In January 2019, the Italian government approved the corporate insolvency law reform, henceforth the Code of Crisis (CCI). This law reform has brought back to the center of the scientific debate the financial distress and insolvency prediction models. In recent decades, there has been a large number of studies about predicting models variously developed by scholars. These studies were about ratio-based and non-ratio-based models, and had to do with statistical approach, model types employed, scoring-based models, and so on. Moreover, these studies also related to an increasing evolution of these models, for example, accounting-based vs. market-based value in statistical multivariate estimation models, leading to greater predictive power. Accordingly, the authors conducted a systematic review of studies published between 1960 and 2020. Thereby, this paper aims to map the studies that are concerned with financial distress and related predicting models in order to portray the state of the scientific debate thus far and, at the same time, the different types, approaches and methods employed along with future trends. Furthermore, this study tries to provide a possible framework for further research about this field, thereby improving our understanding of prediction models and their evolution over time in relation to the digital technologies as well.
Keywords: Business crisis, Insolvency, Literature review, Financial distress, Predicting models.
Luca Ianni, Gianluca Marullo, Stefania Migliori, Francesco De Luca, Financial distress and insolvency prediction models: A systematic review in "MANAGEMENT CONTROL" 2/2021, pp. 127-146, DOI:10.3280/MACO2021-002007