Threat, risk (organised) crime an d Crime-money (laundering)

1. Threat, risk (organised) crime and Crime-money (laundering)

2. Past, present and “OC threat/risks” • 2001: European Multidisciplinary Group declared: “We looked back; we must look forward!”  Therefore: “Future oriented” reporting: the future of OC = the future of its threat/risk • What is threat or risk? • And what is an ‘organised crime risk’?

3. The simple risk formula • Risk = p = ∑xi/N (per time unit) = threat = • the likelihood that an event x of a certain class Y will occur given the total set of events. • Could policy makers please substitute the x and Y? • Y is a closed definition of a class of events • x = single event of class Y • ∑xi-time = time series of events • Apply that to organised crime assessment

4. Finding an insurance policy against“organised crime” • Basic thesis: every determinable harm can be insured if a likelihood can be determined. • What does an insurance firm do with a new risk? (a) it determines the meaning of the class of events Y, then its total N (b) it designs a time series = past events x (c) the costs of events (classified harm) and fills the formula

5. Finding an insurance policy againstorganises crime: continued • What did the EU policy makers do? • (a) they formulated a fuzzy definition and (b) threw away the past. Just try to make a time series. • What can an insurance firm do?

6. The desperate insurance firm • What can an insurance firm do? • It cannot sell an OC insurance policy because there is no determinable risk! (Or serious crime): no x and no Y • On what basis to assess OC crime risk? • If no proper definition, no OC insurance risk • Only con men can sell such policies!

7. The desperate insurance firm (continued) • Are policy makers con men? They sold you multi-million policies  EUROPOL  Organised Crime Threat Assessments  Transnational Organised Crime Convention  Anti-money laundering regime All to make us feel secure!

8. The insurance firm perseveres!! • Continue with our insurance man. What can he do? • He must keep the OC banner: excellent commercial label  never abandon a winning formula! • Next: some correlation with a criterion variable.

9. The insurance firm perseveres!!(continued) For example: • Breakdown of social-economic or criminal variables against criterion variable = “Foreign direct investment” (Daniele and Marani; Italy) • OC and investment: negative correlation but ≠ causal relation, because • Underlying variable: mal governance and corruption.

10. The unmarketable exception clause • The underlying variable: mal governance and corruption. • The ‘Berlusconi exception clause’! How to sell such an insurance product? • Determining the threat of mal governance and sell corruption risk policies. • Commercial challenge for Transparency International, but otherwise unsalable.

11. The threat of crime money • The global threat since the 1980s. • Basic concern: threat to the financial system integrity • Which criminal is going to cut the branch on which he is sitting? • Grubby banks are dangerous . . . . for launderers:

12. The threat of crime money (continued) Calvi: hanging from Black Friars Bridge Sindona (poison) + lawyer shot  Russian bankers (a too long series for a slide) Nugan Hand Bank (Australia, suspicious suicide)  European Union Bank ($ 10 million lost) • Most recent launderers’ risk: unreliable bank employees selling CDs with names to the fiscal authorities!

13. The criminal risk industry • Instead of “threat thinking”: The real question: What is the role of crime money within the financial system? • Again: no data, but an abundance of threat images benefiting the compliance industry. • Lot of juggling with trillions by IMF, OEDC, World Bank, FATF: mutually copy-pasting figures and threats • A (financial) risk industry

14. Copy-pasting threats • ‘Affects currency movements’ • ‘Destabilises banks by sudden withdrawals’ • ‘Influences interest rate’. • ‘Distorts the GDP’. • ‘No optimal investment’ (remarked by “Ponzi-bankers”!)

15. The risk of laundered and unlaundered money • What is the harm of laundered money? Part of the GDP: where is the danger?  Taxable • But there is moral harm: crime should not pay +  corrosion of morals

16. The risk of crime-money and corruption More corruption? • All big corruption scandals in EU concerned white money! Unlaundered money  What is the threat? • Luxury lifestyle? What is the difference with our greedy irresponsible Ponzi-bankers? • If laundered properly, no longer a threat!

17. The role of crime moneyon-going research • The Dutch confiscation database: statistical mud track since 1994 • “Threatened” sector real estate: skewed division but: Mean € 182.000 / median € 150.000 • mean value bank account: € 263.000 / median € 20.000  € 100.000 + : 90  € 1.000.000 + 11  94 % Dutch bank accounts < € 100.000 The role of crime money: less prominent, certainly not threatening, unless falsified by better data!

18. Do what you are (hopefully) paid for • Falsify, falsify, falsify, until the hypothesis do not crack. • Identify your ‘risk’ counting unit: no risk assessment without : ∑xi-n/time • Get to your database owners and hold them accountable: • they are your (democratic) knowledge source.

19. Thou should not hide knowledge • “We are the people”, researchers too, • And have the right to know. • If no data access: sue them under your Freedom of Information Act • If you don’t dare, just join the collective risk assessment ritual dance of the conferences.