The application of social network analysis algorithms in a system supporting money laundering detection

Criminal analysis is a very complex task requiring to process huge amounts of data coming from different sources such as billings and bank account transactions in order to gain knowledge useful for an investigator. In order to support human analytic capabilities, dedicated software tools are needed, and therefore Money Laundering Detection System (MLDS) was proposed as one of such tools in our previous paper. In this paper, the social network analysis component for this system is presented. The component makes it possible to use data from bank statements and the National Court Register and construct and analyze social networks during an investigation into money laundering cases. The system can assign roles to persons from the network and allows for analysis of connections between them. The paper also includes results of experiments aimed at investigating the performance of the implemented algorithms and the correctness of the analysis.