Investigation of money laudering detection by using computational intelligence

Abstract

The large amount of data related to compliance with money laundering requirements and the increasing sophistication of criminal methods are forcing financial companies to look for new tools to help them meet their regulatory obligations. To achieve this goal, technologies whose operation is based on artificial intelligence become inseparable from the prevention of money laundering. This article makes the case for the true cost of money laundering to the global economy. To achieve this, different technologies used in identifying financial fraud were compared. Special attention in this article is given to a subset of artificial intelligence – digital intelligence methods. According to the latest scientific research, these methods are based on soft computing, which allow to adapt to many situations, predict future events, create appropriate rules, and make targeted decisions. Also, the importance of artificial intelligence in the prevention of money laundering is emphasized by the US study analyzed in the article, in which top-level managers responsible for the field of money laundering prevention were interviewed. The respondents expressed a unanimous opinion that the further application of artificial intelligence in the field of money laundering prevention is a priority.