions • Estimates Based on Flows of Finance through Australian Banks and International Transfers

  14. Overseas Money laundered overseas $US100-500 billion? The Australian Economy $380 billion P.o.C. Costs of Crime $11-21 billion ML Proceeds of Crime Overseas Money laundered in Australia $6-8 billion ML $7.7 billion? $1-4.5 billion Australian Money laundered in Australia Australian Money laundered overseas $5.5 billion? Estimates of ML in and through Australia (1996) Overseas Economy $US20,000 billion Costs of Crime

  15. “Just do it…..!” • Is there enough basic data to construct a global model?

  16. How much Crime around the World? U.N. Crime & Justice Survey

  17. Triangulate with other Data …Banks and Businesses rarely report crime, because they think it will adversely affect their “image” Source: www.kpmg.com

  18. Measuring the Proceeds of Crime • “Crime in Australia costs $A11-21 bn, and profits are $A6-8 bn per year” • (John Walker Crime Trends Analysis, 1996) • "Illegal grey economy in Czech Republic about 10% of GDP” • (Hospodárské Noviny, 2 Apr 98) • "$30bill illegal drugs reach the US from Mexico each year" • (Chicago Tribune, 25 Mar 98) • "Shadow business in Russia's economy may range between 25% -50%" • (TASS 17 Mar 98) • "UK black economy between 7-13% of GDP" • (Sunday Telegraph, 29 Mar 98) • "$50-250bn illegally moved from Russia to Western banks in 5 years" • (Russian Interior & Economics Ministries, April 99) • "Illicit drug sales (in the USA) generated up to $48bn a year in profits" • (Congressional hearing, April 99) • "Illegal profits total 2-5% of world GDP or $1-3trillion" • (Dow Jones News, 12 Mar 98)

  19. About Criminal Income • Crime generates income in all countries • Income from crime depends on the prevalence of different types of crime and the average proceeds per crime • Sophisticated and organised crimes generate more income per crime than simpler and individual crimes • Crimes that trade on “forbidden goods” like drugs, arms, pornography, slave labour, copyrights, migration visas etc, are particularly profitable • In general, richer countries generate more income per crime than poor ones • Income inequality or corruption may support a rich criminal class even in a poor country • Not all criminal income is laundered - Even criminals have to eat, sleep, drive fast cars, and pay accountants and lawyers If you like algebra........ • Total Criminal Profits to be Laundered = Total Population times GNP/Capita times: • 700*(TI Corruption Index)*(Bribery+Embezzlement+Fraud rates) + • 500*Drug Trafficking rate + 100*Theft rate + 65*Burglary rate + • 50* Drug Possession rate + 20*Robbery rate + 0.2*Homicide rate + • 0.1*(Assault rate + Sex Assault rate)

  20. About Corruption

  21. Resulting Estimates of Money Generation by Crime Type by World Region$US bill/yr Note: the big numbers come from fraud not drugs

  22. Assumptions about Laundering Processes • Not all laundered money leaves the country • Some countries' finance sectors provide perfect cover for local launderers • Countries where official corruption is common provide benign environments for launderers • Laundered money seeks countries with attractive banking regimes • Tax Havens • "No questions asked" banking • Countries with stable economies and low risk • Trading, ethnic and linguistic links will determine launderers' preferred destinations • Other things being equal, "hot" money will be attracted to havens with trading, ethnic, linguistic or geographic links to the generating country If you like algebra........ • Attractiveness to money launderers = • [GNP per capita] *[3*BankSecrecy+GovAttitude+SWIFTmember-3*Conflict-Corruption +15] • Where: GNP per capita is measured in US$, BankSecrecy is a scale from 0 (no secrecy laws) to 5 (bank secrecy laws enforced),GovAttitude is a scale from 0 (government anti-laundering) to 4 (tolerant of laundering), SWIFTmember is 0 for non-member countries and 1 for members of the SWIFT international fund transfer network,Conflict is a scale from 0 (no conflict situation) to 4 (conflict situation exists), • Corruption is the modified Transparency International index (1=low, 5=high corruption),And the constant '15' ensures that all scores are greater than zero.

