Cybersecurity Europe Insights

Firms Need to Use Tech to Mitigate Growing Money Laundering Threat

Money mule schemes, multi-customer cross-wallet activity and the use of crypto exchanges are the most common money laundering techniques, yet most firms are failing to make use of available technology to mitigate the threat, according to the latest research from Feedzai, the RiskOps platform for financial risk management.

The State of Global Anti Money Laundering Compliance Report surveyed 636 anti-money laundering (AML) compliance experts, representing 77 companies around the world, most of them from the financial services industry, and overall 74 per cent of respondents cited money mule schemes – both unwitting (44 per cent) and witting (30 per cent) – as the most common money laundering threats.

Furthermore, 56 per cent said that multi-customer, cross-wallet payment activity – a favoured tactic of money launderers as it enables them to move funds between different accounts to avoid detection – is the second most common money laundering typology.

The research also found that the crypto market is increasingly being targeted by money launderers; more than half (51) of the AML professionals surveyed said the use of crypto and other non-compliant exchanges is the most common money laundering threat, while 19 per cent cited crypto ATMs.

When asked what they believe the biggest challenges to their AML programmes will be over the next two years, the top answers were ever-changing AML regulations (17 per cent) – specifically around emerging markets and multi-customer, cross wallet activity – and crypto/blockchain (16 per cent), followed by product implementation (seven per cent).

However, despite citing crypto abuse as one of the biggest AML threats and one of the most significant challenges, just 26 per cent of firms currently monitor crypto risks. Furthermore, AML professionals also believe data sharing bolsters AML efforts, but 19 per cent admit their AML and fraud teams do not share data – even though a RiskOps approach helps identify money laundering sooner – and 15 per cent ‘don’t know’ if they do.

Feedzai’s research found that most respondents believe a collaborative approach to data is vital in the fight against money laundering; 61 per cent said automated collation of data from multiple vendors will be a top AML/KYC (know your customer) trend over the next five years, while half (50 per cent) said using a RiskOps approach for data sharing between FIs will bolster anti-money laundering efforts.

However, when asked what their main goals were for 2022, just 29 per cent said creating a single customer view and less than a quarter (23 per cent) said increasing data sharing between company departments. The top three priorities were achieving perpetual know your customer (pKYC) (54 per cent), reducing false positives (54 per cent) and accelerating AML investigations (45 per cent).

Nick Parfitt, principal, AML SME, at Feedzai said: “Money laundering threats are constantly evolving. Our data shows that multi-customer, cross-wallet payment activity to move funds between different accounts, and the use of crypto exchanges are the top money laundering tactics, and that doing more to address these challenges are all top concerns for AML compliance teams.

“Yet, most respondents named implementing pKYC and reducing false positives as their main goals for 2022, revealing there is still some misalignment on how to address AML going forward.

“AML compliance professionals often feel like they are constantly catching up to address the latest financial crime patterns, frequently using yesterday’s technology and tools to address tomorrow’s money laundering challenges.

“Taking a RiskOps approach provides a path forward to make better use of data, do more to address the threat of cryptocurrency and enable AML teams to demonstrate their effectiveness and root out money mule activities.”


  • Francis is a journalist and our lead LatAm correspondent, with a BA in Classical Civilization, he has a specialist interest in North and South America.

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