Abstract
This article addresses the financial performance prediction for Latvian companies. It is of critical importance to be able to provide timely warnings to management, investors, employees, stakeholders and other interested parties who wish to reduce their losses. There are literature review structures that previously made research into company performance prediction. Estimating the risk of bankruptcy of Latvian companies has been carried out by applying two commonly used approaches: Altman’s Z-score estimation and an experience-based machine learning approach using C4.5 Decision Tree. The results show that Altman’s Z-score method predicts bankruptcy for a massive number of companies, while the ML method predicts bankruptcy for only a few. Each of these approaches has its drawbacks. We propose an extended company performance prediction model that considers other factors that influence distress risk, e.g., changes in regulation and other environmental factors. Expert opinion is of great value in estimating a company’s future performance; therefore, an automated solution supporting experts in their decision-making is presented.
Highlights
The Directive of The European Parliament and the Council on preventive restructuring frameworks on the discharge of debt and disqualifications for each member state requires implementing the company warning system
If we look more closely at both methods’ capabilities of capturing bankruptcy cases, the Altman’s Z-score’s bankruptcy prediction precision average is 19.9%, and the Machine learning (ML)-approaches recall average is 11.3%
This article is devoted to the research on company bankruptcy prediction solutions, experiments on bankruptcy prediction for Latvian companies, and the development of a more intelligent company bankruptcy prediction model that can serve as an early warning system
Summary
The Directive of The European Parliament and the Council on preventive restructuring frameworks on the discharge of debt and disqualifications (further on – Directive) for each member state requires implementing the company warning system. Estimating the risk of bankruptcy of a specific company substantiates economic impact to its owners, investors and stakeholders [1], [2]. Such an alert system would allow these companies to make timely adjustments to their operations in order to survive or show better financial results. Available warning systems are based on analyzing the financial ratios most commonly using the Reference: A. “Development of Bankruptcy Prediction Model for Latvian Companies,” Complex Systems Informatics and Modeling Quarterly, CSIMQ, no.
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