Money laundering is a type of financial crime. It involves taking criminally obtained proceeds (dirty money) and disguising their origins so they’ll appear to be from a legitimate source. Anti-money laundering (AML) refers to the activities financial institutions perform to achieve compliance with legal requirements to actively monitor for and report suspicious activities.
History of Anti-Money Laundering
The United States was one of the first nations to enact anti-money laundering legislation when it established the Bank Secrecy Act (BSA) in 1970. An early effort to detect and prevent money laundering, the BSA has since been amended and strengthened by additional anti-money laundering laws. The Financial Crimes Enforcement Network is now the designated administrator of the BSA – with a mission to "safeguard the financial system from the abuses of financial crime, including terrorist financing, money laundering and other illicit activity."
In 1989, multiple countries and organizations formed the global Financial Action Task Force (FATF). Its mission is to devise and promote international standards to prevent money laundering. Shortly after the 9/11 attacks on the US, FATF expanded its mandate to include AML and combatting terrorist financing. The International Monetary Fund (IMF) is another important organization. With 189 member countries, its primary purpose is to ensure stability of the international monetary system. The IMF is concerned about the consequences money laundering and related crimes can have on the integrity and stability of the financial sector and the broader economy.
Why Is Anti-Money Laundering Important?
The estimated amount of money laundered globally in one year is 2% to 5% of global GDP, or US$800 billion to US$2 trillion – and that’s a low estimate. Money laundering often accompanies activities like smuggling, illegal arms sales, embezzlement, insider trading, bribery and computer fraud schemes. It’s also common with organized crime including human, arms or drug trafficking, and prostitution rings.
Anti-money laundering is closely related to counter-financing of terrorism (CFT), which financial institutions use to combat terrorist financing. AML regulations combine money laundering (source of funds) with terrorism financing (destination of funds).
Beyond the moral imperative to fight money laundering and terrorist financing, financial institutions also use AML tactics for:
- Compliance with regulations that require them to monitor customers and transactions and report suspicious activity.
- Protection of their brand reputation and shareholder value.
- Avoidance of consent orders as well as civil and criminal penalties that could be levied because of noncompliance or negligence.
- Reduction of costs related to fines, employee and IT costs, and capital reserved for risk exposure.
Analytics Powers Anti-Money Laundering Efforts
Before turning to SAS, Landsbankinn had a screening system that flagged about 1,000 false positive transactions each day. With a limited number of investigators, lowering that number to focus on truly suspicious claims was important. Just months after turning to SAS Anti-Money Laundering, the number was down to about 100 daily – a 90% reduction in false positives.
Anti-Money Laundering in Today’s World
Money laundering exacts substantial costs to individuals and institutions and can have devastating consequences for society. Learn how artificial intelligence techniques like machine learning are helping redefine AML and compliance for some of the world's top global banking organizations.
Analyst viewpoint
SAS is a Leader in The Forrester Wave™: Anti-Money Laundering Solutions, Q3 2019.
AI and machine learning are helping to redefine anti-money laundering.
Learn more in the full report.
Next-gen anti-money laundering
Ready to advance AML to the next level? Using robotics, semantic analysis and AI can make processes more automated, efficient and effective. Read about 10 keys to success with AML powered by machine learning.
AI and machine learning redefine AML
From transaction monitoring and anomaly detection to customer risk ranking, social network analysis and more, machine learning is drastically changing the ways financial institutions fight back against money laundering.
5 game changers to fight money laundering
To move to the next level of anti-money laundering, you need a tightly focused strategy supported by sophisticated analytics. Learn how SAS can change your AML game plan in the evolving battle against money laundering.
AML/CFT controls, when effectively implemented, mitigate the adverse effects of criminal economic activity and promote integrity and stability in financial markets. International Monetary Fund
Fortify your fight against money laundering
Chief compliance officers at financial institutions face three major challenges in complying with anti-money laundering regulations: A growing volume of cross-border transactions, high false positives, and constantly changing AML regulations and business requirements. See how SAS Anti-Money Laundering can help you achieve compliance – by significantly reducing false positives, boosting operational efficiency and quickly uncovering unknown threats while showing a holistic view of risk.
How Anti-Money Laundering Works
To identify and report potential money laundering and address compliance requirements, financial institutions must have a deep understanding of how the crime works. Money laundering involves three stages: placement, layering and integration. These are a complex series of transactions that start with depositing funds, then gradually moving them into what appear to be legitimate assets.
- Placement refers to how and where illegally obtained funds are placed. Money is often placed via: Payments to cash-based businesses; payments for false invoices; “smurfing,” which means putting small amounts of money (below the AML threshold) into bank accounts or credit cards; moving money into trusts and offshore companies that hide beneficial owners’ identities; using foreign bank accounts; and aborting transactions shortly after funds are lodged with a lawyer or accountant.
- Layering refers to separating criminal funds from their source. It involves converting the illicit proceeds into another form and creating complex layers of financial transactions to disguise the funds' origin and ownership. Criminals do this to obfuscate the trail of their illicit funds so it will be hard for AML investigators to trace the transactions.
- Integration refers to re-entry of the laundered funds into the economy in what appears to be normal, legitimate business or personal transactions. This is sometimes done by investing in real estate or luxury assets. It gives launderers and criminals an opportunity to increase their wealth.
