Anti-Money Laundering (AML)

Anti-Money Laundering (AML) regulations require businesses to monitor transactions and report suspicious ones to authorities.

Ylem can help you with automating the data streaming for the following critical processes:

• Unusual transaction amounts;

• Unusual series of transactions (e.g., too many cash credits);

• Unusual geographic destination or origin of a payment;

• Known threats or typologies.

Streaming monitoring information about large transaction amounts

Here is an example of the pipeline to monitor large transaction amounts

Query example to detect large transactions

A high volume of transactions within a short time

Possible pipeline

SQL query example to retrieve the number of transactions today grouped by bank account

Message to the responsible team

Too many transactions between the same accounts in X days

Possible pipeline

SQL query to retrieve number of transactions between two accounts

Message to the responsible team

Other AML use cases

The idea is clear. Using the following examples and templates from our library you can set up your own AML monitoring pipelines with SQL queries of any complexity.

Some other examples of what you can monitor with Ylem:

• Users with a high volume of transactions every day

• Transactions from or to suspicious or dangerous locations, which you can define on your own

• Suspicious reference data

• Suspicious bank account owners

• Suspicious and inconsistent activities. For example, a high volume of transactions but following the long breaks

• Unusual amounts per user

• Etc.