Assessment of Post-Crisis Financial Performance and Actions in Italian Companies

The Covid-19 epidemic, which has been effective all over the world since the beginning of 2020, has become an economic crisis with the restrictions imposed by states to stop the spread of this epidemic. While this situation caused serious damage to the production activities of many countries, it brought many companies whose financial situation was not so good anyway to the bankruptcy threshold. Using the financial and non-financial variables of 380 innovative companies, selected among 160 thousand SMEs in Italy that is one of the European countries most affected by Covid-19 economic crisis, the financial impact of the crisis on these companies has been tried to be analyzed by comparing the probability of bankruptcy predicted before and after Covid-19. Prediction was carried out using the machine learning algorithm created by ARISK in order to perform the analysis. The aim of the study is to provide a different perspective to the literature in predicting the bankruptcy status of companies in terms of both the types of companies it evaluates and the algorithm it uses. In this study, the most important point to be reached is the analysis of short, middle, and long-term bankruptcy and default situations by performing predictive financial analysis of especially SMEs companies. This study is expected to be a guiding research for the long-term strategic decisions of companies regarding their financial status. Keywords: Bankruptcy prediction, machine learning, risk management, Covid-19 crisis