from 01.01.2018 to 01.01.2019
Saint Petersburg University of the Ministry Internal Affairs of Russian Federation (department of economic security and management of socio-economic processes, professor of the department)
from 01.01.2020 until now
Russian Federation
The article describes the author’s methodology for identifying tax evading organizations. The methodology is based on the analysis of financial and non-financial factors of companies’ activities using the “Random Forest” machine learning method. The results of the study can be used by law enforcement and tax authorities as a tool to counteract tax evasion.
taxes, detection methods, tax evasion, Random Forest, machine learning
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