Stochastic Loss Reserving Using Generalized Linear Models
DOWNLOAD
Download Stochastic Loss Reserving Using Generalized Linear Models PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Stochastic Loss Reserving Using Generalized Linear Models book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Stochastic Loss Reserving Using Generalized Linear Models
DOWNLOAD
Author : Greg Taylor
language : en
Publisher:
Release Date : 2016-05-04
Stochastic Loss Reserving Using Generalized Linear Models written by Greg Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-04 with categories.
In this monograph, authors Greg Taylor and Gráinne McGuire discuss generalized linear models (GLM) for loss reserving, beginning with strong emphasis on the chain ladder. The chain ladder is formulated in a GLM context, as is the statistical distribution of the loss reserve. This structure is then used to test the need for departure from the chain ladder model and to consider natural extensions of the chain ladder model that lend themselves to the GLM framework.
Stochastic Claims Reserving Methods In Insurance
DOWNLOAD
Author : Mario V. Wüthrich
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-30
Stochastic Claims Reserving Methods In Insurance written by Mario V. Wüthrich and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-30 with Business & Economics categories.
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.
Stochastic Loss Reserving Using Bayesian Mcmc Models
DOWNLOAD
Author : Glenn Meyers
language : en
Publisher:
Release Date : 2015
Stochastic Loss Reserving Using Bayesian Mcmc Models written by Glenn Meyers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Actuarial science categories.
"The emergence of Bayesian Markov Chain Monte-Carlo (MCMC) models has provided actuaries with an unprecedented flexibility in stochastic model development. Another recent development has been the posting of a database on the CAS website that consists of hundreds of loss development triangles with outcomes. This monograph begins by first testing the performance of the Mack model on incurred data, and the Bootstrap Overdispersed Poisson model on paid data. It then will identify features of some Bayesian MCMC models that improve the performance over the above models. The features examined include 1) recognizing correlation between accident years; (2) introducing a skewed distribution defined over the entire real line to deal with negative incremental paid data; (3) allowing for a payment year trend on paid data; and (4) allowing for a change in the claim settlement rate. While the specific conclusions of this monograph pertain only to the data in the CAS Loss Reserve Database, the breadth of this study suggests that the currently popular models might similarly understate the range of outcomes for other loss triangles. This monograph then suggests features of models that actuaries might consider implementing in their stochastic loss reserve models to improve their estimates of the expected range of outcomes"--front cover verso.
Bayesian Claims Reserving Methods In Non Life Insurance With Stan
DOWNLOAD
Author : Guangyuan Gao
language : en
Publisher: Springer
Release Date : 2018-12-31
Bayesian Claims Reserving Methods In Non Life Insurance With Stan written by Guangyuan Gao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Mathematics categories.
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.
A Comparison Of Stochastic Claim Reserving Methods
DOWNLOAD
Author : Eric M. Mann
language : en
Publisher:
Release Date : 2011
A Comparison Of Stochastic Claim Reserving Methods written by Eric M. Mann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
Estimating unpaid liabilities for insurance companies is an extremely important aspect of insurance operations. Consistent underestimation can result in companies requiring more reserves which can lead to lower profits, downgraded credit ratings, and in the worst case scenarios, insurance company insolvency. Consistent overestimation can lead to inefficient capital allocation and a higher overall cost of capital. Due to the importance of these estimates and the variability of these unpaid liabilities, a multitude of methods have been developed to estimate these amounts. This paper compares several actuarial and statistical methods to determine which are relatively better at producing accurate estimates of unpaid liabilities. To begin, the Chain Ladder Method is introduced for those unfamiliar with it. Then a presentation of several Generalized Linear Model (GLM) methods, various Generalized Additive Model (GAM) methods, the Bornhuetter-Ferguson Method, and a Bayesian method that link the Chain Ladder and Bornhuetter-Ferguson methods together are introduced, with all of these methods being in some way connected to the Chain Ladder Method. Historical data from multiple lines of business compiled by the National Association of Insurance Commissioners is used to compare the methods across different loss functions to gain insight as to which methods produce estimates with the minimum loss and to gain a better understanding of the relative strengths and weaknesses of the methods. Key.
Claim Models
DOWNLOAD
Author : Greg Taylor
language : en
Publisher: MDPI
Release Date : 2020-04-15
Claim Models written by Greg Taylor and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-15 with Business & Economics categories.
This collection of articles addresses the most modern forms of loss reserving methodology: granular models and machine learning models. New methodologies come with questions about their applicability. These questions are discussed in one article, which focuses on the relative merits of granular and machine learning models. Others illustrate applications with real-world data. The examples include neural networks, which, though well known in some disciplines, have previously been limited in the actuarial literature. This volume expands on that literature, with specific attention to their application to loss reserving. For example, one of the articles introduces the application of neural networks of the gated recurrent unit form to the actuarial literature, whereas another uses a penalized neural network. Neural networks are not the only form of machine learning, and two other papers outline applications of gradient boosting and regression trees respectively. Both articles construct loss reserves at the individual claim level so that these models resemble granular models. One of these articles provides a practical application of the model to claim watching, the action of monitoring claim development and anticipating major features. Such watching can be used as an early warning system or for other administrative purposes. Overall, this volume is an extremely useful addition to the libraries of those working at the loss reserving frontier.
Using The Odp Bootstrap Model
DOWNLOAD
Author : Mark R. Shapland
language : en
Publisher:
Release Date : 2016
Using The Odp Bootstrap Model written by Mark R. Shapland and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Actuarial science categories.
Claims Reserving In General Insurance
DOWNLOAD
Author : David Hindley
language : en
Publisher: Cambridge University Press
Release Date : 2017-10-26
Claims Reserving In General Insurance written by David Hindley and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-26 with Business & Economics categories.
This is a single comprehensive reference source covering the key material on this subject, and describing both theoretical and practical aspects.
Loss Reserving
DOWNLOAD
Author : Gregory Taylor
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Loss Reserving written by Gregory Taylor and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.
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.
Non Life Insurance Pricing With Generalized Linear Models
DOWNLOAD
Author : Esbjörn Ohlsson
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-18
Non Life Insurance Pricing With Generalized Linear Models written by Esbjörn Ohlsson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-18 with Mathematics categories.
Non-life insurance pricing is the art of setting the price of an insurance policy, taking into consideration varoius properties of the insured object and the policy holder. Introduced by British actuaries generalized linear models (GLMs) have become today a the standard aproach for tariff analysis. The book focuses on methods based on GLMs that have been found useful in actuarial practice and provides a set of tools for a tariff analysis. Basic theory of GLMs in a tariff analysis setting is presented with useful extensions of standarde GLM theory that are not in common use. The book meets the European Core Syllabus for actuarial education and is written for actuarial students as well as practicing actuaries. To support reader real data of some complexity are provided at www.math.su.se/GLMbook.