Measuring Global Moneylaundering

Measuring Global Moneylaundering

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 Navet Being nave enough not to know it cant be done Iconoclasm Querying the dominant paradigm In the field of observation, chance favours Serendipity only the prepared mind (Louis Pasteur ) Evidence based action Looking before Leaping John Walker Crime Trends Analysis An Attraction to Mathematics 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 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 0 1 C 2 0 1 2 0 1 1 0 1 0 0 0 0 1 0 D 2 1 2 1 1 5 0 1 2 1 1 0 2 0 2 0 2 0 E 2 0 1 0 1 0 1 3 0 2 1 1 0 1 2 0

0 F 2 1 2 0 1 0 2 1 2 1 6 0 0 1 2 1 2 1 1 0 G 1 0 0 0 1 0 1 0 0 1 1 0 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 0 2 1 1 0 1 3 0 1 0 J 1 1 1 0 2 0 0 1 0 0 0 1 0 2 0 John Walker Crime Trends Analysis A Fascination with Economics 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 1965 Mathematics Scholarship to LSE 1967 AIESEC, Univerzita Karlova v Praze, Kancelsk Stroje. Destination Country--- Country---> Origin Country \/ Country 1 C o u n t r

y 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 1965 Mathematics Scholarship to LSE 1967 AIESEC, Univerzita Karlova v Praze, Kancelsk Stroje. 1970 Transportation modelling/forecasting 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: 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 ):): ln(Bilateral Trade Flow) = ):+ln(GDPCountry1)+ln(GDPCountry2)-ln(Distance)+ ln(GDPCountry1)+ln(GDPCountry1)+ln(GDPCountry2)-ln(Distance)+ ln(GDPCountry2)-ln(GDPCountry1)+ln(GDPCountry2)-ln(Distance)+ ln(Distance)+ The model often includes variables to account for income level (GDP per capita), price levels, language relationships, tariffs, contiguity, and colonial history (whether Country1 ever colonized Country2 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 1965 Mathematics Scholarship to LSE 1967 AIESEC, Univerzita Karlova v Praze, Kancelsk Stroje.

1970 Transportation modelling/forecasting 1975 Use of regional crime data to measure well-being John Walker Crime Trends Analysis Applications in Criminology 1965 Mathematics Scholarship to LSE 1967 AIESEC, Univerzita Karlova v Praze, Kancelsk Stroje. 1970 Transportation modelling/forecasting 1975 Use of regional crime data to measure well-being 1978 - Accidental criminology apprenticeship 1988 Chance meeting re Victimisation Survey 1992 Opportunistic Proposal for Business Victimisation Survey 1992 First Costs of Crime Estimates John Walker Crime Trends Analysis Applications in Criminology 1965 Mathematics Scholarship to LSE 1967 AIESEC, Univerzita Karlova v Praze, Kancelsk Stroje. 1970 Transportation modelling/forecasting 1975 Use of regional crime data to measure well-being 1978 - Accidental criminology apprenticeship 1988 Chance meeting re Victimisation Survey 1992 Opportunistic Proposal for Business Victimisation Survey 1992 First Costs of Crime Estimates 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) Estd Proceeds of Crime Min Mid1 Mid2 Max Homicide Max $2.75m Robbery & Extortion $74.4m <1 <1 <1 22 <1 22 <1 45 Other Violence Min $3.31m Breaking and Entering $714.4m Insurance Fraud $1530m

<1 14 38 <1 71 77 <1 71 153 <1 500 306 Business Fraud $375 - $900m Other Fraud $750m Motor Vehicle Thefts $533.6m Other Thefts $462Environmental Crime $5.21Illicit Drugs $1500m 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 - $7661m 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 $US20,000 billion $US100-500 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 1965 Mathematics Scholarship to LSE 1967 AIESEC, Univerzita Karlova v Praze, Kancelsk Stroje. 1970 Transportation modelling/forecasting 1975 Use of regional crime data to measure well-being 1978 - Accidental criminology apprenticeship 1988 Chance meeting re Victimisation Survey 1992 Opportunistic Proposal for Business Victimisation Survey 1992 First Costs of Crime Estimates 1995 First National Estimates of Moneylaundering 1996 First Prototype Global Model of Moneylaundering John Walker Crime Trends Analysis Official efforts to measure Global Crime up to the 1990s 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); common set of definitions; unrecorded crime. Limited crime types, costly, political risk. From 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. John Walker Crime Trends Analysis Assumptions 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 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) John Walker Crime Trends Analysis 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. John Walker Crime Trends Analysis Assumptions about Laundering Routes The money may stay in the country of origin.. the more corrupt the country, the more it will tolerate internal money laundering or it may go to another country: The money to be laundered outside the country is distributed between all other countries in proportion to: their Attractiveness Index, and 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........ Percentage Laundered 'at home' = 20%*(T.I. Index Score) 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 (Hospodrsk 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 John Walker Crime Trends Analysis Triangulation: Shadow Economy, Crime and Money Laundering

