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Laura Hutton, Executive Director at Quantexa

Financial crime, especially money laundering, remains a complex issue for financial institutions to tackle.All banks have Anti-Money Laundering (AML) systems in place, yet global money laundering transactions are still estimated at 2 to 5 per cent of global GDP– US$800 billion and US$2 trillion – but only 1 per cent is seized by authorities.

Over 25 per cent of financial services firms have not conducted AML/CFT (Combating the Financing of Terrorism) risk assessments across their global footprint (PWC).This is compounded by out of date systems that fail to detect the complex money laundering schemes perpetrated by organised criminals that inundate investigators with large numbers of low quality alerts (in excess of 99%). It is no surprise that criminals are continuing to find loop holes.

Nevertheless, 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 new opportunity for banks to create stronger barriers to fight against these criminals.

Outdated systems and false positives 

Banks across the sector installed their current AML systems as a reaction to increasing regulatory pressure, with investment focused primarily in the retail lines of business. Most repurposed those same systems elsewhere as opposed to building bespoke systems which would be better placed to address the risks faced.

The result? Hugely ineffective and inefficient systems that generate colossal numbers of low quality alerts. Currently 99%+ of alerts are false positives, yet analysts are legally obliged by legislation to investigate all, regardless of legitimacy. These investigations are labour and cost-intensive and result in the analysts distrusting the detection systems they work with. Moreover, it leads to the outsourcing of the investigation processes to lower cost resources with little financial crime knowledge, employed to do basic box-checking processes. This is something that criminals have been able to actively capitalise on, and as such, is becoming an absolute priority for banks in terms of improving their systems.

Remove the blinkers

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. Typically, low-level individuals deposit cash into the banking system in low volumes to avoid detection.Higher level criminals then move these aggregated funds around in larger volumes and overseas. This is a complex structure, designed to avoid raising suspicion and subsequently makes it incredibly difficult for banks to define certain AML transaction monitoring systems (TMS) requirements that identify risk at an acceptable level of false positives.

The use of basic analytics and limited data has prevented current systems being able to make the sort of judgements required to identify well-hidden activity. Vast quantities of data are available, yet it is not made use of – analysis is conducted across a thin slice of data, solely at the transactional or account level, leaving masses of potentially incriminating data uninterpreted.

As a result, sophisticated money launderers are going unnoticed. Banks and financial institutions must act now to be able understand the wider context surrounding the money flows they support, in order to reduce their vulnerability to illegal activity.

A new approach 

In order to address these vulnerabilities, banks need to take a fresh, modern approach to their AML systems in order to combat fraudulent activity. It is clear that banks are treating money laundering as single transactions, rather than a web of connected parties and international corporate structures. Understanding the network and its wider context is the first step into reducing false positives and becoming more efficient and effective in the fight against criminal activity.

Thankfully, new practices are becoming more accessible. Contextual monitoring uses entity and network analysis techniques, in combination with advanced analytical methods to detect anomalous and suspect activity. Taking a holistic approach allows banks to risk assess networks of connected entities and to provide an aggregated view of the risk these networks pose. The result is a significant reduction in the number of false positives and an increase in the number of good quality alerts being raised for investigation.

Money laundering continues to remain a large-scale issue for banks and financial institutions alike. As the criminals get smarter, current stubborn AML systems remain in the dark ages. To make use of the vast data assets now accessible to banks, they need to adopt new compliance technologies and understand criminal networks more widely rather than as single transactions. Only then will banks and financial institutions reduce their vulnerability to money laundering.

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