Big Data Analytics for Financial Crime Typologies

Abstract

The paper proposes a technique to automate the generation of new criminal cases for money laundering from crime and financing terrorism (ML/FT), which are based on ML/FT typologies. At the same time, the paper is focused not on the existing methods, but offer its own implemented on the basis of creating various versions of case typologies and further filtering them by the derived criteria. For this purpose, it is supposed to use Big Data tools. The successful application of the developed technique is shown on examples of the commission and VAT carousel schemes. To implement and verify this technique a program was written that successfully passed the test on case graphs built on ML/FT typologies.