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

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

With improved machine learning models, studies on bankruptcy prediction show improved
accuracy. This paper proposes three relatively newly-developed methods for predicting …

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 …

Bankruptcy prediction is considered as one of the vital topics in finance and accounting. The
purpose of predicting bankruptcy is to build a predictive model that combines several …

Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent
studies have shown that machine learning techniques achieved better performance than …

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 problem has been intensively studied over the past decades. From
traditional statistical models to state of the art machine learning models, various predictive …

This study proposes an integration strategy regarding how to efficiently combine the
currently-in-use statistical and artificial intelligence techniques. In particular, by combining …

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 …