Purpose The objective of this study is to provide a systematic review of the literature on
artificial intelligence (AI) in customer-facing financial services, providing an overview of …

Learning styles which refer to students' preferred ways to learn can play an important role in
adaptive e-learning systems. With the knowledge of different styles, the system can offer …

The class imbalance problem is common in the credit scoring domain, as the number of
defaulters is usually much less than the number of non-defaulters. To date, research on …

Given the large amount of customer data available to financial companies, the use of
traditional statistical approaches (eg, regressions) to predict customers' credit scores may …

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 …

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 …

Stock price direction prediction is an important issue in the financial world. Even small
improvements in predictive performance can be very profitable. The purpose of this paper is …

In the context of credit scoring, ensemble methods based on decision trees, such as the
random forest method, provide better classification performance than standard logistic …

In the past few decades, credit scoring has become an increasing concern for financial
institutions and is currently a popular topic of research. This study aims to generate a novel …

Credit risk assessment is a crucial element in credit risk management. With the extensive
research on consumer credit risk assessment in recent decades, the abundance of literature …