How new technologies help prevent money laundering

Written by Jon Prentice on Tuesday June 18, 2019

$2 trillion – that’s the amount of illicit funds estimated to be laundered through financial institutions annually. Worse, financial crime appears to be increasing. In response, Europol estimate that banks globally are spending $260 billion each year in financial crime defences to combat the issue.

Recent years have seen a shift from the traditional methods of combating money laundering, to a more efficient, autonomous approach, with an increased focus on technology to aid compliance professionals to prevent, detect and recover the proceeds of criminal activity.

Artificial intelligence (AI), FinTech, machine learning, RegTech and big data are terms with which the compliance world is now familiar, but how are these technologies being used to prevent money laundering, and what does the future look like for a compliance professional as a result?

AI, machine learning and big data

AI, machine learning and big data have made tackling financial crime both faster and cheaper, and have allowed firms to adopt a smarter approach. Financial institutions are replacing the traditional black-and-white rules approach with a more technologically focused, flexible and holistic programme, capable of detecting anomalies a lot more efficiently.

Those processes that are typically slow and manual-orientated – such as transaction monitoring – are now being undertaken using AI and machine learning, which have the capabilities of scanning enormous quantities of data far faster than can human beings.

Traditional trigger alerts, such as a transaction being over a certain value, or a transaction being conducted outside the account holder’s country of residence, tend to produce a large number of false positives, all of which require human review in order to satisfy any concerns.

"AI has the ability to identify patterns of transactions, behaviours and anomalies rapidly, allowing compliance professionals to better spend their time."

However, AI has the ability to identify patterns of transactions, behaviours and anomalies rapidly, allowing compliance professionals to better spend their time analysing the results, investigating root causes and collaborating their findings with other financial institutions or authorities.

The utility of technology doesn’t stop at transaction monitoring. Big data has enabled organisations to move away from just tracking financial crime at a transaction level and start to ‘map out’ strings of transactions, enabling connections to be established and patterns to be detected in the data. This allows the organisation to more easily trace the original sources of illicit activity.

Through the use of big data, financial institutions gain a clearer understanding of the trail of illicit gains from activities such as drugs/arms/human trafficking, slavery, corruption, fraud, wildlife trafficking and other such crimes, in addition to establishing the individuals, entities and supply chains involved in the laundering process. This makes it easier to share information with other organisations and authorities in an attempt to reduce the flow of criminal money being laundered through their accounts.  

The FCA and TechSprint

The use of technology – along with collaboration – in order to prevent money laundering is something high on the list of regulator’s agendas, as is the case with the UK Financial Conduct Authority (FCA). 

In May 2019, the FCA held a three-day global anti money laundering and financial crime ‘TechSprint’, an event that addressed how new technology can be applied to combat money laundering and financial crime effectively.

Over the course of the event, 260 participants from 105 firms across 16 countries, together with a variety of other regulators and law enforcement agencies from the United States, Europe, the Middle East and Asia-Pacific worked on ways in which they could develop technologies and solutions to a number of problem statements.

The following ideas were generated at the event.

  • A shared database of ‘bad actors’, secured and distributed using distributed ledger technology. The database would allow a financial institution to query whether a new customer had been rejected by another financial institution due to financial crime activities or concerns.
  • Natural language processing, topic modelling and text analytics to enhance financial crime-focused transaction monitoring solutions within financial institutions.
  • Graph/network analytics to more readily identify relationships between entities to aid in due diligence and ongoing monitoring of potentially suspicious entities and activities.

The teams also developed various methods to enable:

  • Greater sharing of crime typologies/patterns between institutions to aid detection and intervention capabilities.
  • Querying by a financial institution of the confidential/encrypted data of another financial institution using homomorphic encryption and/or zero-knowledge proof technologies. These technologies could enable financial institutions to verify certain types of information with each other, without compromising the security or confidentiality of the underlying data.
  • Centralisation of data from multiple institutions into a shared utility, with the data then being analysed for fraud, money laundering and sanctions monitoring purposes.

A follow up to the TechSprint is scheduled for later this year, with the ambition that the sessions will ‘serve as a catalyst’ for cross-industry dialogue across a multitude of jurisdictions.

Find out more on how technology and collaboration is helping in the fight against human trafficking in our recent Insight

What lies ahead for the compliance professional?

It is unclear exactly how the role of a compliance professional will change in the future given the ever-evolving use of technology. However, there are strong signals that it will be heading away from the traditional approach to more of an analytical role. Technology is not only aiding compliance professionals in their day-to-day tasks, but also keeping up with regulations and the constantly evolving compliance landscape.

Because technology and autonomation will continue to reduce manual and repetitive tasks, compliance teams should have more time to analyse the outcomes of data and be able to focus attention on larger-scale suspicious case – as well as having more capacity to focus their attention on keeping up to date with regulations and ensuring that their firm’s policies and procedures are up to date, so that risk is reduced and regulatory standards are met.

This article forms part of the #BigCompConvo - Join us as we explore and debate the latest challenges and issues facing you and regulatory and financial crime compliance professionals all over the world. If you’d like to contribute an article as part of the Big Compliance Conversation get in touch with us at 

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