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 …

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

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 …

Credit risk assessment plays a key role for correctly supporting financial institutes in defining
their bank policies and commercial strategies. Over the last decade, the emerging of social …

Credit risk assessment is at the core of modern economies. Traditionally, it is measured by
statistical methods and manual auditing. Recent advances in financial artificial intelligence …

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 …

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 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 …

Big data and analytics (BDA) are gaining momentum, particularly in the practitioner world.
Research linking BDA to improved organizational performance seems scarce and widely …