Method for Assessing and Forecasting Economic Risks of an Enterprise Based on Data Mining

Abstract

Purpose of research. The main purpose of this work is to improve the quality and efficiency of managerial decisionmaking based on the development of a method for assessing and forecasting economic risks of an enterprise. This method is based on data mining technology.Methods. The paper uses methods of panel data processing and analysis, for which a mathematical model for predicting the level of competitiveness of an enterprise was built, as well as a model for predicting economic risks of an enterprise based on combining several methods of data mining: clustering of merging panel data for assessing economic risks of an enterprise and the method of merging fuzzy correlation for statistical analysis of panel data.Results. As a result of the application of the developed method, quantitative assessments of the level of competitiveness and economic risks of the enterprise were obtained. Based on the obtained quantitative assessments of the level of competitiveness and the level of economic risk, a cluster analysis of enterprises in some industry was carried out. The developed methods have high accuracy in predicting economic risks of enterprises, improve the capabilities of data mining and combining information about economic risks of enterprises, which increases the competitiveness of enterprises.Conclusion. A method of forecasting economic risks of an enterprise based on data mining technology has been developed. Weighted estimates of spatial features of panel data were obtained, which allow to obtain integral estimates of the economic risks of the enterprise and the level of competitiveness of the enterprise. A model for the analysis of fuzzy rules of semantic features of panel intelligent data analysis of the assessment of economic risks of the enterprise is proposed. The analysis shows that the developed method has high accuracy and better protection against interference when predicting data.