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 …

Purpose: The aim of this paper is to conduct a literature review of corporate bankruptcy
prediction models, on the basis of the existing international academic literature in the …

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 …

The bankruptcy prediction model (BPM) is eminently essential for financial institutions to
verify the creditworthiness of companies or management. The inability to accurately predict …

The article provides a comprehensive review regarding the theoretical approaches,
methodologies and empirical researches of corporate bankruptcy prediction, laying …

Corporate bankruptcy and financial distress prediction is a topic of interest for a variety of
stakeholders, including businesses, financial institutions, investors, regulatory bodies …

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 …

Bankruptcy prediction has received a growing interest in corporate finance and risk
management recently. Although numerous studies in the literature have dealt with various …

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

Bankruptcy prediction models are one of the most sought-after tools in financial decision
making performed by pioneer financial institution. Evolution in computation technique have …