Accurate crop yield forecasting is central to effective risk management for many stakeholders, including farmers, insurers, and governments, in various practices, such as crop management, sales and marketing, insurance policy design, premium rate setting, and reserving. This paper rst...

PurposeThe purpose of this paper is to propose an improved reinsurance pricing framework, which includes a crop yield forecasting model that integrates weather variables and crop production information from different geographically correlated regions using a new credibility estimator, and closed...

We propose new neighbouring prediction models for mortality forecasting. For each mortality rate at age x in year t, denoted as mx,t, we construct images of neighbourhood mortality data around mx,t, i.e., ℇmx,t (x1, x2, s), which includes mortality information for ages in [x − x1, x + x2],...

We propose a new machine learning-based framework for long-term mortality forecasting. Based on ideas of neighbouring prediction, model ensembling, and tree boosting, this framework can significantly improve the prediction accuracy of long-term mortality. In addition, the proposed framework...

This paper provides a flexible multi-factor framework to address some ongoing challenges in mortality modeling, with a special focus on the mortality curvature and possible mortality plateau for extremely old ages. We extend the Gompertz law Gompertz (1825) by proposing a multi-factor...