RISK OF LEGALIZATION OF FUNDS BY BANK CLIENTS FROM GAMBLING CONDUCTED ON THE INTERNET: APPROACHES TO MEASUREMENT

Abstract

Today's fraudsters try to use modern financial services and products provided by banking institutions to legalize criminal proceeds and finance terrorism. Moreover, money laundering through banks using operations related to gambling occupies a significant place and has already turned into a serious financial problem. Currently, Internet gambling is a multi-billion dollar, extensive, widely used industry; specific economic activity, which includes illegal ways of exchanging virtual assets for real money, which causes an imbalance in economic processes. The most acute problems with money laundering arise in the direction of activity on the Internet, and especially through gambling, games and sports totalizers. The purpose of this study is to identify money laundering schemes by bank clients through participation in game and sports totalizers, as well as to determine approaches to assessment, modeling aspects of the risk of legalization of funds from online gambling. Theoretical research methods, such as: abstraction, synthesis, grouping, were used to conduct research and obtain results. and empirical methods, namely: observation and description. In the course of the study, the existing schemes of money laundering through participation in Internet gaming and sports totalizers were highlighted. They point out that the existing regulatory measures regarding online gambling are mainly based on a passive policy of dealing with already received negative consequences. Global approaches to modeling, evaluation, and forecasting of certain aspects of gambling have been identified, which partially help in identifying and assessing the risk of laundering illegal funds: longitudinal modeling; a model for assessing the effectiveness of gaming companies in preventing fraud and money laundering, including on the Internet; a model of national and supranational risk assessment of the financial and non-financial sectors from the point of view of the threat of money laundering; a quantile regression model of in-game bets on a large online gambling data set to detect money laundering; a model for predicting the behavior of Internet players with the establishment of restrictions using machine learning algorithms using account data to identify the risk of legalization of illegal funds. A clear understanding of the types, ways, schemes of threats that can contribute to the laundering of illegal funds, as a result, will provide a practical opportunity for financial institutions to form automatic notifications about suspicious financial transactions, predict and control potential risks, for more efficient organization of their functioning and conducting financial transactions. The results of the conducted research will help, among other things, the state regulatory bodies to make certain changes to the existing state policy of combating the laundering of criminal funds and the financing of terrorism.