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 …

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 …

The logistic regression model is widely used in credit scoring practice due to its strong
interpretability of results, but its recognition performance for default samples which are …

Although black-box models such as ensemble learning models often provide better
predictive performance than intrinsic interpretable models such as logistic regression, black …

In recent years, to handle the ubiquitous uncertainty and unknown noise, different fuzzy
clustering methods have been introduced to solve image segmentation problem for various …

Conventional ensemble clustering is a consensus function that fails to produce final clusters.
Such poor clusters partitioning creates poor stability with reduced clustering accuracy. This …

In this era of Big Data and the advancement of sophisticated analytical techniques, the
financial industry has the capacity to implement innovative technologies within their systems …

Binary classification tasks often face challenges due to imbalanced datasets. The Weighted
Binary Extreme Learning Machine (WB-ELM) has emerged as a potential solution, but its …

Credit cards have become indispensable in modern times, offering convenience, security,
and financial benefits. As fraudsters continually evolve tactics to evade detection, security …

The challenge of the development of information technology at the present time is not only
centered on the technology itself but must be able to collaborate with other fields to be more …