© 2018

Bayesian Claims Reserving Methods in Non-life Insurance with Stan

An Introduction


  • The first book provides explicit Stan code for non-life claims reserving

  • The book has a thorough review of many aspects of Bayesian statistics, and relates them to claims reserving problem

  • The book addresses three important points in claims reserving: proposing a stochastic payments per claim incurred model (Section 4), estimating the tail factor via basis expansion models (Section 5), and aggregating claims liabilities by copulas (Section 6)


Table of contents

  1. Front Matter
    Pages i-xii
  2. Guangyuan Gao
    Pages 1-8
  3. Guangyuan Gao
    Pages 9-33
  4. Guangyuan Gao
    Pages 35-71
  5. Guangyuan Gao
    Pages 73-115
  6. Guangyuan Gao
    Pages 117-152
  7. Guangyuan Gao
    Pages 153-183
  8. Guangyuan Gao
    Pages 185-190
  9. Back Matter
    Pages 191-205

About this book


This book first provides a review of various aspects of Bayesian statistics. It then investigates three types of claims reserving models in the Bayesian framework: chain ladder models, basis expansion models involving a tail factor, and multivariate copula models. For the Bayesian inferential methods, this book largely relies on Stan, a specialized software environment which applies Hamiltonian Monte Carlo method and variational Bayes.  


Non-life insurance claims reserving models Bayesian claims reserving models Basis expansion models Payments per claim incurred method Multivariate claims reserving model Markov chain Monte Carlo methods Stan Copulas

Authors and affiliations

  1. 1.School of StatisticsRenmin University of ChinaBeijingChina

About the authors

Guangyuan Gao, lecturer in actuarial science, School of Statistics at the Renmin University of China.

Bibliographic information