Money launderers’ profile has changed, banks’ AML defences slow to adapt

The Panama and Paradise Papers’ publication as well as the current probes into Russian interference in U.S. elections have shifted counter-money laundering officials’ views on who money launderers are. Financial institutions, too, must change their understanding of who launders money, why and alter their strategies to defend better against a wider range of illegal activity. That change has been slow in coming.

“The role of the money laundering reporting officer is to employ policy and procedures to defend against money launderers. These days there are more and advanced threats than banks can keep up with. Money launderers are well-funded, smart people who can get through banks’ defences. They have the ability to stay one step ahead,” said Julian Dixon, chief executive of Fortytwo Data, an antimoney laundering software provider in London.

Money launderers’ profile has evolved Money launderers tend to be characterised as criminals engaged in illicit cartel activities such as drugs but officials warn that increasingly money launderers no longer fit that profile. That population is viewed now as more varied. “The collective view is evolving away from the traditional picture of what money laundering is — gangs and organised criminals laundering the proceeds of their drug business — to a more variegated set of crimes that can generate proceeds and other nefarious activities,” said Kelvin Dickenson, managing director compliance and data solutions at Opus in New York.

Money launderers increasingly are individuals seeking to evade taxes or governments channelling cash to fund espionage and other illicit activities. “If we think about all the influence peddling that’s happened in the last few years such as foreign governments influencing election cycles that takes a lot of money. If you follow the money you find where the influence peddling is going on. That is tied into illegal campaign contributions, non-registration of foreign agents and a whole host of other crimes that require money to finance them,” Dickenson said.

In addition, like fraudsters and cyber criminals, money launderers are skilled at staying one step ahead of financial institutions’ AML defences. “Criminals throw a lot of resource at money laundering schemes. They hire sophisticated individuals, lawyers, mathematicians, who are good at finding weaknesses in banks’ defences,” Dixon said. Beneficial ownership still difficult to determine Understanding beneficial ownership is key to tracking down money launderers, especially those involved in tax evasion and politically motivated illicit activities.

Europe’s Fourth Anti-Money Laundering Directive (4MLD) requires firms to understand beneficial ownership, but in practice it’s difficult to do. “It’s a tremendous challenge for banks to keep up with that. There are very few straightforward sources you can go to. For the most part you have to ask clients for their beneficial ownership structure and documents that can prove it,” Dickenson said. Even in countries such as the UK where company ownership is supposed to be transparent, companies do not always fulfil their disclosure obligations.

Companies House, the UK’s database for corporate information, revealed more than 57,000 UK businesses were non-compliant with new regulations requiring them to declare People with Significant Control (PSCs) over a business. Companies House provided this information to Fortytwo Data in response to a request under the Freedom of Information Act. “Gathering a single view of an account, customer and organisation is high in importance, but difficult to get. It’s especially difficult to get information on ultimate beneficial ownership in countries that have secretive company filings,” Dixon said. 5MLD requires European member states to establish publicly accessible registers of beneficial ownership for all legal entities, such as the UK’s Companies House.

In theory, these registers should be a boon to banks AML teams; however, it is expected that implementation will vary from country to country. There are no requirements for standardisation, for example, so data quality and usefulness will depend on how much resource a member state devotes to the register. False positive fatigue Money launderers’ increasing sophistication, varied profile and motivation means financial institutions’ traditional defences such as transaction limits have become less effective. Transaction monitoring teams are less able to pick out suspicious activity.

There is plenty of room for improvement in targeting suspicious behaviour and transactions, Dickenson said. “Most banks are somewhat behind the eight ball in the way they monitor transactions for suspicious patterns. There is a massive quantity of transactions that may hit a threshold that may hit a tolerance and would need to be looked at, but the overwhelming majority of them are not actually suspicious. You have this fatigue where analysts look at transactions only to dispense them as not suspicious. When they do see something suspicious it is likely they will overlook it because they have gotten into a rhythm of seeing false positives,” Dickenson said.

Deployment of artificial intelligence tools limited Like other areas of regulatory compliance activity and financial crime prevention, there has been a lot of investigation into using new technology like artificial intelligence to improve outcomes and reduce costs. “AML can be done better than it’s being done today. While banks are taking AML more seriously, their incumbent software is not working properly,” Dixon said. Naturally firms are curious about using new techniques to gather intelligence on beneficial ownership, identify suspicious patterns and monitor transactions. “The current trend to defend against that is to adopt AI and machine learning to better detect suspicious patterns.

There is a movement in banking — and I think the regulators are encouraging it — towards a more intelligent method of identifying suspicious patterns rather than using arbitrary triggers, thresholds and old-fashioned rules,” Dickenson said. While many banks are testing AI AML tools now, few are at the point of using it to replace or complement current systems. Moreover, not all regulators are at ease with AI, which discourages firms from using the technology. Another barrier to AI-powered AML tools is cultural. Some MLROs are reluctant to welcome new technology into their fiefdoms. Cost is another big factor slowing adoption. Even though fines and reputation damage are expensive banks still resist spending on defence.

Produced by Thomson Reuters Accelus Regulatory Intelligence 31-Aug-2018

Published 29-Aug-2018 by Rachel Wolcott, Regulatory Intelligence

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