Delator: Automatic Detection of Money Laundering Evidence on Transaction Graphs via Neural Networks
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Money laundering is one of the most relevant criminal activities today, due to its potential to cause massive financial losses to governments, banks, etc. We propose DELATOR, a new CAAT (computer-assisted audit technology) to detect money laundering activities based on neural network models that encode bank transfers as a large-scale temporal graph. In collaboration with a Brazilian bank, we design and apply an evaluation strategy to quantify DELATOR's performance on historic data comprising millions of clients. DELATOR outperforms an off-the-shelf solution from Amazon AWS by 18.9 AUC. We conducted real experiments that led to discovery of 8 new suspicious among 100 analyzed cases, which would have been reported to the authorities under the current criteria.
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