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Here Laura Hutton, Executive Director at Quantexa, explains the money laundering phenomenon, describing the typical profile of a money laundering ring, the added variety some display, and the challenges banking systems currently face in identifying money laundering systems.

Global money laundering transactions are currently estimated at 2 to 5% of global GDP, or up to US$2 trillion, funding crimes such as terrorism, corruption, tax evasion, drug and human trafficking. By 2020, experts predict that there will be more than 50 billion connected devices across the world. This is a cause for concern for banks and financial institutions alike, as criminals will be attracted to fresh ways to communicate and partake in criminal activity.

Shockingly, over 25% of financial services firms have not conducted AML/CFT risk assessments across their global footprint (PWC) – so it is no surprise that criminals are still finding loop holes. However, according to Wealth Insight, global AML spending is predicted to rise from US$5.9 billion in 2013 to US$8.2 billion in 2017 – promising a stronger barrier to money laundering activities. In part, this has been driven by the increasingly strict regulatory landscape and some eyewatering fines, but organisations are also keen to tackle the problem for both moral and reputational reasons.

The profile of a money laundering ring

The vast majority of money laundering is committed by organised criminal gangs and involves a complex web of individuals, businesses, domestic payments, overseas wires and increasingly trades and settlements. These gangs will need many low-level individuals who deposit cash into the banking system, typically in low volumes to avoid detection. The gangs will then need to move the aggregated funds around in larger volumes and overseas. This is a complex structure and designed to avoid raising suspicion.

One size doesn’t fit all

All banks will have AML systems in place, but this doesn’t mean they are correctly suited. At first, financial institutions put in place systems to detect money laundering within their retail book, looking for simple patterns like large cash deposits in short time periods or transactions which are unexpectedly large for a standard domestic customer. This may flag some of the low-level criminals, but the modern organised criminal is choosing to hide the activity elsewhere, for example, cash-heavy businesses and financial markets where the transaction volumes are significantly bigger and where overseas transactions are the norm.

Banks and regulators realised that these non-retail products had money laundering risk, but no tailored AML systems existed for these complex products. As a result, many organisations have simply repurposed existing retail and market abuse systems that inevitably aren’t suited to the product line that they are trying to protect. A pre-configured AML system for retail banking will focus on finding individual high-risk transactions without the context of corporate structures, geographical money flows and the complex behaviour of that product type. Consequently, these systems are less able to identity suspicious behaviour and do not effectively prevent money laundering.

Time for a new approach

To address the more pressing money laundering risks, and greatly reduce their vulnerability, banks need to take a different approach that can interpret and risk assess these complex webs of activity and present them assembled and ready for investigation. Money launderers are not transactions, they are individuals, and they need to be modelled as such.

The contextual monitoring approach uses entity and network analysis techniques, in combination with advanced analytical methods to uncover the hidden web of criminal activity and highlight these holistically as an aggregated view of risk across multiple products and data sources.

This eliminates the vast number of alerts generated at the transactional level and focusses the attention on the high-risk people, businesses and networks that underpin these criminal gangs.

Money laundering remains a great issue for banks and financial institutions alike. As the criminals get smarter, current AML systems are falling behind. To beat the criminals at their own game, banks must adopt new compliance technologies to make constructive use of the infinite data accessible, join the dots in their customer network, and then become more efficient when acting against illegal money laundering activity.

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