Nashchekina, O. N.Sergienko, OlenaSosnov, IgorTatar, MarynaShapran, Evgeniy2020-11-182020-11-182020Model Tools of Credit Risks Assessment of Agricultural Enterprises in International Trade [Electronic resource] / O. Nashchekina [et al.] // CEUR Workshop Proceedings. – 2020. – Vol. 2649. – Machine Learning Methods and Models, Predictive Analytics and Applications : proc. of the Workshop on the 12th Intern. Sci. Practical Conf. Modern problems of social and economic systems modelling (MPSESM-W 2020), Kharkiv, Ukraine, June 25, 2020. – Electronic text data. – Germany, 2020. – P. 34-49. – URL: http://ceur-ws.org/Vol-2649/paper4.pdf, free (accessed 18.11.2020).https://repository.kpi.kharkov.ua/handle/KhPI-Press/49359The paper aim is improving the methodological tools for agricultural enterprise's credit risks assessment and classification as participant of international trade market. The proposed approach differs from the existing approaches by complexity and systematicness, on the bases of usage of multilevel factor system of the borrower's assessment by local and aggregate components. The object of research is set of credit risks affecting crediting processes in agricultural sector of Ukrainian economy. The following economic and mathematical methods of scientific research were used: factor and comparative analysis (to highlight classification specific features of agricultural sector crediting), methodology of integrated rating (for rating of local components of risk), methods of factor analysis (to confirm the hypothesis of grouping of agricultural enterprises credit risks by components), hierarchical and iterative methods of cluster analysis (to distinguish agricultural enterprises classes by risk level). The proposed methodology is tested on a sample set of observations for 14 agricultural enterprises of Ukraine for 2018 year for the selected 38 credit risk indicators. On the bases of economic and mathematical tools for estimating and analyzing the aggregate system of agricultural enterprises credit risk indicators, namely the methodology of factor analysis, the hypothesis regarding the grouping and formation of agricultural enterprises credit risk classes has been improved. Five major systemic groups of external and internal risks which are specific to agrarian enterprises are identified: mortgage risks, system providing risks, system forming risks, natural and climatic risks, production risks. The obtained classes by risk level by the studied components on the basis of cluster analysis methods make possible to determine the set of critical and safe states in general and by local components and to choose effective behavior trajectory for agricultural enterprise creditworthiness increasing. The assessment results using proposed methodology laid in the bases of scenarios development of agricultural sector lending, make possible to develop a set of measures for strategic and tactical management of agricultural enterprise's creditworthiness and adjust their behavior in international markets.enagricultural enterprisescredit riskseconomic and mathematical toolsassessmentclassificationindicatorsexternal environmentinternal risksArticlehttps://orcid.org/0000-0003-2578-1109https://orcid.org/0000-0002-9796-9218https://orcid.org/0000-0003-0027-5488https://orcid.org/0000-0002-1111-7103https://orcid.org/0000-0002-9236-0905