Excess shadow economy might be an indicator of the proceeds of crime. On this basis, the shadow economy in Australia would produce around AU$20 billion per year, some of which laundered. 40,000 All rich countries have low % shadow economies Ireland 35,000 USA 30,000 Switzerland Austria GDP/capita ($US) 2001 GDP per capita vs. Shadow Economy 25,000 Japan UK Australia 16.821 Italy Many of the richest countries with high % shadow economies have significant transnational crime, illicit drug production and corrupt business practices. UAE 20,000 NZ 15,000 10,000 35.4 Mexico 32.2 Iran Estonia Uruguay RussiaBelarus Colombia Thailand Panama Peru 5,000 China Vietnam Mongolia Poor countries with low % shadow 0 economies are 0 20 mostly command economies 38.9 Morocco Yemen 41.6 42.1 Pakistan

42.1 40 Shadow Economy as % of GDP Source: F. Schneider and J. Walker.John Walker Crime Trends Analysis Georgia Bolivia Lao PDR 60 80 Attractiveness to ML: - Service Exports and Incoming Money Laundering 100.00 Aruba 10.00 Services Exports/GNP Maldives Antigua/Barbuda St Lucia 1.00 Singapore Egypt 0.10 China Austria Sw itzerland Vanuatu Seychelles GrenadaSt Kitts Belize Barbados Dominica Luxembourg St Vincent Tonga Ethiopia India 0.01 C. Afr. Rep. Iran Algeria Myanmar 0.00 0.00 0.00 Albania Libya Sudan 0.01 1.00 Model Estimate of Incoming ML as Percentage of GDP John Walker Crime Trends Analysis 100.00 Attractiveness to ML: Banking Risk Analysis TRANSCRIME 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? CRIMINAL LAW

Old Attractiveness Index Versus New Transcrime & Walker Attractiveness Indices TransCrime Based Score 1. Is there an anti-ML law in the jurisdiction? 700.0 2. Banks covered by the anti-ML law? ADMINISTRATIVE 3. Other financial institutions covered by the anti-ML law? Luxembourg REGULATIONS 600.0 4. Non-financial institutions covered by the anti-ML law? 5. Other professions carrying out a financial activity covered by the Caymans anti-ML law? 6. ID requirements for the institutions covered by the anti-money law?Switzerland 500.0 7. Suspicious transactions reporting? Singaporeof suspicious transactions reports? 8. Central authority (for instance, an FIU) for the collection Austria 9. Co-operation between banks or other financial institutions and police authorities? 400.0 Liechtenstein Hong Kong 1. Prohibition to open a bank account withoutU.K. ID of the Netherlands beneficial owner? BANKING LAW 300.0 2. Limits to bank secrecy in case of criminal investigation and prosecution? Bermuda COMPANY LAW INTERNATIONAL CO-OPERATION PROVISIONS 1. Minimum share capital required for limited liability companies? Ireland 200.0 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? 100.0 5. Any form of annual auditing (at least internal) for limited liability companies? 6. Shareholder register exists for limited liability companies? 0.0 0.0 100.0 300.0 600.0 700.0 1. Extradition (at least 200.0 of foreigners) for ML400.0 offences?500.0 800.0 2. Assistance to foreign law enforcement agencies in investigation Walker 1999 Model Attractiveness Score 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) USD156.2 bn moved out of the United States by way of pricing discrepancies during 2001

USD4.27 bn involved countries which are listed on the United States State Department Al Qaeda watch-list. USD 213 bn moved into the United States. Fraud or laundering? 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 Capitalisms 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 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 Corps cant be done conclusion. 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. John Walker Crime Trends Analysis UNODC Illicit Drugs model Table 1. Production and Distribution from Source Countries to Destination Countries Consumer Regions Producer Regions East Africa North Africa Southern Africa West and Central Africa Caribbean Central America North America South America C. Asia & Transcaucasus East and South-East Asia Nr & M.East /SW Asia South Asia Eastern Europe Western & Central Europe South East Europe Oceania All Countries Total Production in Source Country (Kg Heroin Equiv) 0 714 0 0 0

