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ИД «Финансы и кредит»






Economic Analysis: Theory and Practice

An approach to neural network analysis of text information in the economic assessment of companies

Vol. 20, Iss. 8, AUGUST 2021

Received: 27 May 2021

Received in revised form: 8 June 2021

Accepted: 22 June 2021

Available online: 30 August 2021


JEL Classification: C53, G3

Pages: 1574–1594


Aleksandr R. NEVREDINOV Bauman Moscow State Technical University (Bauman MSTU), Moscow, Russian Federation

ORCID id: not available

Subject. When evaluating enterprises, maximum accuracy and comprehensiveness of analysis are important, although the use of various indicators of organization’s financial condition and external factors provide a sufficiently high accuracy of forecasting. Many researchers are increasingly focusing on the natural language processing to analyze various text sources. This subject is extremely relevant against the needs of companies to quickly and extensively analyze their activities.
Objectives. The study aims at exploring the natural language processing methods and sources of textual information about companies that can be used in the analysis, and developing an approach to the analysis of textual information.
Methods. The study draws on methods of analysis and synthesis, systematization, formalization, comparative analysis, theoretical and methodological provisions contained in domestic and foreign scientific works on text analysis, including for purposes of company evaluation.
Results. I offer and test an approach to using non-numeric indicators for company analysis. The paper presents a unique model, which is created on the basis of existing developments that have shown their effectiveness. I also substantiate the use of this approach to analyze a company’s condition and to include the analysis results in models for overall assessment of the state of companies.
Conclusions. The findings improve scientific and practical understanding of techniques for the analysis of companies, the ways of applying text analysis, using machine learning. They can be used to support management decision-making to automate the analysis of their own and other companies in the market, with which they interact.

Keywords: bankruptcy prediction, machine learning, enterprise analysis, artificial neural networks, natural language processing


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Vol. 20, Iss. 8
August 2021