Updated 2024-08-14
Published 2024-04-22
In the popular Belgian animated series, the Smurfs collectively perform tasks to achieve a larger goal.
Therefore, smurfing metaphorically represents conducting many small transactions to hide a more significant amount of illicit money that is thus laundered.
Smurfing is a method of integrating smaller illicit funds into the financial system and making them appear legitimate. These funds are later used in money laundering and terrorist financing.
Once the funds have been sufficiently "smuggled" through various banks and/or commercial operations, they can be consolidated for use in the legitimate economy to finance criminal or terrorist activities without being easily traced back to their criminal origins.
Smurfing is not a new practice, but it has taken on new forms with new technologies.
It poses significant challenges for supervised entities and authorities combating money laundering and terrorist financing.
This method exploits the limitations of traditional surveillance systems designed to flag large, suspicious transactions.
To be detected and prevented, smurfing requires more sophisticated and nuanced methods.
Smurfing became a recognised technique in the 1980s and 1990s when financial institutions introduced stricter anti-money laundering rules.
These regulations often included reporting requirements for transactions above a certain threshold to curb large-scale money laundering activities.
Therefore, smurfing responded to these measures, attempting to avoid controls by splitting large transactions into multiple, smaller transactions.
As digital financial services emerged, smurfing evolved beyond traditional cash deposits to include complex schemes, such as digital transfers, financial instrument purchases, and cryptocurrency.
In recent years, regulators and financial institutions have become better at detecting and preventing smurfing through advanced analytics, machine learning, and other technological developments.
However, the challenge remains significant, as criminals often develop new and increasingly sophisticated smurfing methods.
These methods can include using advanced technology, such as AI and blockchain, to hide the origin and destination of funds, making detection even more difficult.
Failing to detect and mitigate smurfing activities can have severe legal and financial consequences for your company, such as hefty fines, loss of reputation, and even criminal charges for the individuals involved.
In addition, money laundering leads to large amounts of money moving outside the legal financial system every year.
Regulators find it increasingly difficult to keep up with the evolution of smurfing behaviour.
Criminals are usually quick to adopt new technologies, making new practices harder to detect.
Some factors that contribute to smurfing behaviour evolving and taking on new forms are the following:
Smurfers use cryptocurrencies due to their anonymity and ease of conducting cross-border transactions.
Digital wallets and decentralised exchanges make it difficult to track these funds.
Smurfers extensively use various digital payment platforms to distribute small amounts of money, complicating the tracking process.
The use of peer-to-peer payment systems is increasing for seemingly harmless transactions, making them difficult to detect.
AI will change many aspects of our society, including money laundering.
The use of automated systems and artificial intelligence to conduct transactions in patterns that mimic legitimate behaviour is increasing, making surveillance more challenging.
In addition, cyber-attacks can facilitate smurfing by gaining access to accounts to carry out small transactions that divert money to illegal networks.
There is an increasing trend to recruit money couriers via social media and job advertising platforms, targeting unsuspecting individuals to transfer and withdraw illicit funds.
In addition, smurfing has become an increasingly organised activity, often involving international networks that use individuals in different jurisdictions to carry out the activity, complicating transaction monitoring.
Money launderers increasingly integrate smurfing operations within small, cash-intensive businesses to mix illicit funds with legitimate proceeds.
A more sophisticated and common form of smurfing involves using commercial transactions to disguise the illicit origin of funds by over- or under-invoicing goods and services.
In addition, many money launderers quickly exploit regulatory differences between jurisdictions and engage in smurfing activities in countries with weaker anti-money laundering enforcement.
Financial institutions and other actors managing funds must adopt a comprehensive approach to detect and combat smurfing effectively.
This approach should include measures such as implementing the latest technology, employee training, and cooperation between companies and authorities.
Machine learning and AI can help you analyse transaction patterns and identify anomalies that may indicate smurfing.
Systems can learn from historical data to improve identification over time.
Big data solutions can process and analyse large amounts of transactional data in real time and detect potentially suspicious activities among common customer transactions.
Your company should implement robust customer due diligence procedures, especially for customers involved in high-risk activities or showing signs of suspicious behaviour.
This includes verifying the source of funds and the purpose of the transactions.
Customers' activities should be monitored continuously, and their risk profiles should be updated based on new transactions and behaviours.
You can use geolocation data to identify unusual transactions for a customer's established patterns to detect smurfing. Some unusual transactions include transactions in high-risk countries or transactions that don't match the customer's profile.
Organisations should also explore using blockchain and distributed database technologies to increase transaction transparency and traceability, making it harder for smugglers to hide their activities.
The key is remaining adaptable and vigilant, as criminals continuously develop their techniques to avoid detection. Fortunately, developing new technologies can help increase detection capabilities and accuracy.
Supervised entities should increase employees' awareness and knowledge through regular training. In addition, cooperation with other actors and supervisors should focus on sharing information and experiences and improving the ability to fight financial crime.
Smurfing is a complex and evolving practice that poses significant challenges for financial institutions and regulators.
The use of new technologies, such as cryptocurrencies and AI, has made smurfing more difficult to detect and prevent. It's crucial for financial companies to continuously innovate and adapt their surveillance methods to keep up with the ever-changing landscape of smurfing behaviour.
Failing to detect and mitigate smurfing activities can lead to severe legal and financial consequences, making it imperative for companies to invest in advanced analytics and machine learning to combat this illicit practice.
Additionally, international cooperation and coordination among regulatory authorities are vital to combat the global nature of smurfing effectively.