Corporate Financial Distress: an Alert Perspective. Statistical Background, Firm Valuation and Empirical Evidences from Italian Firms in a Digital Age Context

Banks are nowadays compelled to implement specifically adequate internal procedures and reporting files to be able to identify and manage potential non-performing corporations at a very early stage. This practice has become necessary to monitor performing loans and avoid any deterioration in credit quality. Banks have to fix the set of UTP (“Unlikely-To-Pay”) and consider all the situations listed both in the EU CRR (“Capital Requirements Regulation”) definition of default and in the IFRS notion of impairment. Different sets of UTP triggers may be defined on a portfolio-by-portfolio basis where the core corresponds to the financial distress prediction, which represents an extensive ongoing research topic. To investigate the influence on different states of financial distress of both micro-economic indicators and firm-specific factors, this paper applies a predictive model, well known in academics, on a unique sample of UTP. In particular, the Z-Score and its revised version were applied to companies included in a special and confidential register of UTP loan positions from a major Italian bank. This allowed the authors to effectively analyze the ZScore and Z’-Score ability to predict UTP positions. Existing literature on Z-Score, on the contrary, considers the filling of bankruptcy procedures as a criterion for distress, which represents only the final phase of a crisis. In addition, the inclusion of corporate governance variables as control variables is another relevant contribution, since most of past research includes only economic and financial variables. Results confirm the ability of the Z’-Score model to predict UTP, which is an event far earlier than insolvency