This open access book discusses the statistical modeling of insurance problems, a process
which comprises data collection, data analysis and statistical model building to forecast …

The aim of this article is to present a mixture composite regression model for claim severity
modeling. Claim severity modeling poses several challenges such as multimodality, tail …

Claim reserving is primarily accomplished using macro-level or aggregate models, with the
Chain-Ladder method being the most popular one. However, these methods are …

In general insurance, claims are often lower-truncated and right-censored because
insurance contracts may involve deductibles and maximal covers. Most classical statistical …

We introduce new approaches for forecasting IBNR (Incurred But Not Reported) frequencies
by leveraging individual claims data, which includes accident date, reporting delay, and …

Insurance claim severity data are characterized by complex distributional phenomenons,
where flexible density estimation tools such as the finite mixture models (FMM) are …

ABSTRACT A well-designed framework for risk classification and ratemaking in automobile
insurance is key to insurers' profitability and risk management, while also ensuring that …

This paper introduces a new julia package, LRMoE, a statistical software tailor-made for
actuarial applications, which allows actuarial researchers and practitioners to model and …

This paper introduces a new R package, LRMoE, a statistical software tailor-made for
actuarial applications which allows actuarial researchers and practitioners to model and …

The four-parameter generalized beta distribution of the second kind (GBII) has been
proposed for modeling insurance losses with heavy-tailed features. The aim of this paper is …