Measuring Global Moneylaundering Presented by John Walker at

Measuring Global Moneylaundering Presented by John Walker at the Utrecht School of Economics November 2007 John Walker Crime Trends Analysis

Three Important Things in Life l Naïveté l l Iconoclasm l l Querying the dominant paradigm Serendipity l l Being naïve enough not to know it can’t be done “In the field of observation, chance favours only the prepared mind” (Louis Pasteur ) Looking before Leaping l Evidence based action John Walker Crime Trends Analysis

An Attraction to Mathematics l l Using “matrix algebra”, we can add, multiply subtract or divide tables like this one. This particular matrix is very special, because if you multiply it by itself, it gives the number of routes between pairs of countries VIA A THIRD country. A B C D E F G H I J A 5 0 2 1 2 0 2 1 1 0 2 0 1 1 B 2 1 4 0 1 2 1 1 0 2 0 0 0 1 C 2 0 1 1 0 0 0 0 1 0 D 2 1 1 5 0 1 2 1 1 0 2 0 2 0 E 2 0 1 0 1 3 0 2 1 1 0 1 2 0 0 F 2 1 2 0 1 0 2 1 6 0 0 1 2 1 1 0 G 1 0 0 0 1 1 0 1 0 0 H 2 0 0 0 2 0 1 2 1 1 0 3 0 1 0 I 1 1 0 0 2 0 2 1 1 0 1 3 0 1 0 J 1 1 1 0 2 0 0 1 0 2 0 John Walker Crime Trends Analysis

A Fascination with Economics l 1965 – Mathematics Scholarship to LSE In economics, supply and demand describe market relations between prospective sellers and buyers of a good. The supply and demand model determines price and quantity sold in the market. The model is fundamental in microeconomic analysis of buyers and sellers and of their interactions in a market. It is also used as a point of departure for other economic models and theories. The price P is determined by a balance between production at each price (supply S) and the desires of those with purchasing power at each price (demand D). From Wikipedia John Walker Crime Trends Analysis

Discovering Macroeconomics l l 1965 – Mathematics Scholarship to LSE 1967 – AIESEC, Univerzita Karlova v Praze, Kancelářské Stroje. Destination Country--- > Origin Country / Country 1 C o u n t r y 2 A Country 2 C o u n t r y 3 C o u n t r y 4 B E Country 3 C o u n t r y 5 C o u n t r y 6 C C o u n t r y 7 D A+B+C+D E+F G G H Country 5 I Country 6 K H J I+J L Country 7 K+L M Etc A E T O T A L S F Country 4 TOTALS E T C B+F+G+I+K H C+J L John Walker Crime Trends Analysis D+M M N N N Sum(A: N)

Real-World Applications l 1965 – Mathematics Scholarship to LSE l 1967 – AIESEC, Univerzita Karlova v Praze, Kancelářské Stroje. 1970 – Transportation modelling/forecasting l l The gravity model of trade in international economics predicts bilateral trade flows based on the economic sizes of and distance between two units. The model was first used by Jan Tinbergen in 1962. The basic theoretical model for trade between two countries (i and j) takes the form of: l Where F is the trade flow, M is the economic mass of each country, D is the distance and G is a constant. Using logarithms, the equation can be converted to a linear form for econometric analysis. The basic model for such a test results in the following equation (note: constant G becomes part of α): l l ln(Bilateral Trade Flow) = α+βln(GDPCountry 1)+βln(GDPCountry 2)-βln(Distance)+ε The model often includes variables to account for income level (GDP per capita), price levels, language relationships, tariffs, contiguity, and colonial history (whether Country 1 ever colonized Country 2 or vice versa). The model has also been used in international relations to evaluate the impact of treaties and alliances on trade, and it has been used to test the effectiveness of trade agreements and organizations such as NAFTA and the WTO. John Walker Crime Trends Analysis

Measuring Crime l 1965 – Mathematics Scholarship to LSE l 1967 – AIESEC, Univerzita Karlova v Praze, Kancelářské Stroje. l 1970 – Transportation modelling/forecasting l 1975 – Use of regional crime data to measure well-being John Walker Crime Trends Analysis

Applications in Criminology l 1965 – Mathematics Scholarship to LSE l 1967 – AIESEC, Univerzita Karlova v Praze, Kancelářské Stroje. l 1970 – Transportation modelling/forecasting l 1975 – Use of regional crime data to measure well-being l 1978 - Accidental criminology apprenticeship l 1988 – Chance meeting re Victimisation Survey l 1992 – Opportunistic Proposal for Business Victimisation Survey l 1992 – First Costs of Crime Estimates John Walker Crime Trends Analysis

Applications in Criminology l 1965 – Mathematics Scholarship to LSE l 1967 – AIESEC, Univerzita Karlova v Praze, Kancelářské Stroje. l 1970 – Transportation modelling/forecasting l 1975 – Use of regional crime data to measure well-being l 1978 - Accidental criminology apprenticeship l 1988 – Chance meeting re Victimisation Survey l 1992 – Opportunistic Proposal for Business Victimisation Survey l 1992 – First Costs of Crime Estimates l 1995 – First National Estimates of Moneylaundering John Walker Crime Trends Analysis

A Fundamental Insight about ML How Much Crime is there ? How Much Profit is there in the Crime ? What Proportion of the Profits is Laundered ? Where does it go for Laundering ? John Walker Crime Trends Analysis How does it impact on Society ?

