Development of a model for predicting money laundering rate
The article suggests model for predicting the level of money laundering on the basis of data from the Ministry of Internal Affairs of the Russian Federation on the state of economic crime in Russia since the beginning of 2011. Using a seasonally integrated autoregressive moving average (SARIMA) mode...
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| Format: | Article |
| Language: | English |
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Publishing House of the State University of Management
2022-07-01
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| Series: | Вестник университета |
| Subjects: | |
| Online Access: | https://vestnik.guu.ru/jour/article/view/3574 |
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| author | E. S. Anisimov J. M. Beketnova |
| author_facet | E. S. Anisimov J. M. Beketnova |
| author_sort | E. S. Anisimov |
| collection | DOAJ |
| description | The article suggests model for predicting the level of money laundering on the basis of data from the Ministry of Internal Affairs of the Russian Federation on the state of economic crime in Russia since the beginning of 2011. Using a seasonally integrated autoregressive moving average (SARIMA) model, it compares different regression models for the research tasks (linear regression, logistic regression, autoregressive and SARIMA). The necessity of taking into account seasonal regularities in the structure of money laundering was underlined, and the SARIMA model with the lowest deviations from the actual values was chosen. The necessity of taking into account seasonal regularities in the structure of money laundering was underlined, and the SARIMA model with the lowest deviations from the actual values was chosen. The article presents the results of data analysis using the method of least squares, calculating the mean squared error (MSE). High accuracy of short-term forecasts was noted: the deviation from the actual number of cases is about three cases (with the average number of cases being 68 over the last 10 years). The forecasting model can be recommended for implementation in the analytical complexes of financial monitoring and supervisory authorities. |
| format | Article |
| id | doaj-art-6e38fdba1c1e4ce2926e3133c3772a03 |
| institution | Kabale University |
| issn | 1816-4277 2686-8415 |
| language | English |
| publishDate | 2022-07-01 |
| publisher | Publishing House of the State University of Management |
| record_format | Article |
| series | Вестник университета |
| spelling | doaj-art-6e38fdba1c1e4ce2926e3133c3772a032025-02-04T08:28:12ZengPublishing House of the State University of ManagementВестник университета1816-42772686-84152022-07-010513614310.26425/1816-4277-2022-5-136-1432469Development of a model for predicting money laundering rateE. S. Anisimov0J. M. Beketnova1Financial UniversityFinancial UniversityThe article suggests model for predicting the level of money laundering on the basis of data from the Ministry of Internal Affairs of the Russian Federation on the state of economic crime in Russia since the beginning of 2011. Using a seasonally integrated autoregressive moving average (SARIMA) model, it compares different regression models for the research tasks (linear regression, logistic regression, autoregressive and SARIMA). The necessity of taking into account seasonal regularities in the structure of money laundering was underlined, and the SARIMA model with the lowest deviations from the actual values was chosen. The necessity of taking into account seasonal regularities in the structure of money laundering was underlined, and the SARIMA model with the lowest deviations from the actual values was chosen. The article presents the results of data analysis using the method of least squares, calculating the mean squared error (MSE). High accuracy of short-term forecasts was noted: the deviation from the actual number of cases is about three cases (with the average number of cases being 68 over the last 10 years). The forecasting model can be recommended for implementation in the analytical complexes of financial monitoring and supervisory authorities.https://vestnik.guu.ru/jour/article/view/3574financial monitoringanti-money launderingeconomic crimecrime forecastingstatistical analysis |
| spellingShingle | E. S. Anisimov J. M. Beketnova Development of a model for predicting money laundering rate Вестник университета financial monitoring anti-money laundering economic crime crime forecasting statistical analysis |
| title | Development of a model for predicting money laundering rate |
| title_full | Development of a model for predicting money laundering rate |
| title_fullStr | Development of a model for predicting money laundering rate |
| title_full_unstemmed | Development of a model for predicting money laundering rate |
| title_short | Development of a model for predicting money laundering rate |
| title_sort | development of a model for predicting money laundering rate |
| topic | financial monitoring anti-money laundering economic crime crime forecasting statistical analysis |
| url | https://vestnik.guu.ru/jour/article/view/3574 |
| work_keys_str_mv | AT esanisimov developmentofamodelforpredictingmoneylaunderingrate AT jmbeketnova developmentofamodelforpredictingmoneylaunderingrate |