Claim Reserving in Non-Life Insurance
Author : G. C. Taylor
Publisher :
Page : pages
File Size : 22,31 MB
Release : 1986
Category :
ISBN : 9780785542551
Author : G. C. Taylor
Publisher :
Page : pages
File Size : 22,31 MB
Release : 1986
Category :
ISBN : 9780785542551
Author : Guangyuan Gao
Publisher : Springer
Page : 210 pages
File Size : 40,59 MB
Release : 2018-12-31
Category : Mathematics
ISBN : 9811336091
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.
Author : Mario V. Wüthrich
Publisher : John Wiley & Sons
Page : 438 pages
File Size : 11,3 MB
Release : 2008-04-30
Category : Business & Economics
ISBN : 0470772727
Claims reserving is central to the insurance industry. Insurance liabilities depend on a number of different risk factors which need to be predicted accurately. This prediction of risk factors and outstanding loss liabilities is the core for pricing insurance products, determining the profitability of an insurance company and for considering the financial strength (solvency) of the company. Following several high-profile company insolvencies, regulatory requirements have moved towards a risk-adjusted basis which has lead to the Solvency II developments. The key focus in the new regime is that financial companies need to analyze adverse developments in their portfolios. Reserving actuaries now have to not only estimate reserves for the outstanding loss liabilities but also to quantify possible shortfalls in these reserves that may lead to potential losses. Such an analysis requires stochastic modeling of loss liability cash flows and it can only be done within a stochastic framework. Therefore stochastic loss liability modeling and quantifying prediction uncertainties has become standard under the new legal framework for the financial industry. This book covers all the mathematical theory and practical guidance needed in order to adhere to these stochastic techniques. Starting with the basic mathematical methods, working right through to the latest developments relevant for practical applications; readers will find out how to estimate total claims reserves while at the same time predicting errors and uncertainty are quantified. Accompanying datasets demonstrate all the techniques, which are easily implemented in a spreadsheet. A practical and essential guide, this book is a must-read in the light of the new solvency requirements for the whole insurance industry.
Author : Gregory Clive Taylor
Publisher : North Holland
Page : 252 pages
File Size : 17,51 MB
Release : 1986
Category : Business & Economics
ISBN :
Author : David Hindley
Publisher : Cambridge University Press
Page : 513 pages
File Size : 25,36 MB
Release : 2017-10-26
Category : Business & Economics
ISBN : 1107076935
This is a single comprehensive reference source covering the key material on this subject, and describing both theoretical and practical aspects.
Author : Gregory Taylor
Publisher : Springer Science & Business Media
Page : 396 pages
File Size : 18,83 MB
Release : 2012-12-06
Category : Business & Economics
ISBN : 1461545838
All property and casualty insurers are required to carry out loss reserving as a statutory accounting function. Thus, loss reserving is an essential sphere of activity, and one with its own specialized body of knowledge. While few books have been devoted to the topic, the amount of published research literature on loss reserving has almost doubled in size during the last fifteen years. Greg Taylor's book aims to provide a comprehensive, state-of-the-art treatment of loss reserving that reflects contemporary research advances to date. Divided into two parts, the book covers both the conventional techniques widely used in practice, and more specialized loss reserving techniques employing stochastic models. Part I, Deterministic Models, covers very practical issues through the abundant use of numerical examples that fully develop the techniques under consideration. Part II, Stochastic Models, begins with a chapter that sets up the additional theoretical material needed to illustrate stochastic modeling. The remaining chapters in Part II are self-contained, and thus can be approached independently of each other. A special feature of the book is the use throughout of a single real life data set to illustrate the numerical examples and new techniques presented. The data set illustrates most of the difficult situations presented in actuarial practice. This book will meet the needs for a reference work as well as for a textbook on loss reserving.
Author : Jonas Crevecoeur
Publisher :
Page : pages
File Size : 12,89 MB
Release : 2020
Category :
ISBN :
Author : Robert L. Brown
Publisher : ACTEX Publications
Page : 204 pages
File Size : 34,52 MB
Release : 2007
Category : Business & Economics
ISBN : 1566986117
Author : Thomas Mikosch
Publisher : Springer Science & Business Media
Page : 435 pages
File Size : 33,72 MB
Release : 2009-04-21
Category : Mathematics
ISBN : 3540882332
"Offers a mathematical introduction to non-life insurance and, at the same time, to a multitude of applied stochastic processes. It gives detailed discussions of the fundamental models for claim sizes, claim arrivals, the total claim amount, and their probabilistic properties....The reader gets to know how the underlying probabilistic structures allow one to determine premiums in a portfolio or in an individual policy." --Zentralblatt für Didaktik der Mathematik
Author : Anders Hedegaard Jessen
Publisher :
Page : pages
File Size : 10,62 MB
Release : 2009
Category :
ISBN : 9788791927430