AML/CFT Transaction Monitoring – introduction to the basic concept

AML/CFT transaction monitoring is equally if not more challenging than Risk-based Approach towards KYC procedures. Of course all depends on the business context, volume of clients, volume of transactions, technology available to support the business processes and controls embedded in them, and so on, and so far. In this blog entry I am going to elaborate a bit on transaction monitoring.

The principle aim of transaction monitoring in the context of AML/CFT is to detect any suspicious activities that lead to the conclusion that the means being subject of the transactions are the proceeds of any crime. We may say so, as current definitions of money laundering across the World cover almost any predicate offence. In sone jurisdictions it is easier to list predicate offences that are not in scope of money laundering than otherwise.

Said so, lets look into the concept of AML/CFT transaction monitoring. In order to be able to detect a suspicion we need to observe an unusual behavior of the party ordering the transaction, unusual or sanctioned destination of the transfer of value or something unusual about the transaction itself.

This initial consideration leads to the trio of layers we need to consider when designing a transaction monitoring program aimed at detection of suspicious transactions:

a) unusual behaviour of the client (change or inconsistency)

b) unusual transaction profile / features

c) transfers coming from or going to unusual or higher risk destinations (unexpected by KYC outcome or unusual change observed)

The information about the client himself, its ownership structure, legal form, place of incorporation, places of doing business, beneficial ownership, source of wealth, source of funds or characteristics of business or personal transaction profile comes from the KYC procedures we have been considering in our preceding entry of this blog.

Destination of the transfer of value that should alert us are those inconsistent with the client KYC profile or are forbidden by law, e.g. restrictions enforced by the OFAC, the US State Treasury, the UN, the EU or the UK.

Lastly, the unusual transaction features, are a result of comparing the expected by the KYC profile of the client transaction patterns with actuals, e.g. excessive volume of payments, unexpected value of transfers, rapid change of volume or value.

All of the above are easy if we have a handful of transactions to monitor, sufficient number of capable hands to take care of the process and sufficient time to inspect every payment before we process it or otherwise facilitate for the client. If the numbers go up, we need to consider sufficient technologies to support us in flagging transactions for review and where possible also to support the decision making process. These features are often supported by automation, robotics and narrow AI.

Thank you for bearing with me 🙂

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