Explainable Artificial Intelligence (XAI) models allow for a more transparent and
understandable relationship between humans and machines. The insurance industry …

The success of artificial intelligence (AI), and deep learning models in particular, has led to
their widespread adoption across various industries due to their ability to process huge …

Most analytics models are built on complex internal learning processes and calculations,
which might be unintuitive, opaque, and incomprehensible to humans. Analytics-based …

Purpose Explainable artificial intelligence (XAI) has importance in several industrial
applications. The study aims to provide a comparison of two important methods used for …

The control of credit risk is an important topic in the development of supply chain finance.
Financial service providers should distinguish between low-and high-quality customers to …

Risk prediction models in credit scoring have to fulfil regulatory requirements, one of which
consists in the interpretability of the model. Unfortunately, many popular modern machine …

The greatest technological transformation the world has ever seen was brought about by
artificial intelligence (AI). It presents significant opportunities for the financial sector to …

Data analytics in financial applications has evolved as a result of technological
improvements, increased data availability, and the necessity for financial institutions to make …

The financial industry's rapid evolution emphasizes the importance of accurate credit
scoring, crucial for decision-making and timely access to loans. Challenges arise due to …

Explainable Artificial Intelligence (XAI) models allow for a more transparent and
understandable relationship between humans and machines. The insurance industry …