Money laundering rate modelling

The article continues the analysis of the work of the model developed by the authors of forecasting money laundering rate. The purpose of the study is to compare the results of the forecast with the actual data. Authors used official data by the Ministry of Internal Affairs of the Russian Federation...

Full description

Saved in:
Bibliographic Details
Main Authors: J. M. Beketnova, E. S. Anisimov
Format: Article
Language:English
Published: Publishing House of the State University of Management 2023-05-01
Series:Вестник университета
Subjects:
Online Access:https://vestnik.guu.ru/jour/article/view/4400
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832541563676262400
author J. M. Beketnova
E. S. Anisimov
author_facet J. M. Beketnova
E. S. Anisimov
author_sort J. M. Beketnova
collection DOAJ
description The article continues the analysis of the work of the model developed by the authors of forecasting money laundering rate. The purpose of the study is to compare the results of the forecast with the actual data. Authors used official data by the Ministry of Internal Affairs of the Russian Federation on economic crime rate for the period January 2011 – July 2022. In the last published work, a forecast was formed based on the seasonal integrated autoregression – moving average (SARIMA) model for 11 months of 2022 from February to December. This forecast for the past 6 months has been verified by comparison with the actual values by calculating the relative error and the RMSE (root mean square error). In comparison, the authors noted a rare distribution of registered cases for the last decade: an excess of the number of crimes in May over June. The result of the study may be used as an auxiliary tool in the analytical complexes of subjects of financial monitoring and supervisory authorities. The results reflected the high accuracy of the forecasts obtained for the sum of the periods, and the conclusion was also made about the importance of observing the seasonal structure of the dynamics of crimes for operational changes in the parameters of the model.
format Article
id doaj-art-953eedbe214044e3a879c8abc9f6a769
institution Kabale University
issn 1816-4277
2686-8415
language English
publishDate 2023-05-01
publisher Publishing House of the State University of Management
record_format Article
series Вестник университета
spelling doaj-art-953eedbe214044e3a879c8abc9f6a7692025-02-04T08:28:15ZengPublishing House of the State University of ManagementВестник университета1816-42772686-84152023-05-010315315910.26425/1816-4277-2023-3-153-1592742Money laundering rate modellingJ. M. Beketnova0E. S. Anisimov1Financial University under the Government of the Russian FederationFinancial University under the Government of the Russian FederationThe article continues the analysis of the work of the model developed by the authors of forecasting money laundering rate. The purpose of the study is to compare the results of the forecast with the actual data. Authors used official data by the Ministry of Internal Affairs of the Russian Federation on economic crime rate for the period January 2011 – July 2022. In the last published work, a forecast was formed based on the seasonal integrated autoregression – moving average (SARIMA) model for 11 months of 2022 from February to December. This forecast for the past 6 months has been verified by comparison with the actual values by calculating the relative error and the RMSE (root mean square error). In comparison, the authors noted a rare distribution of registered cases for the last decade: an excess of the number of crimes in May over June. The result of the study may be used as an auxiliary tool in the analytical complexes of subjects of financial monitoring and supervisory authorities. The results reflected the high accuracy of the forecasts obtained for the sum of the periods, and the conclusion was also made about the importance of observing the seasonal structure of the dynamics of crimes for operational changes in the parameters of the model.https://vestnik.guu.ru/jour/article/view/4400financial monitoringanti-money launderingeconomic crimescrime forecastingstatistical analysis
spellingShingle J. M. Beketnova
E. S. Anisimov
Money laundering rate modelling
Вестник университета
financial monitoring
anti-money laundering
economic crimes
crime forecasting
statistical analysis
title Money laundering rate modelling
title_full Money laundering rate modelling
title_fullStr Money laundering rate modelling
title_full_unstemmed Money laundering rate modelling
title_short Money laundering rate modelling
title_sort money laundering rate modelling
topic financial monitoring
anti-money laundering
economic crimes
crime forecasting
statistical analysis
url https://vestnik.guu.ru/jour/article/view/4400
work_keys_str_mv AT jmbeketnova moneylaunderingratemodelling
AT esanisimov moneylaunderingratemodelling