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№ 2019/3

Forecasting methods and models

DEBUNOV Leonid Mykolajovych1

1Oles Honchar Dnipro National University

Modeling company's financial sustainability with the use of artificial neural networks

Economy and forecasting 2019; 3:76-93https://doi.org/10.15407/econforecast2019.03.076


For enterprises in market conditions, not only the sum of profit is important, but also their financial capacity to continue its activity. The ability of a company to counteract the threat of bankruptcy is an essential condition for its long-term functioning and sustainable development. The financial sustainability of an enterprise is a complex characteristic that can't be described by the value of a single simple indicator. In modern conditions, for its diagnosis, a comprehensive analysis using various financial indicators is used. When a human does it, such an assessment may be subjective and depends on the level of the analyst's qualification and competence.
The article proposes the use of artificial neural networks to build an economic and mathematical model of company's financial sustainability, which is designed to remove the human factor, and to increase the speed and accuracy of the companies' bankruptcy threat diagnosis. An example of such a model is presented that is relevant for Ukrainian companies in the current conditions of the period after the economic crisis of 2014-2015. To model financial sustainability, a three-level artificial neural network of direct signal propagation was constructed. As input factors it is proposed to use 17 financial indicators that should give the most complete assessment of the company's financial sustainability. The study shows that prediction of bankruptcy is possible in the time horizon up to 3 years from the date of filing annual financial statements. The constructed model allows not only to accurately classify enterprises as "financially sustainable" and "potential bankrupt" but also opens up opportunities for further researches about the mutual dependence between the values of financial indicators while maintaining a certain level of financial sustainability. The model may be useful for financial institutions, investment funds, audit firms and companies themselves for timely prediction of the company's bankruptcy.

Keywords:financial sustainability, bankruptcy, neural networks, economic and mathematical modeling, classification, bankruptcy diagnostics, financial indicators, limit of financial sustainability, neuro-network modeling, perceptron, neuron, enterprise

JEL: C45

Article in English (pp. 76 - 93) DownloadDownloads :14