Artificial intelligence (AI) provides many opportunities to improve private and public life.
Discovering patterns and structures in large troves of data in an automated manner is a core …

Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …

The paper proposes an explainable Artificial Intelligence model that can be used in credit
risk management and, in particular, in measuring the risks that arise when credit is borrowed …

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

We are witnessing a fast development of Artificial Intelligence (AI), but it becomes
dramatically challenging to explain AI models in the past decade.“Explanation” has a flexible …

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 …

Explainability of artificial intelligence methods has become a crucial issue, especially in the
most regulated fields, such as health and finance. In this paper, we provide a global …

Financial technologies, boosted by the availability of machine learning models, are
expanding in all areas of finance: from payments (peer to peer lending) to asset …

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 …

External stakeholders require accurate and explainable financial distress prediction (FDP)
models. Complex machine learning algorithms offer high accuracy, but most of them lack …