Predicting impending bankruptcy and financial distress of a mining company using the HGN model

Early identification of imminent bankruptcy is crucial for saving a company. It allows for timely implementation of essential measures through preventive restructuring. This paper addresses the current issue of identifying impending bankruptcy in non-financial companies. Existing predictive models can be used to detect imminent bankruptcy, but most of them fail to identify it in time. In this paper, we apply our own predictive model, HGN. Previous research has confirmed its usefulness in performance evaluation, as well as its predictive capability. The model takes into account significant factors that influence the unfavourable financial situation of a company. Detecting the imminent bankruptcy of a company in a timely manner requires an exact approach to modifying the model. The modified version of the model places a strong emphasis on the company's debt situation, regardless of the time horizon of the debt. For the purposes of early identification of impending bankruptcy, the model is tested based on real data from a company in the Mining of chemical and fertiliser minerals sector (SK NACE 08.91.0). The company underwent restructuring and eventually went bankrupt, meeting the criteria for testing the identification of imminent bankruptcy. By substituting certain financial indicators contained in the basic version of the HGN model, we modify its calculation to provide a more objective forecast of undesirable development. The modification emphasises the financial situation and the factors that significantly influence future trends. Based on the comparative analysis and quantified results, we recommend the preference of the HGN model for the early warning system.