The use of neural networks in the analysis of economic security of the university

Abstract

Subject. The article considers the introduction of digitalization tools into the process of analyzing the economic security of the university. The growth of technologies related to the use of neural networks, their practical application is currently not adequately developed. Objectives. The aim is to critically review and evaluate the main methods used in the analysis of economic security, develop analytical tools for assessing and forecasting the economic security of higher education institutions based on modern information technology achievements. Methods. The study employs general and specific scientific methods of cognition, methods of data analysis, and machine learning. Results. I reviewed the developed methods of analyzing the economic security of various economic entities and higher educational institutions, underpinned the need to form a complex (integrated) index of economic security of the university, offered a solution to issues related to the choice of methods used for the formation of a complex (integrated) index, the justification of weighting coefficients and threshold values for each index and area of activity of a higher education institution, and interpretation of analysis results. Conclusions. The disclosed formation of the integrated indicator of economic security of the university, the reasoned choice of architecture and method of training of the neural network form the basis for further development of analytical tools to assess economic security, enabling higher efficiency and quality of analysis, and management decisions made on its basis.