  23. Model Index: Most Attractive to Launderers COUNTRY Score Luxembourg 686 United States 634 Switzerland 617 Cayman Islands 600 Austria 497 Netherlands 476 Liechtenstein 466 Vatican City 449 United Kingdom 439 Singapore 429 Hong Kong 397 Ireland 356 Bermuda 313 Bahamas, Andorra, Brunei, Norway, Iceland, Canada 250-299 Portugal, Denmark, Sweden, Monaco, Japan, Finland, Germany, New Zealand, Australia, Belgium 200-249 Bahrain, Qatar, Italy, Taiwan, United Arab Emirates, Barbados, Malta, France, Cyprus 150-199 Gibraltar, Azores (Spain), Canary Islands, Greenland, Belarus, Spain, Israel 100-149

  24. Triangulation: Attractiveness to ML: Service Exports and Incoming Money Laundering

  25. Transcrime & Walker Attractiveness Indices Triangulation: Attractiveness to ML: Banking Risk AnalysisTRANSCRIME “Euroshore” project 1. Money laundering punished in your criminal system? 2. Legislation provides for a list of crimes as predicate offences? 3. Predicate offences cover all serious crimes? 4. Predicate offences cover all crimes? 5. Provision allowing confiscation of assets for an ML offence? 6. Special investigative bodies or investigations in relation to ML offences? 1. Is there an anti-ML law in the jurisdiction? 2. Banks covered by the anti-ML law? 3. Other financial institutions covered by the anti-ML law? 4. Non-financial institutions covered by the anti-ML law? 5. Other professions carrying out a financial activity covered by the anti-ML law? 6. ID requirements for the institutions covered by the anti-money law? 7. Suspicious transactions reporting? 8. Central authority (for instance, an FIU) for the collection of suspicious transactions reports? 9. Co-operation between banks or other financial institutions and police authorities? 1. Prohibition to open a bank account without ID of the beneficial owner? 2. Limits to bank secrecy in case of criminal investigation and prosecution? 1. Minimum share capital required for limited liability companies? 2. Prohibition on bearer shares in limited liability companies? 3. Prohibition on legal entities as directors of limited liability companies? 4. Registered office exists for limited liability companies? 5. Any form of annual auditing (at least internal) for limited liability companies? 6. Shareholder register exists for limited liability companies? 1. Extradition (at least of foreigners) for ML offences? 2. Assistance to foreign law enforcement agencies in investigation of ML cases? 3. Law enforcement may respond to a request from a foreign country for financial records? 4. Provision allowing the sharing of confiscated assets for ML offences? 5. The 1988 UN Convention been ratified? • CRIMINAL LAW • ADMINISTRATIVE REGULATIONS • BANKING LAW • COMPANY LAW • INTERNATIONAL CO-OPERATION PROVISIONS

  26. …Putting all this information together... Model’s Top 10 Origins of Laundered Money Rank Origin Amount ($Usmill/yr) % of Total 1 United States 1320228 46.3% 2 Italy 150054 5.3% 3 Russia 147187 5.2% 4 China 131360 4.6% 5 Germany 128266 4.5% 6 France 124748 4.4% 7 Romania 115585 4.1% 8 Canada 82374 2.9% 9 United Kingdom 68740 2.4% 10 Hong Kong 62856 2.2%

  27. Model’s Top 10 Flows of Laundered Money Rank Origin Destination Amount ($USmill/yr) % of Total 1 United States United States 528091 18.5% 2 United States Cayman Islands 129755 4.6% 3 Russia Russia 118927 4.2% 4 Italy Italy 94834 3.3% 5 China China 94579 3.3% 6 Romania Romania 87845 3.1% 7 United States Canada 63087 2.2% 8 United States Bahamas 61378 2.2% 9 France France 57883 2.0% 10 Italy Vatican City 55056 1.9%

  28. Model’s Top 10 ML Destinations Rank Destination Amount ($Usmill/yr) % of Total 1 United States 538145 18.9% 2 Cayman Islands 138329 4.9% 3 Russia 120493 4.2% 4 Italy 105688 3.7% 5 China 94726 3.3% 6 Romania 89595 3.1% 7 Canada 85444 3.0% 8 Vatican City 80596 2.8% 9 Luxembourg 78468 2.8% 10 France 68471 2.4%

