Fuzzy-Multiple Analysis of Financial Statements of Enterprises

Abstract

The aim of the paper is to develop a methodology for assessing the financial condition of an enterprise based on a fuzzy-multiple modification of the Audit-IT integrated scoring methodology. The modification was carried out using the approach developed by O. A. Nedosekin to assess the risk of bankruptcy of the enterprise and consisting in the aggregation of indicators of coefficient analysis using standard five-point classifiers. Based on the developed methodology, the estimates of the financial condition and performance, as well as the integral assessment (score) of the financial condition of the enterprise for three years, were calculated. The correspondence of the calculated estimates to the results obtained using Audit-IT was revealed. At the next step, the technique is modified by including additional parameters in the complex and dividing it into four blocks: (1) financial soundness; (2) liquidity; (3) profitability; (4) business activity. An integrated assessment for each of the blocks was found by aggregating indicators calculated by the “Your Financial Analyst” program. The final assessment of the financial and economic condition of the enterprise is formed by aggregating four integral estimates based on standard five-point classifiers. Calculation of relevant estimates allows for intra-industry ranking of enterprises, as well as their clustering, followed by a study of the correlation dependencies between indicators of financial and economic activity within clusters. The proposed methodology demonstrates the possibility of transforming the standard integrated scoring methodology for assessing the financial condition of an enterprise into the corresponding fuzzy-plural technique, which has a number of important advantages. In particular, it allows to change the complex of the studied parameters depending on the goals and objectives of the study without significant processing of the model; to adjust the weight of the parameters depending on the industry and territorial specifics, as well as to conduct expert assessments; as well as to bring together quantitative estimates of indicators with estimates of the dynamics of their change.