0 8,400 5,268 770 94,050 365,150 0 2,147 0 0 0 476,500 Total Seized/Lost Total Available Transferred to in Source for Sale Markets Country (Kg Heroin (Kg Heroin (Kg Heroin Equiv) Equiv) Equiv) 0 0 0 0 0 0 209 440 0 582 9,551 0 0 0 0 0 10,781 0 714 0 0 0 0 8,191 4,829 770 93,468 355,599 0 2,147 0 0 0 465,719 2,293 3,410 1,099 9,954 364 783 28,735 3,255 12,076 59,928 78,352 61,666 89,913 97,248 10,208 6,436 465,719 E N S W A f r i

c a A f r i c a A f r i c a & Total Seized/ lost in Transit (Kg Heroin Equiv) 47 35 7 51 80 180 6,621 399 2,748 6,885 27,723 252 923 3,994 4,713 198 54,856 0 0 0 0 0 0 0 0 0 240 2,053 0 0 0 0 0 2,293 0 714 0 0 0 0 0 0 0 267 2,429 0 0 0 0 0 3,410 0 0 0 0 0 0 0 0 0 119 980 0 0 0

0 0 1,099 C A f r i c a 0 0 0 0 0 0 0 0 0 1,076 8,878 0 0 0 0 0 9,954 C a r i b b e a n 0 0 0 0 0 0 0 0 0 39 325 0 0 0 0 0 364 C N S A m e r i c a A m e r i c a A m e r i c a 0 0 0 0

0 0 8,191 1,574 0 2,050 16,920 0 0 0 0 0 28,735 0 0 0 0 0 0 0 3,255 0 0 0 0 0 0 0 0 3,255 0 0 0 0 0 0 0 0 0 85 698 0 0 0 0 0 783 John Walker Crime Trends Analysis C T r A a s n i s a c a u & c a s u s 0 0 0 0 0 0 0 0 770 1,222 10,084 0 0 0 0 0 12,076 E & S E A s i a

0 0 0 0 0 0 0 0 0 59,928 0 0 0 0 0 0 59,928 N e a r E a s t & / S MW i d A d s l i e a 0 0 0 0 0 0 0 0 0 0 78,352 0 0 0 0 0 78,352 S E W A s i a E u r o p e & 0 0 0 0 0 0 0 0 0 6,663 55,003 0 0 0 0 0

61,666 0 0 0 0 0 0 0 0 0 9,483 78,283 0 2,147 0 0 0 89,913 C E u r o p e 0 0 0 0 0 0 0 0 0 10,508 86,740 0 0 0 0 0 97,248 S E E u r o p e 0 0 0 0 0 0 0 0 0 1,028 9,180 0 0 0 0 0 10,208 O c e a n i a 0 0 0 0 0 0 0 0 0 762 5,673

0 0 0 0 0 6,436 A l l C o u n t r i e s 0 714 0 0 0 0 8,191 4,829 770 93,468 355,599 0 2,147 0 0 0 465,719 UNODC Illicit Drugs model Table 2. Supply and Demand in Destination Countries Regions E N S W A f r i c a A f r i c a A f r i c a & C a r i b b e a n C A f r i c a C N

S A m e r i c a A m e r i c a A m e r i c a C T r A a s n i s a c a u & c a s u s E & S E A s i a N e a r E a s t & / S MW i d A d s l i e a S E W A s i a E u r o p e & S E E

u r o p e C E u r o p e A l l O c e a n i a C o u n t r i e s Production: Total Production in Source Country (Kg Heroin Equiv) Total Seized/Lost in Source Country (Kg Heroin Equiv) Total Available for Sale (Kg Heroin Equiv) Farmgate Price at Origin (US$/Kg Heroin Equiv) Producer Income (US$mill) 0 0 0 0 0 714 0 714 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 8400 209 8191 0 21 5268 440 4829 0 12 770

0 770 0 2 94050 582 93468 1339 125 365150 9551 355599 2830 1006 0 0 0 0 0 2147 0 2147 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 476500 10781 465719 2520 1173 Supply: Total Intended for Consumption (Kg Heroin Equiv) Total Seized/Lost at Destination (Kg Heroin Equiv) Total Available for Consumption (Kg Heroin Equiv) Wholesale price at Destination US$ /gm Wholesaler Income (US$mill) 2293 47 2246 28 63 3410 35 3375 42 142 1099 7 1092 28 30 9954 51 9903 15 153 364 80 285 38 11 783 180

