Regulators are increasingly interested in trade-based money laundering and banks are feeling the pressure to stem the flow of illicit funds. Joy Macknight investigates how banks are using emerging technology to improve their effectiveness.

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International trade flows are under scrutiny, as governments and regulators around the world try to get a handle on trade-based money laundering (TBML). Criminals, such as people traffickers, drug smugglers and organised crime groups, can potentially use legitimate trade transactions to mask illicit gains and move funds around the world through methods such as multiple invoicing, mispricing goods and phantom shipments.

As regulated entities, banks are feeling the heat – particularly in the trade finance arena, where they have oversight of trade documentation, such as letters of credit (LoCs), bills of lading, invoices, confirmations and payment orders. “There are no more complex requirements for financial institutions to penetrate than TBML,” says Vincent Heintz, regional head of financial crime compliance (FCC) for Europe and Americas at Standard Chartered.

Camouflaged by complexities

The complexity stems from the nature of trade, involving multiple parties such as banks, shipping companies, logistics firms, port authorities, manufacturers and wholesalers, each of which uses its own documentation. Mr Heintz adds: “It is a wilderness of complexity when it comes to paperwork, which creates ready camouflage for sophisticated criminal actors to facilitate the illicit transmission of criminally derived value in the form of actual goods or payments.”

An additional complication, from a banking perspective, is that of all the private sector actors involved in the trade value chain, only financial institutions have an affirmative, legal and regulatory obligation to assess the risks around trade finance, monitor transactions, detect suspicious activity and affirmatively report that activity to law enforcement and regulators.

Regulatory guidance has emerged from many active jurisdictions, including Singapore, Hong Kong, the US and the UK, as well as international bodies. For example, the Financial Action Task Force (FATF) issued a set of countermeasures against money laundering, commonly called '40 recommendations', in 2004 and two years later released a paper specifically on TBML, which identified 16 red flag indicators. “Every bank managing trade activity must embed FATF’s recommendations into their processes and adapt them to their environment,” says Idrissa Diop, director of the compliance department at African Export-Import Bank.

Red flags

Industry groups also weighed in. In 2015 the Bankers Association for Finance and Trade (BAFT) published ‘Guidance for identifying potentially suspicious activity in letters of credit and documentary collections’, adding guidance to the FATF and other organisations’ red flags. Two years later, BAFT, the Wolfsberg Group and the International Chamber of Commerce (ICC) jointly published a paper, ‘Trade finance principles’, which was updated in early 2019.

However, it is important to remember that trade finance activity makes up less than 20% of world trade. The vast majority is carried out under ‘open account’ terms, where the buyer and seller agree to the contract among themselves, without a bank intermediary. As such, the bank only executes the payment, without any visibility into the transaction.

BAFT’s August 2017 paper, ‘Combating trade-based money laundering: Rethinking the approach’, addressed this quandary. Tod Burwell, CEO and president of BAFT, says: “We looked at what things banks can do to try to mitigate this problem, what they can’t do and who else in the ecosystem is better positioned to contribute to the solutions to the problem.”

The paper makes three proposals: greater information sharing across all stakeholders involved in trade transactions; deploying emerging technology, such as artificial intelligence; and more robust data analytics. On the final point, Mr Burwell says: “Trying to drill down into the data related to trade suspicious activity reports [SARs] doesn’t produce sufficient clarity. There needs to be a better way to capture, track and analyse data around trade and TBML.”

He references an initiative, led by the Asian Development Bank, to develop an SAR template adopted specifically to trade. “I am hopeful that by the end of 2019 we will have a template that the industry can rally around," says Mr Burwell. "Then it will be up to us collectively to see if financial intelligence units and regulators around the world would be willing to adopt and support that, because that would enable data analytics to drill down on the problem.” 

Sharing information 

A significant hurdle to fight TBML effectively is data protection controls that limit cross-border information exchange. “Such controls restrict the ability of financial institutions, as parties to a trade transaction, from accessing the relevant information required for due diligence on other parties. This will impact upon the effectiveness of transaction monitoring and screening,” says the BAFT, Wolfsberg Group and ICC paper.

“True insight can only be generated if all banks around the globe could share data; otherwise a transaction that was rejected by one bank can easily be re-submitted to another bank. Organised crime could potentially arbitrage the banks and use ones that have the lowest compliance controls in place,” adds Enno-Burghard Weitzel, head of product management trade services at Commerzbank. “With daily or real-time information sharing, it is possible to upscale the effective compliance controls at all banks that participate in that information sharing.”

On an international level, a recent step forward was the first meeting of the FATF supervisors’ forum in mid-November, which brought together 100 senior financial and professional supervisors from more than 40 countries to share their knowledge and experience. Enhancing international co-operation between national supervisors to improve the effectiveness of cross-border supervision was top of the agenda.

Some jurisdictions are already allowing greater data sharing on a domestic level. Michael Shearer, global head of product management, financial crime threat mitigation at HSBC, points to the UK’s Joint Money Laundering Intelligence Taskforce (JMLIT) as an example of a public-private partnership through which banks can share information with law enforcement and one another. “These engagements are proving valuable,” he says. “Information sharing is key to making these connections and enabling us to join up to truly fight crime on an international scale.”

Joint efforts

Daniel Wager, vice-president, global financial crime compliance, at LexisNexis Risk Solutions, who was a US federal agent for more than two decades, points out that it is never just one bank involved end to end in TBML. “It is inherent in the money-laundering process to use multiple institutions because it means no one has possession of the end-to-end information illuminating the illicit activity. It may be financed by one bank with a standard LoC, but the payment will be made to a different financial institution, so no one can see the disparity between the goods that were supposed to move and the actual payment that was made,” he says.

