Insolvency Pattern Trends in Albanian Enterprises: An in-depth Investigation

Predicting bankruptcy has become a significant focus for researchers, especially during periods of economic instability such as the COVID-19 pandemic and the ongoing Russian-Ukrainian conflict. Early detection of financial distress enables stakeholders to make more informed decisions, minimizing the adverse effects of business failures. In Albania, studies on bankruptcy prediction are scarce, particularly for economic entities such as limited liability companies and joint-stock companies, which dominate the market. This paper aims to develop a bankruptcy prediction model tailored to the Albanian economic environment. By analyzing the financial data of 70 companies, we apply multivariate discriminant analysis to construct a stepwise Z-score model. This model incorporates 25 financial ratios, calculated using the SPSS software, to assess the probability of bankruptcy. Our findings indicate that liquidity, turnover, financial structure, and profitability ratios are significant predictors of bankruptcy. The model achieves an overall classification accuracy of 84.3%, with 91.4% accuracy in predicting bankrupt companies. These results suggest that the model is robust enough to forecast the likelihood of bankruptcy for Albanian economic entities with high accuracy.