Selected Methods of Predicting Financial Health of Companies: Neural Networks Versus Discriminant Analysis

Jarmila Horváthová,Martina Mokrišová,Igor Petruška

doi:10.3390/info12120505

Jarmila Horváthová, Martina Mokrišová + Show 1 more

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https://doi.org/10.3390/info12120505

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Journal: Information	Publication Date: Dec 6, 2021
Citations: 9	License type: CC BY 4.0

Affiliation: University of Prešov

Abstract

This paper focuses on the financial health prediction of businesses. The issue of predicting the financial health of companies is very important in terms of their sustainability. The aim of this paper is to determine the financial health of the analyzed sample of companies and to distinguish financially healthy companies from companies which are not financially healthy. The analyzed sample, in the field of heat supply in Slovakia, consisted of 444 companies. To fulfil the aim, appropriate financial indicators were used. These indicators were selected using related empirical studies, a univariate logit model and a correlation matrix. In the paper, two main models were applied—multivariate discriminant analysis (MDA) and feed-forward neural network (NN). The classification accuracy of the constructed models was compared using the confusion matrix, error type 1 and error type 2. The performance of the models was compared applying Brier score and Somers’ D. The main conclusion of the paper is that the NN is a suitable alternative in assessing financial health. We confirmed that high indebtedness is a predictor of financial distress. The benefit and originality of the paper is the construction of an early warning model for the Slovak heating industry. From our point of view, the heating industry works in the similar way in other countries, especially in transition economies; therefore, the model is applicable in these countries as well.

Highlights

There are a number of approaches to measure a company’s financial health and predict its financial distress and bankruptcy, but their use depends on the current market situation, as there is a shift in the development of these measures applied for financial health prediction [1]
The study suggests that neural networks perform significantly better than discriminant analysis in predicting corporate bankruptcies
At the beginning of the analysis and prediction of the financial health of enterprises and their possible bankruptcy, means, medians and standard deviations were calculated for selected financial indicators, especially for the group of enterprises that were prosperous and non-prosperous (Table 3)

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. It is the interest of every business owner to evaluate the financial health of their company as quickly and as as possible. From this point of view, it is important to find out, in particular, whether the company is able to increase its value and provide a guarantee that the investment in the company will receive a return. The question remains how to measure and predict the financial health of a company. The most important measure is the monitoring of the financial performance of the company. There are a number of approaches to measure a company’s financial health and predict its financial distress and bankruptcy, but their use depends on the current market situation, as there is a shift in the development of these measures applied for financial health prediction [1]

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