S. Lyeonov, Joanna Żurakowska-Sawa, O. Kuzmenko, V. Koibichuk
{"title":"引力和智能数据分析,以评估金融机构的洗钱风险","authors":"S. Lyeonov, Joanna Żurakowska-Sawa, O. Kuzmenko, V. Koibichuk","doi":"10.14254/2071-8330.2020/13-4/18","DOIUrl":null,"url":null,"abstract":"The wide variety of schemes to use companies for money laundering, such as oil smuggling, illegal gas sales, misappropriation of the Central Bank refinancing, misappropriation of bank funds and state-owned enterprises, form the research issues. The sample under study includes 102 countries around the world, which are closely monitored by the Financial Action Task Force (FATF) and have different levels of sociopolitical and economic development. The scientific and methodological approach to assess the financial monitoring risk in terms of the use of financial institutions for money laundering is based on the methods of multidimensional static analysis, descriptive, cluster and dispersive data analysis, gravity theory, nonlinear econometric modeling, differential and bifurcation analysis of dynamic nonlinear systems. The result of the study is a developed model of comprehensive risk assessment for the countries’ financial institutions for money laundering, which considers grouping of countries by the Received: February, 2020 1st Revision: October, 2020 Accepted: December, 2020 DOI: 10.14254/20718330.2020/13-4/18 Journal of International Studies S ci en ti fi c P a pe rs © Foundation of International Studies, 2020 © CSR, 2020 Journal of International Studies Vol.13, No.4, 2020 260 level of money laundering risk, identification of the cluster belonging to the state; formation of an integrated index as a money laundering risk rating assessment, and risk assessment based on the gravitational model; construction of a phase portrait for a dynamic system of the risk to use the countries’ financial institutions based on a nonlinear econometric model.","PeriodicalId":330787,"journal":{"name":"The Journal of international studies","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Gravitational and intellectual data analysis to assess the money laundering risk of financial institutions\",\"authors\":\"S. Lyeonov, Joanna Żurakowska-Sawa, O. Kuzmenko, V. Koibichuk\",\"doi\":\"10.14254/2071-8330.2020/13-4/18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The wide variety of schemes to use companies for money laundering, such as oil smuggling, illegal gas sales, misappropriation of the Central Bank refinancing, misappropriation of bank funds and state-owned enterprises, form the research issues. The sample under study includes 102 countries around the world, which are closely monitored by the Financial Action Task Force (FATF) and have different levels of sociopolitical and economic development. The scientific and methodological approach to assess the financial monitoring risk in terms of the use of financial institutions for money laundering is based on the methods of multidimensional static analysis, descriptive, cluster and dispersive data analysis, gravity theory, nonlinear econometric modeling, differential and bifurcation analysis of dynamic nonlinear systems. 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引用次数: 15
Gravitational and intellectual data analysis to assess the money laundering risk of financial institutions
The wide variety of schemes to use companies for money laundering, such as oil smuggling, illegal gas sales, misappropriation of the Central Bank refinancing, misappropriation of bank funds and state-owned enterprises, form the research issues. The sample under study includes 102 countries around the world, which are closely monitored by the Financial Action Task Force (FATF) and have different levels of sociopolitical and economic development. The scientific and methodological approach to assess the financial monitoring risk in terms of the use of financial institutions for money laundering is based on the methods of multidimensional static analysis, descriptive, cluster and dispersive data analysis, gravity theory, nonlinear econometric modeling, differential and bifurcation analysis of dynamic nonlinear systems. The result of the study is a developed model of comprehensive risk assessment for the countries’ financial institutions for money laundering, which considers grouping of countries by the Received: February, 2020 1st Revision: October, 2020 Accepted: December, 2020 DOI: 10.14254/20718330.2020/13-4/18 Journal of International Studies S ci en ti fi c P a pe rs © Foundation of International Studies, 2020 © CSR, 2020 Journal of International Studies Vol.13, No.4, 2020 260 level of money laundering risk, identification of the cluster belonging to the state; formation of an integrated index as a money laundering risk rating assessment, and risk assessment based on the gravitational model; construction of a phase portrait for a dynamic system of the risk to use the countries’ financial institutions based on a nonlinear econometric model.