New software detects money laundering faster than ever before

Researchers from Centrum Wiskunde & Informatica (CWI) and King's College London have designed an entirely novel approach to detecting money laundering, based on algorithms which rapidly identify when criminals are dividing a large sum of money into multiple smaller transactions between many bank accounts – a technique known as ‘smurfing’.

 

The algorithms run on data taken from several bank accounts which are represented as nodes on a large, complex graph, and the software is programmed to focus on the part of the graph where it detects the most suspicious activity.

For example, if there is a deposit of one million pounds, the software can monitor where this exact sum of money is being transferred – it has the ability to identify all combinations of related transactions that take place, even if the money is split between different accounts and outgoings.

 

As detailed in a paper published in the Proceedings of the 2023 SIAM International Conference on Data Mining, researchers Dr Solon Pissis (CWI, Networks and Optimization group), Dr Huiping Chen and Dr Grigorios Loukides (King's College, Department of Informatics), together with Dr Robert Gwadera (independent researcher), say the new software is over three times more effective than current detection methods and can also analyse larger amounts of data.

 

Read more on the website of Centrum Wiskunde & Informatica (CWI).