Accurate estimation of value-at-risk (VaR) and assessment of associated uncertainty is crucial for both insurers and regulators, particularly in Europe. Existing approaches link data and VaR indirectly by first linking data to the parameter of a probability model, and then expressing VaR as a...

In the context of predicting future claims, a fully Bayesian analysis --- one that specifies a statistical model, prior distribution, and updates using Bayes's formula --- is often viewed as the gold-standard, while Buhlmann's credibility estimator serves as a simple approximation. But those...

Here we make several comments concerning the full nonparametric Bayesian approach that motivated the new techniques in the paper "Credibility estimation of distribution functions with applications to experience rating and general insurance,'' by Cai, Wen, Wu, and Zhou, published in the North...

With the advent of the "big" data era, large-sample properties of a statistical learning method are becoming more and more important in an actuary's daily work. For a fixed sample size, regardless of how large it is, the variance of an estimator can be larger than a pre-assigned level to an...