DO NOT WAIT for a platform adoption which will allow you to accurately detect a number of Trade-Based Money Laundering suspicious patterns.

What are we talking about ?

Trade-based money laundering (TBML) is a sophisticated method used by criminals and illicit organizations to launder money and hide the proceeds of illegal activities through international trade transactions. It involves manipulating trade invoices, prices, and shipments to obscure the true nature and origin of funds.

One of the key risk factors associated with TBML is its potential to facilitate other illicit activities, such as corruption, tax evasion, fraud, and terrorist financing, and that is how a Financial Institution can see itself embarked in bad cases with consequences of reputational and regulatory nature .

TBML can be used to transfer funds across jurisdictions, bypassing regulatory and financial controls, and disguising the true beneficiaries of the funds. This makes it a favored method for criminals and terrorist organizations to finance their operations and launder their proceeds, posing a threat to the integrity of the FI.

Another major challenge is the complexity and opacity of trade transactions, which can create vulnerabilities that criminals can exploit. The sheer volume and complexity of global trade, involving numerous parties, jurisdictions, and documentation, can make it challenging for the FI to detect and prevent TBML. Inadequate trade documentation, weak investigation and non holistic view based analysis, inconsistent regulatory oversight, and a lack of transparency in supply chains, sometimes a mere lack of understanding of that activity by some users recently hired or not versed into Trade Finance, can create opportunities for criminals to exploit loopholes and engage in TBML activities with your FI without you being aware of it.

The consequences of TBML can be severe and far-reaching.

For you as a compliance officer, as you already well know, TBML can result in financial losses for your FI, reputational damage, regulatory sanctions, and legal liabilities. Your FI may unknowingly become involved in TBML schemes, resulting in unintended consequences, including disruptions to the supply chains of your customers, customer & partner friction, damage to their brand reputation and to your own image as an FI.

What should a software vendor be offering within that space ?

For a software vendor, offering the financial institutions a set of models on TBML requires a thorough understanding of the topic and the ability to implement complex indicators which are being fed by some external sources of information on vessels, routes, and goods / pricing which will have to be updated and made reliable enough.

Here are some steps that should be followed when dealing with TBML challenges in a Financial Institution:

Business Analysis is key and should be translated into relevant AI features:

-start by conducting in-depth analysis on TMBL risk factors extending your work beyond your current knowledge of some already known risk factors by the organisation, there is growing expertise on the market that you should leverage.

-make sure that users can familiarize themselves with the definition, AI methods, and some TBML Machine Learning based models offered by the vendor which will allow the FI to save time and efforts around building those same models, and truly aim at detecting the unknown behaviours.

-explore case studies which are putting the FI at risk, the current reports, and data from reputable sources such as international organizations, government agencies, specialised maritime organisations and data providers focusing within that field their efforts on getting some valuable and meaningful primary risk indicators.

Users will also have to take note of key concepts, trends, and challenges related to TBML, so that the level of awareness is increased and the value we get our of their analysis is heightened.

How will you be implementing true and reliable detection capabilities ?

You will set up a realistic enough project plan which will be agile and will go through some short iterations as to the models to be implemented, too many projects have failed because of an excessive coverage and ambition.

You will very rapidly focus on different methods of TBML, such as over- and under-invoicing, multiple invoicing, and phantom shipments. You will be able to test your models on the basis of real cases in order to stress test your approach.

Next, you will discuss the consequences of not implementing a set TBML risk factors through a prioritisation of those same indicators, including their impact on the detection capabilities.

As a general, you will use a clear and concise language when interacting with the users, avoiding jargon or technical terms that may be difficult to understand. You will present facts based on real alerts, data, and evidence from reputable sources to support your outputs, and consolidate your alerts into cases, so that the end result is meaningful for the investigator.

You will also provide constant recommendations and solutions to further extend the scope of your TBML project, once the first stages have proven successful.

You will also try and keep away from the complexity of an intensive paper based activity generated by many shipping and trade finance documents, by digitalizing them and extracting some valuable information though relevant correlations and a real time check of potential inconsistencies at the source level when the document is being loaded and scanned, AI coming at your rescue at this stage.

You will never stop analysing existing regulatory measures and their limitations and you will propose practical and effective incremental iterations that can be implemented, such as enhanced due diligence, information sharing among branches, and leveraging technology to track and trace trade transactions.

Will you still avoid running into trouble ?

Identifying and define Risks Factors to then transform them in Machine Learning features is a true challenge for data scientist and investigators.

Identifying the specific risks associated with TMBL hand in hand with an experience software vendor will allow you to ring fence each risk, and will allow you to feed a global risk assessment plan at the group level.

Being aware of vulnerabilities by properly identifying them in the trade process will make the prevention possible and reduce your exposure to a risk of non detection of huge amounts being laundered.

Moreover, overcoming the weaknesses or failures in trade documentation, customs processes, supply chain management, and regulatory oversight, can only happen through the implementation of a reliable and mature solution with an end to end coverage of your requirements.

You will stop the vulnerabilities which can be exploited by criminals and mitigate the risks they pose to the integrity of your trade activities.

Constantly re-evaluate the existing measures and best practices which have been implemented to mitigate the risks of TBML, such as detection fine tuning, dynamic KYC & due diligence procedures, enhancing trade documentation, record-keeping, improving regulatory oversight, and leveraging technology for trade transparency and traceability.

This journey might be challenging indeed, but only a software vendor versed into that domain with a true coverage, will allow you to make that trip safe.