  29. Model results compared to Press reports • "Illegal grey economy in Czech Republic about 10% of GDP” (Hospodárské Noviny, 2 Apr 98) • Model estimates 14.8% of GDP • "$30bill illegal drugs reach the US from Mexico each year"(Chicago Tribune, 25 Mar 98) • Model estimates $26bill laundered in Mexico each year • “More than $2bill is laundered in Poland each year"(National Bank of Poland, reported on 15 Apr 98) • Model estimates $3bill laundered in Poland each year • "Share of shadow business in Russia's economy may range between 25% -50%"(TASS 17 Mar 98) • Model estimates money laundering 15% of Russian GDP • "Switzerland is implicated in $500bill of money laundering each year"(Swiss Finance Ministry, reported on 26 Mar 98) • Model estimates $59bill - including only "first-stage" laundering. • "UK black economy between 7-13% of GDP"(Sunday Telegraph, 29 Mar 98) • Model estimates total money laundering 7.4% of UK GDP • "$50-250bn illegally moved from Russia to Western banks in 5 years"(Russian Interior & Economics Ministries, April 99) • Model estimates $28bn per year from Russia to western banks • "Money Laundering in Belarus about 30% of GDP"(European Humanities University, 20 Nov 98) • Model estimates 22.2% of Belarus GDP is laundered money • "Illicit funds generated and laundered in Canada per year $5-17 bn"(Canadian Solicitor General, Sep 1998) • Model estimates $22bill generated and laundered in Canada each year, • but also that $63bn of US crime funds laundered in Canada. • "Approximately $2.7bn are laundered in Colombia each year"(BBC Monitoring Service, Nov 98) • Model estimates $2.1bn laundered in Colombia every year • "Illicit drug sales (in the USA) generated up to 48bn a year in profits for laundering"(Congressional hearing, April 99) • Model estimates $34.6bn generated and laundered by illicit drug trade in USA • "Illegal profits total 2-5% of world GDP or $1-3trillion"(Dow Jones News, 12 Mar 98) • Model estimates total global money laundering $2.85 trillion After late 1999, it became apparent that most published estimates were based on my model

  30. Triangulation:Shadow Economy, Crime and Money Laundering All rich countries have low % shadow economies • “Excess” shadow economy might be an indicator of the proceeds of crime. Many of the richest countries with high % shadow economies have significant transnational crime, illicit drug production and corrupt business practices. • On this basis, the shadow economy in Australia would produce around AU$20 billion per year, some of which laundered. Poor countries with low % shadow economies are mostly “command economies” Source: F. Schneider and J. Walker.

  31. Triangulation: Cross-border flow Analysis(Raymond Baker, 2005) From “Capitalism’s Achilles Heel”, Baker 2005. Based on a review of studies of transnational crime

  32. Triangulation: the Economics of the Global Illicit Drugs Trades • By 2005 UNODC researchers were convinced they had sufficient data in their Annual Reports Questionnaires to develop a global model of the illicit drugs market. • ARQs received from most countries around the world – all continents; rich/poor; developed/less developed countries. • We developed mechanisms for testing the credibility of ARQ data from different countries by comparing them with other ARQ data and other studies. • We developed mechanisms for filling the gaps in the data, by classifying different countries and “interpolating”. • We identified the economic logic of the illicit drugs trades. • We identified ways to deduce the “trade routes” of the illicit drugs trades, by comparing “mentions”, and developed this into a “tracking model” that can explain corruption levels in transit countries.

  33. The Economics of the Illicit Drugs Trades

  34. General Conclusions from the Model • Global money laundering may be as much as $US3 trillion per annum • Business Fraud exceeds illicit drugs as a source of laundered money • Attacking the economics of crime can be an effective transnational crime prevention strategy. • Economists can play a valuable role in monitoring and combating transnational crime and money laundering. • Does AML reduce crime? – Probably not by much. • Does AML reduce ML? – Probably not much, but it diverts it from the finance sectors to more costly avenues. • Does AML help catch criminals? – Probably only a few, but sometimes very important ones. • Does AML protect the economy? – Probably a massive boost to the economy by ensuring that the finance sector is seen as honest, wary and supervised.

  35. Model Estimates of ML Flows from Developing Countries

  36. Model Estimates of ML Flows from Developing Countries E Europe 176963 SE Europe 129512 CAsia/Transcaucasus 15201 E & SE Asia 444536 Near & Middle East/SW Asia 12213 Caribbean 6452 N & W Africa 4178 South Asia 3465 Central America 2525 E Africa 3559 Oceania 209 W & C Africa 3278 South America 30361 Southern Africa 14321 C & S America total $39.3 bn; Africa total $25.3 bn; Europe total $306.5bn; ME & Asia total $475.6bn Global total $846.8 bn

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