Analysis and Forecasting the Solvency of Enterprises Using Statistical and Intellectual Methods of Data Analysis

Student: Sabitova Svetlana

Educational Programme: Business Informatics (Bachelor)

Year of Graduation: 2018

The research is devoted to the problem of assessing the financial condition of enterprises and forecasting the probability of insolvency. The problem of building an optimal binary classifier is solved. The analysis of existing methods for assessing the solvency of enterprises is performed. Also, some new models that can be used to predict bankruptcy were built using statistical and intellectual methods of data analysis. With the help of the comparative analysis, it is established that the use of modern methods of data analysis makes it possible to obtain a much more qualitative assessment of the financial state of enterprises in comparison with the "classical" methods, e.g. Altman’s, Taffler&Tishaw’s, Zmievski’s.

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