TITLE:
Can Failure Process Information Improve Bankruptcy Prediction? Evidence from Finland
AUTHORS:
Erkki K. Laitinen
KEYWORDS:
Bankruptcy, Prediction of Bankruptcy, Failure Process, Process Measures, Finnish Firms
JOURNAL NAME:
Theoretical Economics Letters,
Vol.15 No.2,
April
27,
2025
ABSTRACT: Bankruptcies result in significant financial and social losses for all stakeholders of companies each year. For this reason, researchers have been working for decades to develop effective methods for predicting bankruptcy. Most prediction models are based on financial ratios extracted from the last financial statements before bankruptcy. However, researchers have given less attention to the process that led the company to bankruptcy. The purpose of this study is to investigate whether information about the process can improve bankruptcy prediction. The benchmark model was based on three financial ratios measuring profitability, liquidity, and solvency. The process model was constructed using these ratios and their processes leading up to bankruptcy. The process of each ratio was measured by two dimensions: the form and the level of the process. The importance of process information was assessed using data from Finnish limited companies. The data included 147 bankrupt companies and 23,386 active companies. The results of the logistic regression analysis showed that process information helps improve prediction accuracy, but the effect is not strong.