Impact of Trade-Based Money Laundering (TBML) on developing economies

Elizaveta_Savinykh
Elizaveta_Savinykh Posts: 3 QUANTEXA TEAM

Are you interested in the impact of trade-based money laundering (TBML) on developing economies?

If so, don’t miss the this publication by Global Financial Integrity (GFI), Fedesarrollo, Transparency International Kenya, and Advocates Coalition for Development and Environment (ACODE) titled ‘Trade Based Money Laundering: A Global Challenge’.

Three points in particular resonate with us:

  1. The report is addressed to national governments, whose reach goes much further than FIs, especially in terms of making data available to all actors and in terms of forcing cooperation between these actors. Given the international nature and complexity of TMBL, eradicating the practice will require global collaboration.
  2. The report recommends the creation of national UBO registries. This type of information is key for the fight against TBML and the recommendation is pertinent, especially in light of the recent preliminary ECJ court ruling on whether UBO registers violate EU data protection laws.
  3. The report highlights the inherent complexity of TBML, therefore reinforces the point that identifying complex typologies with isolated transaction checks is a losing battle. Some interesting findings include:
  • A wide variety of merchandise can be involved
  • A wide variety of methods are used, even when one considers only the misinvoicing typology, which covers: falsifying the product, country of origin, value, ownership and even the existence of the product
  • TBML cases span on average 3 jurisdictions

    However, there are other points that are worth considering:

    • The report largely relies on the well-established TBML typologies such as over/under-invoicing, multiple invoicing and over/under-shipment for its case categorization. This does not acknowledge that these typologies require collusion as a prerequisite. Identifying social links between trading parties is one of the most direct ways to target TBML.
    • The report continues to align to traditional thinking on TBML: while it acknowledges that any merchandise can be used to launder funds, the authors still resort to listing goods, despite that monitoring for specific lists of high-risk goods has shown limited risk identification results.
    • Making national UBO directories mandatory and publicly available is very powerful, however the report is silent on how this information can/should be leveraged in the fight against TBML. Both governments and FIs require technology to bring it into holistic risk decisioning surrounding customers and counterparties.
    • The report highlights informal value transfer systems as a key TBML typology on par with over/under-invoicing, yet offers no suggestions as to how either governments or FIs can address this risk. Without a clear call to action, it should not be left to FIs to resolve the issue, rather governments should step in to drive potential solutions.
    • The report makes no distinction between trade finance and open account trade. With 80% of world trade carried out under ‘open account’ terms, the FI’s involvement is frequently limited to clean payments with no visibility of the underlying transactions, making many of the report’s observations non-actionable, at least for FIs.
    • While the report recommends the need for governments to invest in new technologies, it specifically references the pricing of trade transactions, despite the authors’ own findings being broader e.g. the misinvoicing methodology (accounting for 63% of all methodologies analyzed) includes a range of falsification methods, not all of which are specific to price (such as phantom shipments or the misrepresentation of goods). The analysis carried out by the authors was built on UN Comtrade import/export data to identify broad value gaps rather than transaction-specific price discrepancies and a more detailed analysis was only possible where disaggregated customs data was available.

    In the absence of access to structured customs data with detailed goods categorization, organizations will need to continue to rely on broader risk identification approaches, e.g. by monitoring for collusion risk.

    Do you agree?

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