Year: 2025
Type: article
Abstract: Research objective: The main objective of the article is to present selected discriminant models and a set of financial indicators that enable the assessment of an enterprise's financial condition, with a particular focus on identifying early signs of bankruptcy risk. Methodology: The article was prepared using a critical literature review method, focusing on studies related to the assessment of bankruptcy risk through early warning models. The analysis was based on peer-reviewed academic publications, financial reports, and statistical data from recognized databases such as Scopus, Web of Science, and national financial institutions. Main findings: The analysis shows that discriminant models and financial indicators are valuable tools that help managers detect early warning signs of a company’s worsening financial condition. These tools support informed decision-making in areas such as financial planning, risk assessment, and strategic management. Application of the study: In a dynamic and evolving economic environment, managers must take timely action to reduce the risk of business disruption. Early warning models help identify early symptoms of financial difficulties, enabling quicker and more effective responses. The discriminant models presented in the article support financial decision-making by helping managers assess and improve a company's financial stability. Originality/Novelty of the study: This article highlights the complementary use of discriminant models and financial indicators to assess the risk of insolvency in enterprises. By combining these tools, it provides a multidimensional view of a company's financial condition—both current and future. The study emphasizes the importance of selecting appropriate models depending on the context, offering practical guidance for managers. Unlike previous research that focused on individual models, this paper integrates various approaches, offering a broader framework for evaluating a company’s financial security and supporting more informed decision-making.
Author: Łukasz Antos
Institution: Jan Kochanowski University
Language: English
Subfield: Accounting
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410465251