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The recently revealed $8.8 billion Troika Laundromat offshore money laundering scandal was a vast and complex deception. Not just a limited scheme, between 2006 and 2013 it facilitated fake trade deals, reinsurance fraud, tax evasion, hidden investments, a fuel pricing fraud scheme at Sheremetyevo Airport—and much more.
The Organized Crime and Corruption Reporting Project and other news organizations are publishing the details. Formerly-prestigious Troika Dialog, a Russian investment bank, was the main force behind the laundromat. But perhaps twenty banks were involved – and many of the organizations involved as counterparties will have had compliance programs in place. Why didn’t they detect the activity when it was happening? With nearly $9 billion in transactions, how did Troika Laundromat run silently for years?
Change the static approach to anti-money laundering
Part of the problem is the static methodology. Money laundering is a contagion that needs an active approach to stop it when it shifts to newer, more complex and harder to find schemes. An active approach means better customer profiling and segmentation to add depth of information to the monitoring process. It also means that passive AML controls and rules are no longer sufficient, nor is maintaining the same methods as before to stop emerging forms of money laundering and tax avoidance. AML compliance is becoming more than just obeying the rules, but also having all the information and using it effectively and intelligently.
Create a transparent environment, not just a compliant one
Another part of the challenge that banks must overcome in spotting money laundering is finding the scheme hidden in the high number of transactions, or the needle in the needle stack. The Troika Laundromat took advantage of this by creating thousands of phony transactions to hide the true nature of their activity.
Even with a scheme and web of shell companies as large as the Troika Laundromat, an integrated approach to AML compliance could provide insight beyond basic structuring and questionable transactions. An active and integrated AML approach that produces transparency includes:
- Insight on geographic risk. This assesses heightened risk of entities and individuals based on where they were located and who they did business with.
- More stringent enhanced due diligence delivers deeper understanding of medium and high-risk individuals, based on more than just basic demographics, products and anticipated counterparties. Analyzing business directories, stored bad actor repositories, and news publications allows earlier visibility into potential risks and criminal relationships.
- Changing from a rules-based system to one that truly learns can separate suspicious activity from low risk It gives banks the ability to understand whether their customers and counterparties are using them to facilitate criminal acts.
This approach helps banks assess risk and rates countries according to their risk of money laundering and terrorist financing as a first step. It automates and improves screening and pinpoints previously unknown risks in business and other relationships. Cognitive capabilities deliver comprehensive know your customer insight and compliance. They also help reduce the false positives that take time away from analysts to analyze and investigate highly suspicious activity like the kinds that were perpetrated here.
Tie it all together in three steps
Making the shift from the current approach to one that better utilizes information and resources takes three fundamental steps:
- First, make sure you have the tools to gather all the data: Where entities are, who they are, and who they do business with.
- Second, use technology to eliminate unnecessary data gathering and give your analysts more time to do their critical work. Make decisions based on accurate and more complete data.
- Third, break down the silos between teams and treat financial crime as the interconnected discipline it is. AML involves multiple types of fraud, tax evasion, illegal trades and other crimes. Fight money laundering the same way the perpetrators conduct it, with multi- and cross-channel detection, discovery and investigation. We have to find the bad actors, not just the questionable transactions.