• Oleg Patlasov K.G. Razumovski Moscow State University of technologies and management
  • Olga Mzhelskaya Omsk Humanitarian Academy


The paper presents the authors’ estimations according to the scoring modeling techniques; also, internationally spread models of bankruptcy forecasting are systematized. Advantages and disadvantages of dynamic modelling methods as applied to financial condition assessment are presented here. Methodological problems of financial modelling are explained here in detail. Regression, logit-regression and discriminant models are built on the basis of data on the Rosselkhozbank and Sberbank of Russia regulations, taking into account the agrarian specifics of organizations and regional specificity of the Omsk region. An attempt has been made to balance the simplicity of calculations and the accuracy of predictions. Graphs, to be used for express analysis, are constructed on the basis of two core financial indicators.

Author Biographies

Oleg Patlasov, K.G. Razumovski Moscow State University of technologies and management

Doctor of economy, professor,

Сhief- specialist of the Federal State Budget Educational Institution of Higher Education K.G. Razumovski Moscow State University of technologies and management; Omsk Humanitarian Academy

Research interests: Risk Management, Economic Analysis and Financial Management,  Personnel Marketing

Olga Mzhelskaya, Omsk Humanitarian Academy

head of the Humanities and Foreign Language department at Omsk Humanitarian Academy, Russia. She is PhD in Philological Sciencies.

Research interests: linguistics and humanitarian research of communication processes, sociology and management in education, business consulting. She has published 60 scientific papers, 2 monographs and 12 text books and manuals. Twice she has been a laureate of All Russia Best scientific book contest organized by Russian Fond of Education Development.


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How to Cite
Patlasov, O., & Mzhelskaya, O. (2020). FINANCES OF RUSSIA AGRARIAN COMPANIES: SCORING MODELING FOR ESTIMATING. The EUrASEANs: Journal on Global Socio-Economic Dynamics, (3(22), 21-30.