You just need to search. Here’s a link to an actuarial case study in our set of case studies by Mick Cooney:
There was a talk at StanCon in Oxford in 2024 about insurance:
Conor Goold
Joint estimation of body and tail loss development factors in insurance: a case study using hidden Markov models in Stan
Here’s a link to their company’s Bayesian product:
Ledger Data Science Team releases BayesBlend - Ledger Newsroom
Here’s a link to an actuarial blog talking about Bayes in general and Stan in particular:
There was a whole workshop:
The second edition of this free textbook uses Stan, STOCHASTIC LOSS RESERVING USING BAYESIAN MCMC MODELS:
https://www.casact.org/sites/default/files/2021-02/08-Meyers.pdf
That was just from the first page of Google hits for Query [stan bayesian insurance actuarial].
Peer review is a very noisy process. I got stuff through peer review before I really understood what I was doing properly and I get stuff rejected now where I’m convinced I know more than the reviewers.
No, but you have a lot of code and documentation that’s gone through peer review!