603 73 44 28735 6621 22113 98 2175 3255 399 2856 25 71 12076 2748 9328 21 194 59928 6885 53042 38 2022 78352 27723 50629 7 379 61666 252 61413 71 4355 89913 923 88990 36 3198 97248 3994 93254 73 6779 10208 4713 5496 26 145 6436 198 6237 140 874 465719 54856 410863 50 20635 Demand: Estimated User Population (Thousands) Estimated Actual Consumption per year (Kg Heroin Equiv) Implied Consumption per user (gms Heroin Equiv) Average Retail Price US$ /gm Retailer Income (US$mill) 84 2021 24.2 40 82 108 3038 28.0 124 377 85 983 11.5

81 80 524 8913 17.0 57 508 21 285 13.5 41 12 24 603 25.2 83 50 1301 22113 17.0 402 8886 286 2856 10.0 101 288 370 9328 25.2 51 480 2105 53042 25.2 108 5725 2009 50629 25.2 12 596 3102 61413 19.8 123 7567 2406 80091 33.3 133 10681 1450 83929 57.9 302 25340 180 5496 30.6 183 1006 99 5614 56.5 561 3148 14154.3 390353 27.6 166 64825 0 2 30 84

236 351 0 0 153 355 508 0 21 620 1311 6711 8663 12 71 0 217 300 2 12 60 286 360 125 1,942 0 3703 5770 1006 157 0 217 1381 0 4355 3212 7566 5 76 2175 7483 9739 0 5729 18560 24290 0 0 803 2274 3076 1173 2908 14813 44191 63085 Regional Net Values: Source Country Producers' Income Source Country Wholesalers' Income less Purchase Costs International Wholesalers' Income less Purchase Costs Net Retailer Profit (US$mill) Gross Value of Regional Trade 38 19 57 18 49 68 0 - 7 1 8

44 6 50 John Walker Crime Trends Analysis 37 861 898 The Economics of the Illicit Drugs Trades John Walker Crime Trends Analysis Conclusions 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. 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

Recently Viewed Presentations

  • AP Chemistry Exam Review

    AP Chemistry Exam Review

    Identifying Purity of a Substance. Impurities in a substance can change the percent composition by mass . If more of a certain element is added from an impurity, then the percent mass of that element will increase and vice versa
  • Biomes of the World - West Muskingum Local Schools

    Biomes of the World - West Muskingum Local Schools

    Aquatic Biomes. Make up more than 70% of the Earth's surface. Aquatic biomes are not grouped by climate. They are grouped by water depth and salinity. Salinity is the amount of salt dissolved in the water. Rainfall and temperature also...
  • MAFI 420: Management Information Systems Exercise 2: Telecommunications

    MAFI 420: Management Information Systems Exercise 2: Telecommunications

    What are the principal components of telecommunications networks and key networking technologies?. What are the types of networks? How networks are structured? What are the main . telecommunications transmission media and types of networks
  • Challenge Québec Motocross

    Challenge Québec Motocross

    On est en : 2005 (et ça continue) Classement Open 1996 # 1 Hubert Rousseau # 2 Marc Pelletier # 3 Eric Ouellet # 4 Michel Rhéaume # 5 Marco Pomerleau # 6 Donald Thivierge # 7 Hugo Laroche #...
  • Chapter 26 Franklin D. Roosevelt and The New Deal

    Chapter 26 Franklin D. Roosevelt and The New Deal

    Superheroes of the Great Depression EXTRA CREDIT- Draw your superhero and illustrate his/her superpower. Use color and be creative!! Causes Uneven Prosperity Personal Debt Playing the Stock Market Over Production of Goods Agenda AIM- If only 3% of Americans owned...
  • Response to Intervention: Georgia&#x27;s Student Achievement ...

    Response to Intervention: Georgia's Student Achievement ...

    Georgia's RTI Process Includes: A 4-Tier delivery model designed to provide support matched to student need through the implementation of standards-based classrooms. Evidence-based instruction as the core of classroom pedagogy. Evidence-based interventions utilized with increasing levels of intensity based on...
  • Loop Analysis (7.8); Circuits with Op-Amps (3.3)

    Loop Analysis (7.8); Circuits with Op-Amps (3.3)

    Times New Roman Symbol Blank Presentation Microsoft Equation 3.0 Loop Analysis (3.2) Circuits with Op-Amps (3.3) Op Amps Use of Op Amps Applications of Op Amps The Op Amp Symbol The Op Amp Model Typical Op Amp "Ideal" Op Amp...
  • Guardianshi p, Wills & Power of Attorney Planning

    Guardianshi p, Wills & Power of Attorney Planning

    The information provided in this session is for information purposes only. It . must not be relied on as legal . advice. You should seek legal advice about your own particular circumstances.