In practice, as a well-known statistical method, the logistic regression model is used to
evaluate the credit-worthiness of borrowers due to its simplicity and transparency in …

There is an increasing influence of machine learning in business applications, with many
solutions already implemented and many more being explored. Since the global financial …

The family of gradient boosting algorithms has been recently extended with several
interesting proposals (ie XGBoost, LightGBM and CatBoost) that focus on both speed and …

The water quality prediction performance of machine learning models may be not only
dependent on the models, but also dependent on the parameters in data set chosen for …

Class imbalance impedes the predictive performance of classification models. Popular
countermeasures include oversampling minority class cases by creating synthetic examples …

Rare events, especially those that could potentially negatively impact society, often require
humans' decision-making responses. Detecting rare events can be viewed as a prediction …

This paper focuses on how to effectively construct dynamic financial distress prediction
models based on class-imbalanced data streams. Two class-imbalanced dynamic financial …

Credit scoring is an effective tool for banks to properly guide decision profitably on granting
loans. Ensemble methods, which according to their structures can be divided into parallel …

Artificial intelligence (AI) is receiving increasing attention in business and society. In
banking, the first applications of AI were successful; however, AI is mainly applied in …

Many years have passed since Baesens et al. published their benchmarking study of
classification algorithms in credit scoring [Baesens, B., Van Gestel, T., Viaene, S …