Economic Model of Crime, ML & TF TC = Total Costs of Crime TP = Total Proceeds of Crime KP = Known Proceeds of Crime TE = Total Economy TM = Total Money Laundering TT = Total Terrorist Financing KM = Known Money Laundering KT = Known Terrorist Financing Incoming Money Laundering 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] John Walker Crime Trends Analysis

Estimates of ML in and through Australia (1996) • Estimates based on Costs of Crime and Expert Survey Crime Category/ Implied ML Estimates for Australia ($mill) Est’d Proceeds of Crime Min Mid 1 Mid 2 Max Homicide Max $2. 75 m Robbery & Extortion $74. 4 m <1 <1 <1 22 <1 45 Other Violence Min $3. 31 m Breaking and Entering $714. 4 m Insurance Fraud $1530 m <1 14 38 <1 71 77 <1 71 153 <1 500 306 Business Fraud $375 - $900 m Other Fraud $750 m Motor Vehicle Thefts $533. 6 m Other Thefts $462 Environmental Crime $5. 21 Illicit Drugs $1500 m 56 38 27 8 <1 300 225 113 53 82 <1 750 540 188 187 116 2 1050 900 600 480 347 8 1350 402 1394 2328 4536 Total $5951 - $7661 m John Walker Crime Trends Analysis

Estimates of ML in and through Australia (1996) • Estimates based on Costs of Crime and Expert Survey • 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 John Walker Crime Trends Analysis

Estimates of ML in and through Australia (1996) Overseas Economy Overseas Money laundered overseas $US 20, 000 billion $US 100 -500 billion? Costs of Crime The Australian Economy $380 billion P. o. C. Costs of Crime $11 -21 billion ML Overseas Money laundered in Australia $7. 7 billion? Australian Money laundered overseas $5. 5 billion? John Walker Crime Trends Analysis Proceeds of Crime $6 -8 billion ML $1 -4. 5 billion Australian Money laundered in Australia

Going Global l 1965 – Mathematics Scholarship to LSE l 1967 – AIESEC, Univerzita Karlova v Praze, Kancelářské Stroje. l 1970 – Transportation modelling/forecasting l 1975 – Use of regional crime data to measure well-being l 1978 - Accidental criminology apprenticeship l 1988 – Chance meeting re Victimisation Survey l 1992 – Opportunistic Proposal for Business Victimisation Survey l 1992 – First Costs of Crime Estimates l 1995 – First National Estimates of Moneylaundering l 1996 – First Prototype Global Model of Moneylaundering John Walker Crime Trends Analysis

Official efforts to measure Global Crime up to the 1990 s • 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 1990 s. Only measures recorded crime. • Crime Victims Surveys developed in the 1970 s (USA, UK); common set of definitions; unrecorded crime. Limited crime types, costly, political risk. • From the 1980 s, 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. John Walker Crime Trends Analysis

Assumptions about Criminal Income l Crime generates income in all countries l Income from crime depends on the prevalence of different types of crime and the average proceeds per crime l Sophisticated and organised crimes generate more income per crime than simpler and individual crimes l In general, richer countries generate more income per crime than poor ones l Income inequality or corruption may support a rich criminal class even in a poor country l Not all criminal income is laundered - Even criminals have to eat, sleep, drive fast cars, and pay accountants and lawyers If you like algebra. . . . l Total Criminal Profits to be Laundered = Total Population times GNP/Capita times: l 700*(TI Corruption Index)*(Bribery+Embezzlement+Fraud rates) + l 500*Drug Trafficking rate + 100*Theft rate + 65*Burglary rate + l 50* Drug Possession rate + 20*Robbery rate + 0. 2*Homicide rate + l 0. 1*(Assault rate + Sex Assault rate) John Walker Crime Trends Analysis

Assumptions about Laundering Processes l Not all laundered money leaves the country l Some countries' finance sectors provide perfect cover for local launderers l Countries where official corruption is common provide benign environments for launderers l Laundered money seeks countries with attractive banking regimes l Tax Havens l "No questions asked" banking l Countries with stable economies and low risk l Trading, ethnic and linguistic links will determine launderers' preferred destinations l 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. . . . l Attractiveness to money launderers = l [GNP per capita] *[3*Bank. Secrecy+Gov. Attitude+SWIFTmember-3*Conflict-Corruption +15] l l Where: GNP per capita is measured in US$, Bank. Secrecy is a scale from 0 (no secrecy laws) to 5 (bank secrecy laws enforced), Gov. Attitude 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. John Walker Crime Trends Analysis

