Predictive Model as Screening Tool for Early Warning of Corporate Insolvency in Risk Management: Case Study from Slovak Republic

Bankruptcy prediction in Slovakia’s industrial manufacturing sector is vital due to its significant role in the national economy. This study aims to develop a predictive model for forecasting corporate bankruptcy within the industrial manufacturing sector in Slovakia. The novelty of this study lies in developing a model tailored to crisis conditions, validated using COVID-19 data, and adapted to the Central European context for greater accuracy and relevance. The model is constructed using financial data extracted from the Orbis database, based on company financial statements from 2020 and 2021, and encompasses firms of various sizes. Employing backwards binary logistic regression, five statistically significant predictors were identified, enabling the model to forecast impending bankruptcy with a one-year lead time. The model was trained on a sample of 1305 companies and achieves an overall prediction accuracy of 83.78%, with an AUC (Area Under the Curve) value of 91.7%, indicating strong discriminative power. The resulting model demonstrates robust predictive capability and may serve as a practical decision-support tool for managers, investors, creditors, and other stakeholders assessing the financial health of firms.