This study aims to conduct a bibliometric analysis of reputational risk and sustainability. The research was conducted using the Scopus database, which returned 88 publications published during 2001-2020, revealing that the amount of research output within this field is limited, and more...

Life insurers, whose contractual liabilities include providing minimum guaranteed interest rates to policyholders, are significantly affected by persistently low interest rates. Hence, this study reviews the literature on the prolonged low interest rate environment and its impact on the life...

The purpose of this paper is to propose a methodology that enables researchers to identify relevant search terms when conducting a literature review. This methodology requires an analysis of existing literature review articles on the topic under study to form keywords. The objective of this...

In insurance rate-making, the use of statistical machine learning techniques such as artificial neural networks (ANN) is an emerging approach, and many insurance companies have been using them for pricing. However, due to the complexity of model specification and its implementation, model...

The need to assess the risks of the trustworthiness of counterparties is increasing every year. The identification of increasing cases of unfair behavior among counterparties only confirms the relevance of this topic. The existing work in the field of information and economic security does not...

We propose a hybrid classical-quantum approach for modeling transition probabilities in health and disability insurance. The modeling of logistic disability inception probabilities is formulated as a support vector regression problem. Using a quantum feature map, the data are mapped to quantum...

The growing trend in the number and severity of auto insurance claims creates a needfor new methods to efficiently handle these claims. Machine learning (ML) is one of the methodsthat solves this problem. As car insurers aim to improve their customer service, these companieshave started adopting...

The purpose of this paper is to survey recent developments in granular models and machine learning models for loss reserving, and to compare the two families with a view to assessment of their potential for future development. This is best understood against the context of the evolution of these...

Calibration is a highly challenging task, in particular in multiple yield curve markets. This paper is a first attempt to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian process regression, a machine learning methodology having many...

Banks play a vital role in strengthening the financial system of a country; hence, their survival is decisive for the stability of national economies. Therefore, analyzing the survival probability of the banks is an essential and continuing research activity. However, the current literature...