As new research highlights the explosive growth of the anti-money laundering (AML) software market, VIXIO speaks with vendor Lucinity about the challenges and opportunities of the industry.
A new report has found that the global AML software market is set to triple in size in the years ahead, driven by increased legal requirements for financial institutions and increased use of artificial intelligence (AI) tools.
According to the latest data from Research and Markets.com, the value of the AML software market is set to grow from $2.1bn in 2021 to $6.2bn by 2028.
The projection comes at a time of increased focus on AML issues among regulators and payment service providers (PSPs) alike, as new threats from the growing adoption of e-wallets, instant payments and cryptocurrency continue to complicate the landscape.
In a statement on financial crime risk in digital payments, published in June this year, consultancy firm McKinsey & Company referred to AML controls as a risk that can pose an “existential threat” to PSPs.
"Perceived weaknesses in the controls applied by electronic-payments platforms will consequently draw attention from regulators,” wrote Daniel Mikkelsen, a senior partner at McKinsey.
“Banks, furthermore, are increasingly expecting the PSPs that form part of their network to have strong anti–money laundering (AML) and fraud controls in place.
“Rather than wait for new regulation, PSPs can move proactively, incorporating lessons from banks’ experience while utilizing their own advanced technological skills.”
Similarly, in a report published in July last year, the Financial Action Task Force (FATF) wrote of the need for new technologies to fight financial crime amid the “profound impact” of the digital transformation of the financial system.
“New technologies have the potential to make AML and counter-terrorist financing (CTF) measures faster, cheaper and more effective,” said FATF, noting specifically how the use of AI can “help to better identify risks and respond to, communicate and monitor suspicious activity.
The benefits of AI
Lucinity, an AML software company that was founded in 2018, is one such provider that is responding to FATF’s call.
Based in Reykjavík, Iceland, Lucinity builds AI-powered systems that help clients to understand their customers’ transactions in as close to real time as possible.
Daniel Pálmason, vice president of legal and compliance at Lucinity, told VIXIO that the company sees itself not as a replacement for human AML analysts, but as a tool that can significantly reduce the time they spend crunching numbers.
Pálmason claims technology in this area has been quite stagnant for the past 20 years and it is something he and his company are changing.
“We create solutions that are modern, intuitive and can hopefully help to revolutionise the AML software industry,” he said.
“Our main focus is to make the lives of our analysts easier, so we use artificial intelligence to eliminate as much of the noise as possible.
“We bring forward the necessary information in a very intuitive manner that tells a story so that they have all the information they need right in front of them to make the best decision.”
But ultimately, human decision-making is still a vital component in the fight against money laundering, as Pálmason explained.
“Humans are best at putting things into context, learning from experience and recognising the intangibles when it comes to money laundering,” he said. “Their time is best spent making the decisions.”
Pálmason said that AML solutions are faster at recognising patterns and risks, helping to reduce the amount of time an analyst might spend looking at months worth of data to minutes or even seconds.
“Of course, if you were to put me in front of every transaction, I could do the job very well, but it would take me years to go over what the computer can do in one day.”
According to Pálmason, banks and PSPs typically deploy their AML software solutions to support their activities in high-risk sectors, such as gambling, charities, construction, cash-intensive businesses, high net worth and individual wealth management.
Lucinity says its solutions can be adapted for each sector, so that new risk factors and new types of pattern recognition can be applied to each.
For example, transaction-based risk factors could include volume of transactions, timing of transactions, origin and destination of transactions, and patterns in cross-border transactions.
Users can then combine these with other non-transaction-based risk factors such as sanctioned entities, adverse media and politically exposed persons (PEPs).
”You can apply certain models to recognise the patterns, and you can construct models that are typical for individual sectors,” said Pálmason, adding that “it is all a matter of identifying the risks and then enhancing the models to account for those risks”.
Out with the old
This year, UK Finance, a trade association for the banking and financial sector, highlighted the risk of using “legacy technology” as one of the top four innovation challenges in the remittance and AML industry in 2022.
“As guidance issued by many regulators indicates, fraud and financial crime typologies are becoming more complex in many areas,” said UK Finance.
“Manually delivered regulatory and financial crime risk management regimes struggle to identify many of these threats, capture the correct data to act quickly, mitigate losses and avoid regulatory breaches.”
One of the biggest challenges for firms offering AML solutions is the sharing and combining of data across different providers due to ownership and privacy concerns.
In the UK in 2018, for example, Pay.UK announced that Faster Payments would launch a new solution offered by Vocalink, the processor of Faster Payments, to help track and stop the use of money mules for money laundering.
This aimed to solve the problem that banks had at an individual level; as soon as the transaction left the bank, it would be impossible to follow the flow of money.
However, by partnering across several banks, it would be possible to deploy machine learning to identify patterns, follow illicit flows and shut them down.
“By bringing together payments data from multiple banks in a secure way, we are able to deliver a new kind of intelligence that analyses billions of transactions, connects the dots and then identifies how the laundered money is split, layered and dispersed across the whole banking network,” said David Rich, executive vice president for financial crime solutions at Vocalink, speaking at the time of launch.
At Lucinity, Pálmason said the company uses raw transaction data provided by its clients, and this is sometimes combined with open-source data from providers such as Experian, which is a partner of Lucinity.
However, in the US, Lucinity says it has a patent for a system that will allow it to analyse multiple clients’ data simultaneously without mixing it together or revealing it to non-custodians.
This is likely to be one of the key focus areas for Hjörtur Líndal Stefánsson, who joined Lucinity this month as chief technology officer (CTO), following a six-year stint as an engineer at Amazon.
In its report on AML/CTF technology last year, FATF noted that data sharing and ensuring data quality are likely to be priority areas in the years ahead.
“The increased effectiveness of AML/CTF is limited by the inability of regulated entities to share information with their counterparts and across borders,” said FATF.
“Ultimately, to fully understand the nature and risk of suspicious transactions, actors require access to their full pathway which is often beyond borders or held by other entities.
“New technologies may offer significant value to overcoming this challenge.”