Turbulent economic situation, changes in financial reporting, swift legislative changes, or
companies' earnings management during the COVID-19 crisis might have impacted the …

In this study, we apply several advanced machine learning techniques including extreme
gradient boosting (XGBoost), support vector machine (SVM), and a deep neural network to …

Research background: Effective monitoring of financial health is essential in the financial
management of enterprises. Early studies to predict corporate bankruptcy were published at …

There is an increasing interest in machine learning for bankruptcy prediction with more and
more researchers contributing to the literature. Although there is a considerable amount of …

Bankruptcy prediction is an important problem in finance, since successful predictions would
allow stakeholders to take early actions to limit their economic losses. In recent years many …

The area of corporate bankruptcy prediction attains high economic importance, as it affects
many stakeholders. The prediction of corporate bankruptcy has been extensively studied in …

This article presents a comparative analysis of machine learning models for business failure
prediction. Bankruptcy prediction is crucial in assessing financial risks and making informed …

Predicting corporate bankruptcy is one of the fundamental tasks in credit risk assessment. In
particular, since the 2007/2008 financial crisis, it has become a priority for most financial …

Bankruptcy prediction has long been a significant issue in finance and management
science, which attracts the attention of researchers and practitioners. With the great …

Bibliometric analysis is an effective method to carry out quantitative study of academic output
to address the research trends on a given area of investigation through analysing existing …