Assumptions about Laundering Routes l The money may stay in the country of origin. . l l the more corrupt the country, the more it will tolerate internal money laundering or it may go to another country: l The money to be laundered outside the country is distributed between all other countries in proportion to: l their Attractiveness Index, and l the distance between the origin and destination countries. The distance between countries is a proxy for the geographic, linguistic, ethnic and trade barriers between countries If you like algebra. . . . l Percentage Laundered 'at home' = 20%*(T. I. Index Score) l Percentage generated in country X and laundered in country Y is proportional to: (100 -Percentage Laundered 'at home') * Attractiveness Score of Y- (Distance between countries X and Y)2 John Walker Crime Trends Analysis

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 "$30 bill illegal drugs reach the US from Mexico each year" (Chicago Tribune, 25 Mar 98) Model estimates $26 bill laundered in Mexico each year “More than $2 bill is laundered in Poland each year" (National Bank of Poland, reported on 15 Apr 98) Model estimates $3 bill 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 $500 bill of money laundering each year" (Swiss Finance Ministry, reported on 26 Mar 98) Model estimates $59 bill - 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 -250 bn illegally moved from Russia to Western banks in 5 years" (Russian Interior & Economics Ministries, April 99) Model estimates $28 bn 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 $22 bill generated and laundered in Canada each year, but also that $63 bn of US crime funds laundered in Canada. "Approximately $2. 7 bn are laundered in Colombia each year" (BBC Monitoring Service, Nov 98) Model estimates $2. 1 bn laundered in Colombia every year "Illicit drug sales (in the USA) generated up to 48 bn a year in profits for laundering" (Congressional hearing, April 99) Model estimates $34. 6 bn generated and laundered by illicit drug trade in USA "Illegal profits total 2 -5% of world GDP or $1 -3 trillion" (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 John Walker Crime Trends Analysis

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

Attractiveness to ML: - Service Exports and Incoming Money Laundering John Walker Crime Trends Analysis

Attractiveness to ML: Banking Risk Analysis TRANSCRIME “Euroshore ” project “Euroshore” CRIMINAL LAW 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? Transcrime & Walker Attractiveness Indices ADMINISTRATIVE REGULATIONS BANKING LAW COMPANY LAW INTERNATIONAL CO-OPERATION PROVISIONS 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? John Walker Crime Trends Analysis

Triangulation: Transfer Pricing Fraud from Zdanowicz, J (2004) l USD 156. 2 bn moved out of the United States by way of pricing discrepancies during 2001 l USD 4. 27 bn involved countries which are listed on the United States State Department ‘Al Qaeda watch-list’. l USD 213 bn moved into the United States. l Fraud or laundering? l Overseas beneficiaries or American? John Walker Crime Trends Analysis

Triangulation: Cross-border flow Analysis (Raymond Baker, 2005) Global Flows Low ($US bn) High ($US bn) Drugs $120 $200 Counterfeit goods $80 $120 Counterfeit currency $3 $3 Human trafficking $12 $15 Illegal arms trade $6 $10 Smuggling $60 $100 Racketeering $50 $100 $331 $549 Mispricing $200 $250 Abusive transfer pricing $300 $500 Fake transactions $200 $250 Commercial Subtotal $700 $1000 Corruption $30 $50 Grand Total $1061 $1599 Crime Subtotal From “Capitalism’s Achilles Heel”, Baker 2005. Based on a review of studies of transnational crime John Walker Crime Trends Analysis

The Economics of the Global Illicit Drugs Trades l 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 – regardless of Rand Corp’s “can’t be done” conclusion. l ARQs received from most countries around the world – all continents; rich/poor; developed/less developed countries. l We developed mechanisms for testing the credibility of ARQ data from different countries by comparing them with other ARQ data and other studies. l We developed mechanisms for filling the gaps in the data, by classifying different countries and “interpolating”. l We identified the economic logic of the illicit drugs trades. l 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. John Walker Crime Trends Analysis

UNODC Illicit Drugs model……… John Walker Crime Trends Analysis

UNODC Illicit Drugs model……… John Walker Crime Trends Analysis

The Economics of the Illicit Drugs Trades John Walker Crime Trends Analysis

Conclusions l Global money laundering may be as much as $US 3 trillion per annum l Business Fraud exceeds illicit drugs as a source of laundered money l Attacking the economics of crime can be an effective transnational crime prevention strategy. l Economists can play a valuable role in monitoring and combating transnational crime and money laundering. l Does AML reduce crime? – Probably not by much. l Does AML reduce ML? – Probably not much, but it diverts it from the finance sectors to more costly avenues. l Does AML help catch criminals? – Probably only a few, but sometimes very important ones. l 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. John Walker Crime Trends Analysis

Key Skills Blending Dodgy Data and Heroic Assumptions … Getting the Message Across. . … and turning it into something surprisingly useful. Dilbert cartoons used with permission. COPYRIGHT: UNITED FEATURES SYNDICATE INC. Distributed by Auspac Media John Walker Crime Trends Analysis