Credit risk is the critical problem faced by banking and financial sectors when the borrower
fails to complete their commitments to pay back. The factors that could increase credit risk …

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, stemming from the failure of a contractual party, is a significant variable in
financial institutions. Assessing credit risk involves evaluating the creditworthiness of …

Financial institutions are increasingly leveraging on advanced technologies, facilitated by
the availability of Machine Learning methods that are being integrated into several …

The quest to open black box artificial intelligence (AI) systems evolved into an emerging
phenomenon of global interest for academia, business, and society and brought about the …

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 …

Diabetes is a deadly chronic disease that occurs when the pancreas is not able to produce
ample insulin or when the body cannot use insulin effectively. If undetected, it may lead to a …

Federated learning has drawn a lot of interest as a powerful technological solution to the
“credit data silo” problem. The interpretability of federated learning is a crucial issue due to …

As the range of decisions made by Artificial Intelligence (AI) expands, the need for
Explainable AI (XAI) becomes increasingly critical. The reasoning behind the specific …

Banks' credit scoring models are required by financial authorities to be explainable. This
paper proposes an explainable artificial intelligence (XAI) model for predicting credit default …