Anti-Money Laundering (AML)
What is AML?
Description
Fraudio's Anti-Money Laundering (AML) product detects sequences of transactions that are linked to potential money laundering by analysing certain patterns. Machine learning techniques are utilised to convert combinations of these patterns into alerts for suspicious activity.
We work with our customers to understand their AML requirements. This includes finding out where they are licensed and who their regulator is. This is important because the regulators have explicit reporting indicators that must be taken into account, as well as guidance on subjective reporting indicators. The regulator often has specific local requirements that detail what information must be included in a Suspicious Activity Report (SAR), along with a dedicated portal for submitting such information.
Objective and Subjective Reporting
Objective reporting covers the requirement for regulated financial institutions to report when transactions they process are above specific thresholds as set by the regulator. Below is an example of objective reporting indicators in the Netherlands, and how the regulator defines subjective reporting.
Objective indicators
- A transaction for a sum of €10,000 or more that involves the exchanging of cash into other currencies or from small to large denominations of banknotes.
- A cash deposit for a sum of €10,000 or more in favour of a credit card or a prepaid instrument of payment (prepaid card).
- The use of a credit card or a prepaid instrument of payment (prepaid card) in connection with a transaction for the sum of €15,000 or more.
- A money transfer for a sum of €2,000 or more, unless it is a money transfer by an entity that leaves the processing of the money transfer in question to another entity that is also subject to the obligation to report, as stipulated in Section 16, subsection 1 of the Wwft Act.
Please notify us of any objective reporting requirements that need to be included for transaction monitoring purposes.
Subjective indicators
- A transaction for which the entity has reason to believe that it might be related to money laundering or terrorism financing.
Source: Banks | FIU-Nederland
There are many patterns that Fraudio’s machine learning algorithms look for to determine if there is suspicious activity in a customers transaction processing that can relate to money laundering.
Suspicious Activity Reports
Regulators require information regarding suspicious transactions to be delivered to them in a Suspicious Activity Report (SAR). As mentioned, some regulators have portals where the regulated entity is given login credentials and must upload the information directly. Other times the SARs can be filled out and sent to the regulator.
In general the regulator is looking for information on the individual or entity who is under suspicion, the details of the transaction(s), who the counterparty to the transaction(s), and the reason why the suspicion has been triggered.