Regulations/Compliance and AML
The FATF helps countries create a financial intelligence unit (FIU) that’s responsible for managing the flow of information between their institutions and law enforcement agencies. Government legislation and regulation by each country’s FIU make financial institutions the first line of defense against money laundering and terrorist financing.
By reporting suspicious activities to the government via suspicious transaction reports (STRs) and suspicious activity reports (SARs), banks alert law enforcement to possible criminal activities. Many regulatory bodies have enacted critical AML legislation with compliance requirements banks follow to enforce anti-money laundering, such as:
- US: US Patriot Act, Bank Secrecy Act.
- Europe: EU Fourth Anti-Money Laundering Directive (4AMLD).
- Canada: Proceeds of Crime (Money Laundering) and Terrorist Financing Act (PCMLTFA).
- Australia: Anti-Money Laundering and Counter-Terrorism Financing Act of 2006.
AML regulations vary by jurisdiction – but in general, financial institutions undertake the following measures to meet compliance requirements:
- Customer identification program/know your customer (KYC). Financial institutions must require proper customer identification and verification to ensure legitimacy. Higher risk products and services (e.g., private banking) require more in-depth documentation.
- Large currency transaction reporting. Requirements call for institutions to file a regulatory report (known as a “CTR” in the US) for transactions above a certain threshold made by a single customer during a business day.
- Suspicious activities monitoring and reporting. Regulatory agencies publish AML guidelines about behavior that should be monitored (e.g., making numerous cash deposits or withdrawals over several days to avoid a reporting threshold). If an AML investigator uncovers behavior that exceeds reporting thresholds and has no apparent business purpose, they file a SAR/STR with the FIU to fulfill regulatory requirements.
- Sanctions compliance. Regulatory bodies such as the US Treasury Department, US Office of Foreign Assets Control, the United Nations, the European Union, Her Majesty’s Treasury and the Financial Action Task Force on Money Laundering have requirements for financial institutions to check transaction parties against lists of sanctioned individuals, companies, institutions and countries.
Technology and anti-money laundering
A successful anti-money laundering program involves using data and analytics to detect unusual activities. This is done by monitoring transactions, customers and entire networks of behaviors.
As artificial intelligence technologies like machine learning become more prevalent, these next-gen AML technologies will automate many manual processes – helping to effectively identify financial crimes risks.
SAS financial crimes solutions include embedded machine learning and other advanced analytics techniques to drastically bolster anti-money laundering efforts. Techniques include deep learning, neural networks, natural language generation and processing, unsupervised learning and clustering, robotic process automation and more.
These techniques can be used for:
- Suspicious activity monitoring – to uncover new schemes and detect increasingly sophisticated financial crimes tactics.
- Intelligent alert prioritization – to triage alerts that warrant investigation and hibernate low-value alerts.
- Alert/case enrichment –to show AML investigators relevant images, prior cases, SARs, third-party data, maps, transaction history and more.
- Automated SAR filings via natural language generation and processing – to transform data into language and stories.
- A holistic entity view built from network analytics – to help you visualize and explore relationships in data.
- Alert scoring with Bayesian algorithms – to relatively score all subjects of AML investigations.
- Client risk rating – for empirical scoring of money laundering risk exposure.
- Intelligent customer segmentation that builds smart peer groupings – to improve coverage across customers and/or accounts.
- Peer-based anomaly detection – to identify abnormal behavior for a subject relative to peers.
- Rare-event detection – to identify those similar to a subject of interest (such as a law enforcement inquiry).
- Automated manual processes across the trade transaction life cycle – to detect patterns of illicit trade finance activity through optical character recognition.
4 types of money laundering
Trade-based money laundering
Moving criminal funds through trade transactions (import/export of goods) to disguise their origins is known as trade-based money laundering (TBML). Some criminals carry out TBML by over- or under-invoicing for shipments. Other methods involve multiple invoicing (for the same shipment), misrepresenting the quality of the shipped goods, or shipping more – or fewer – goods than agreed.
Crypto/virtual currency and money laundering
Crypto and virtual currencies have opened the door to new methods of laundering funds. For example, bitcoin ATMs can have “holes” with their AML compliance methods. And the degree of regulatory compliance by online cryptocurrency trading markets (exchanges) varies. Criminals use other methods too, such as “tumblers.” Tumblers are mixing services that split up dirty cryptocurrency, sending it through a series of different addresses and eventually recombining it into clean funds – for a hefty fee.
Drug trafficking and money laundering
The illicit drug trade funds large, powerful and often violent criminal organizations. Drug traffickers must launder money to hide its origins, hide their identity, and prevent confiscation. Illegal drug transactions are sometimes done through avenues like dark web marketplaces. Some of the tactics drug traffickers use involve bulk cash smuggling, structured deposits, and money service businesses and currency exchanges.
Terrorist financing
Terrorists financing their acts raise money and clean it through various methods. They hide the funds by preying on weaknesses in the financial system. Spotting these funds is challenging, unless a known terrorist or organization opens an account. Banks that spot an unusual or suspicious transaction are advised to file a report with the financial intelligence unit, which then undertakes a money laundering investigation.
SAS® Anti-Money Laundering
In a world of evolving risks, it’s hard to keep pace as you manage alerts, test scenarios and work to maintain compliance with AML regulations. SAS Anti-Money Laundering is a proven platform that improves detection accuracy and can lower total cost of ownership. It provides transaction monitoring, customer due diligence, real-time sanctions and watchlist screening, and regulatory reporting – enhanced by advanced analytics capabilities like machine learning and robotic process automation.
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