He agrees that the UK JMLIT model has made advances in opening protected dialogue between financial institutions, regulators and enforcement agencies; similarly, the US Financial Crimes Enforcement Network’s Bank Secrecy Act Advisory Group has encouraged dialogue and public-private co-operation.

“There is a virtuous cycle of intelligence sharing and the picture becomes three dimensional in terms of the threats and risks we are up against,” adds Mr Heintz. “The public-private partnership model is the way forward. It is at least as and arguably more effective than the traditional algorithm-driven, transaction monitoring approach that banks are expected to do.”

Standard Chartered also uses its Correspondent Banking Academy to educate and share information across industries, law enforcement agencies and regulators. “The academy has two aspects: the conferences, which have the look and feel of industry conferences, and a portal that we’ve established to allow professionals to log in and benefit from our training materials,” says Mr Heintz. “There are many ways to share information and given the complexity of trade it would make a compelling case for others in the trade value chain to join in.”

“We are beginning to see far more collaboration, co-operation and willingness of the banks to become much more open with their data. Open banking, which applies to the current account and loan space, may need to apply to trade finance as a mechanism for combating TBML,” says Dr Rebecca Harding, CEO of Coriolis Technologies, a fintech that provides data-as-a-service for trade and trade finance sectors.

AI and data

While agreeing on the need for greater information sharing across the trade ecosystem, Colin Camp, senior director of business development and sales, Asia-Pacific, at tech platform Pelican, focuses on the advances made in AI, natural language processing, optical character recognition (OCR) and machine learning that is enabling efficiency in compliance through data extraction and contextual analysis. “There is no point in everyone getting together to share data if you don’t have the tools to mine and interrogate it,” he says.

“Banks are starting to see the benefits of using technology to do the manual and menial tasks around checking documents and extracting data, which is the biggest challenge for [them],” adds Mr Camp. “They can now refocus staff on doing the tasks that really matter, such as the investigative work.”

Mr Diop agrees. “Today we are conscious of the risks associated with our activities and that we can’t continue with manual checking," he says. "We need to invest heavily in technology; compliance officers can’t deal without it. The way to frame, control and mitigate those risks is to invest in systems that allow compliance teams and the business to have a better understanding as to who they are financing, the product and the environment where they are active.”

The real problem for banks is what they do not know, according to Ms Harding. “There is no transparency upstream and downstream in trade finance supply chains,” she says. “But new technology has mastered a way of finding out what we don’t know. AI and machine learning are basically gap-plugging tools that allow us to understand more in those black holes.”

Leveraging fintechs

Since it is difficult to quickly build AI and data analytics capabilities in-house, banks are collaborating with fintechs and integrating their solutions into their processes and systems. For example, Adrian Rigby, chief operating officer, global trade and receivables finance, at HSBC and his team, together with their FCC colleagues, have been collaborating with data analytics start-up Quantexa to create an automated system for money-laundering controls, based on contextual monitoring using both internal and external data.

The solution, built on the platform that picked up The Banker’s 2019 Tech Projects Award for Compliance, was launched in the UK and Hong Kong, HSBC’s two biggest markets accounting for about 35% of its global trade volume‎. Mr Rigby says it has already proved to be an effective control at quickly identifying problematic transactions in the first months since going live. The bank plans to roll out the solution in 35 additional markets by the end of 2020.

“We are deploying this solution to make sure we detect more financial crime and have greater control. But we are also using it because the manual control we have across every transaction impacts the 99.9% of our customers and counterparties that are not involved in financial crime – so we were also looking to improve customer service,” says Mr Rigby.

According to Mr Shearer, HSBC partnered with Quantexa to bring in expertise on combining internal and external data sets to give banks a richer contextual picture. “This contextual picture is critical, because it allows us to see the wider network connected to a trade, not just transactions in isolation. We need to see the whole picture to understand the behaviour of any individuals in the network who are seeking to exploit the bank’s services to commit crime,” he says.

“We are also combining this data with data inside the bank,” says Mr Shearer. “This means that if other investigations are triggered – let’s say by our transaction monitoring systems or by law enforcement or staff – then we can make the connections to the trade world. Also, if we identify a suspected criminal actor, we can make connections across all of our business lines so that we avoid doing business with them in another.”

Emerging technology

Alexon Bell, chief product officer for anti-money laundering at Quantexa, explains: “[Our solution] is a combination of technology that has only emerged in the past three years: highly scaleable big data platforms, and the ability to create and generate networks at scale by leveraging open-source platforms to parallelise compute across large data infrastructures.”

Quantexa has several projects under way at other banks – it recently announced a partnership with Standard Chartered – and is expanding into fraud detection. “We are expanding across the life cycle of trade, not only post-trade monitoring but fraud solutions that are pre-trade. For example, a bank might receive an LoC and Quantexa would do a check before the bank sends the money, potentially telling it not to send the money,” says Mr Bell.

Commerzbank is experimenting with AI, OCR and machine learning and is also talking to fintechs such as Coriolis. According to Mr Weitzel, the bank is in discussions around integrating pieces from fintechs into its trade finance processes. “The space is very vibrant, with highly interesting fintechs that provide very niche solutions to the overall problem,” he adds. “However, one technical challenge that all banks are facing is how to integrate these solutions seamlessly into the internal compliance process for trade finance.”

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