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 …

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 …

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 …

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 …

Banking is a popular topic for empirical and methodological research that applies
operational research (OR) and artificial intelligence (AI) methods. This article provides a …

Enterprise credit evaluation model is an important tool for bank and enterprise risk
management, but how to construct an effective decision tree (DT) ensemble model for …

Credit scoring is an important tool for banks and lending companies to realize credit risk
exposure management and gain profits. GBDTs, a group of boosting-type ensemble …

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 is the risk of financial loss when a borrower fails to meet the financial commitment.
While there are many factors that constitute credit risk, due diligence while giving loan (credit …

In the last years, the application of artificial intelligence methods on credit risk assessment
has meant an improvement over classic methods. Small improvements in the systems about …