This report examines Artificial Intelligence (AI) in the financial sector, outlining its potential to
revolutionise the industry and identify its challenges. It underscores the criticality of a well …

This study proposes a framework for fraud detection in the auto insurance industry by using
predictive models. The feature selection is performed utilizing a publicly available car …

The banking, financial services, and insurance (BFSI) sector is one of the earliest and most
prominent adopters of artificial intelligence (AI). However, academic research substantially …

Artificial intelligence (AI) has accelerated the advancement of financial services by
identifying hidden patterns from data to improve the quality of financial decisions. However …

Fraud is a significant issue for insurance companies, generating much interest in machine
learning solutions. Although supervised learning for insurance fraud detection has long …

Insurance is a data-rich sector, hosting large volumes of customer data that is analysed to
evaluate risk. Machine learning techniques are increasingly used in the effective …

Over the last decade, digitisation and individualisation have fostered the development of on-
demand services in many industries. In the insurance sector, technological progress brings …

Fraud is a social phenomenon, and fraudsters often collaborate with other fraudsters, taking
on different roles. The challenge for insurance companies is to implement claim assessment …

We develop a novel machine learning (ML) framework to estimate a surrender charge for
variable annuities (VAs) with the balance between human behavior and rational optimality …

The detection of anomalous data patterns is one of the most prominent machine learning
use cases in industrial applications. Unfortunately very often there are no ground truth labels …