Money laundering detection is the process by which financial institutions and other entities identify and prevent the movement of illicit funds.
The process involves:
Monitoring financial transactions for suspicious activities
Implementation of compliance measures such as know your customer (KYC)
Reporting anomalies and money laundering schemes to the appropriate authorities
In an era of globalized financial systems and technological advancement, the methods used by money launderers have become more effective, sophisticated, and widespread. An estimated $2 trillion in dirty money is laundered by banks every year and is linked to various types of criminal activity such as insider trading, bribery, embezzlement, drug trafficking, and terrorism.
The Key Components of Money Laundering Detection
Money laundering detection comprises various policies, procedures, and technologies that work together to monitor and analyze financial transactions. Here is a brief look at the key components.
Transaction Monitoring Programs
For Australian businesses, transaction monitoring programs are a crucial part of compliance with the Anti-Money Laundering and Counter-Terrorism Financing (AML/CTF) Act 2006. The Act requires each business to document how it monitors customer transactions and the processes it follows to identify suspicious transactions.
Monitoring program legislation also requires companies to self-determine their money laundering risk. To do this, they should consider:
The types of customers they have – particularly if some occupy prominent public positions in government or organizations (otherwise known as politically exposed persons or PEPs)
The types of designated services they provide. Services at risk of money laundering include the financial services, gambling, bullion, and digital currency exchange sectors
How the services are provided (for example, face-to-face or online)
The countries they operate (or do business) in
Know Your Customer (KYC) Procedures
KYC procedures help financial institutions verify client identities, understand the nature of their activities, and define appropriate risk levels. This is another part of AML compliance that requires businesses to document their customer identification procedures. Such procedures are based on the type of customer in question and their associated risk level.
Other processes that need to be detailed include:
How the business verifies the identity of consumers and real entities (companies or organizations)
How the business responds to data discrepancies during verification. For example, when the name of an applicant in their passport does not match the name they provided
The risk-based controls and systems to be used if more information needs to be collected before verification
Simplified verification procedures for certain companies, such as domestic Australian companies and majority-owned subsidiaries of Australian companies listed on the ASX
Simplified verification procedures for trusts, such as managed investment schemes and government superannuation funds
Technology
As the prevalence of digital payments continues to increase, so does the diversity and complexity of financial crimes related to these types of transactions. While traditional AML methods were resource-intensive, new technology powered by artificial intelligence (AI) and machine learning (ML) now does most of the heavy lifting.
More payments mean more data to analyze, but happily, ML can now detect patterns in vast datasets and flag potentially suspicious activity for review. Other tools monitor transactions continuously so that threats can be detected before they have the chance to materialize.
Artificial intelligence is well suited to the optimization of routine, rule-based tasks, such as those that are central to customer onboarding processes and enhanced due diligence (EDD). With the rise of cryptocurrency, specialized tools have also been developed to trace transactions on blockchain networks and detect illicit activities related to digital assets.
The Money Laundering Detection Process
While the specifics vary from one bank or jurisdiction to the next, the process of detecting money laundering tends to follow a four-step process.
Step 1 – Detection
AI and ML-powered systems identify suspicious transactions based on predetermined criteria. These invariably relate to:
Unusually large, frequent, or complex transactions
Transactions that utilize shell companies and offshore accounts in known tax havens
Transactions that involve high-risk regions or countries
Transactions that involve sanctioned persons or organizations
Transactions that are split to avoid threshold transaction report (TTR) obligations
Unexpected transaction patterns that appear to serve no legitimate purpose
Transactions that are inconsistent with a customer’s prior behavior or risk profile
Rule-Based Systems
Rule-based systems then alert compliance officers to the presence of potentially fraudulent transactions. In the case of unusually large transactions, any deposit that exceeds $10,000 may be marked for review.
Other rule-based systems send alerts based on:
Pattern detection – a customer may make multiple transactions of $9,900 to stay under the $10,000 threshold and avoid bank submission of a TTR to AUSTRAC
Behavioral analytics – as touched on above, AI and ML compare current transactions to a customer’s baseline behavior and look for anomalies
Geographic monitoring – where transactions that involve high-risk countries are automatically flagged
Step 2 – Review
Alerts are then distributed to compliance analysts or investigators within the bank's AML, financial crime risk management (FCRM), or financial crime compliance (FCC) department. Analysts conduct an initial review to determine if the alert is a false positive or warrants further investigation. They review the customer’s profile, account history, KYC information, and expected transaction patterns.
Step 3 – Investigation
Enhanced due diligence is a core part of a money laundering investigation. As part of EDD, analysts may:
Request additional documentation such as invoices, contracts, or other explanations for the transaction
Verify the legitimacy of the origin of the funds (particularly for large amounts)
Ascertain who owns or controls the account in question (for businesses with complex ownership structures)
In this phase, banks may share information, pool resources, and coordinate actions to obtain more clarity on the type and extent of fraudulent transactions.
Step 4 – Documentation, Auditing, and Reporting
In step four, banks keep detailed records of suspicious transactions, the actions they took, and any interactions with the customer. Documentation may serve as evidence if the case proceeds to court, but it also supports audits (internal or external) that identify areas where future AML procedures could be improved.
Banks also report to (or collaborate with) various bodies such as AUSTRAC, the Australian Federal Police (AFP), or ASIC in cases where money laundering overlaps with securities fraud or market manipulation.
Summary:
Money laundering detection is the process of identifying and preventing the concealment of illegally obtained funds
The key components of money laundering detection are transaction monitoring, KYC procedures, and technology. Each works to help businesses identify potential threats and comply with AML regulations
The money laundering detection process has four key steps. In the detection phase, banks use rule-based systems to flag suspicious transactions. These are then reviewed and investigated, with processes documented and results shared with other banks and regulatory bodies
