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Generalized Linear Models For Insurance Data

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Generalized Linear Models For Insurance Data

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Author : Piet de Jong
language : en
Publisher:
Release Date : 2008

Generalized Linear Models For Insurance Data written by Piet de Jong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Insurance categories.

This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.

Generalized Linear Models For Insurance Data

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Author : Piet de Jong
language : en
Publisher: Cambridge University Press
Release Date : 2008-04-02

Generalized Linear Models For Insurance Data written by Piet de Jong 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 2008-04-02 with Business & Economics categories.

All techniques illustrated on data sets relevant to insurance; SAS code and output, data sets, exercise solutions on website

Generalized Linear Models For Insurance Data

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Author : Piet de Jong
language : en
Publisher:
Release Date : 2008

Non Life Insurance Pricing With Generalized Linear Models

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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.

Theory And Applications Of Generalized Linear Models In Insurance

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Author : Jun Zhou
language : en
Publisher:
Release Date : 2011

Theory And Applications Of Generalized Linear Models In Insurance written by Jun Zhou 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.

Generalized linear models (GLMs) are gaining popularity as a statistical analysis method for insurance data. We study the theory and applications of GLMs in insurance. The first chapter gives an introduction of the theory of GLMs and generalized linear mixed models (GLMMs) as well as the bias correction for GLM estimators. It is shown that the maximum likelihood estimators (MLEs) of the parameters in GLMs are asymptotically normal and asymptotically unbiased. However, when the sample size $n$ or the total Fisher information is small, the MLEs can be biased. The bias is usually ignored in practice. However, in small or moderate--size portfolios, a bias correction can be appreciable. For segmented portfolios, as in car insurance, the question of credibility arises naturally; how many observations are needed in a risk class before the GLM estimators can be considered credible? In this thesis we study the limited fluctuations credibility of the GLM estimators as well as in the extended case of GLMMs. We show how credibility depends on the sample size, the distribution of covariates and the link function. We give a criteria for full credibility of the GLM estimators. This provides a mechanism to obtain confidence intervals for the GLM and GLMM estimators. If the full credibility criteria cannot be satisfied, it is interesting to calculate the partial credibility matrix and the GLM estimators. Here, for a general link function the credibility matrix is not known explicitly. Under certain assumptions, numerical methods are developed to compute the GLM estimators and the credibility matrix. For some specific link functions, further properties are developed. For instance, Hachemeister's credibility regression model is one such special case of our model, where the link function is linear. Loss reserving is a major challenge for casualty actuaries due to the frequently changing business environments. Recently, some aggregate loss reserving models have been extended to or developed by research actuaries within the framework of GLMs. In this thesis we establish a structural loss reserving model which combines the exposure and loss emergence patterns and the loss development pattern, again within the framework of a GLM. Discounted loss reserves can also be obtained from this model.

Predictive Modeling Applications In Actuarial Science

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Author : Edward W. Frees
language : en
Publisher: Cambridge University Press
Release Date : 2014-07-28

Predictive Modeling Applications In Actuarial Science written by Edward W. Frees 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 2014-07-28 with Business & Economics categories.

This book is for actuaries and financial analysts developing their expertise in statistics and who wish to become familiar with concrete examples of predictive modeling.

Proceedings Of The Third International Conference On Computing Mathematics And Statistics Icms2017

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Author : Liew-Kee Kor
language : en
Publisher: Springer
Release Date : 2019-03-27

Proceedings Of The Third International Conference On Computing Mathematics And Statistics Icms2017 written by Liew-Kee Kor and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-27 with Computers categories.

This book is a product of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017) to be held in Langkawi in November 2017. It is divided into four sections according to the thrust areas: Computer Science, Mathematics, Statistics, and Multidisciplinary Applications. All sections sought to confront current issues that society faces today. The book brings collectively quantitative, as well as qualitative, research methods that are also suitable for future research undertakings. Researchers in Computer Science, Mathematics and Statistics can use this book as a sourcebook to enrich their research works.

Actuarial Models For Disability Insurance

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Author : S Haberman
language : en
Publisher: Routledge
Release Date : 2018-12-13

Actuarial Models For Disability Insurance written by S Haberman and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-13 with Mathematics categories.

Disability insurance, long-term care insurance, and critical illness cover are becoming increasingly important in developed countries as the problems of demographic aging come to the fore. The private sector insurance industry is providing solutions to problems resulting from these pressures and other demands of better educated and more prosperous

Navigating The Technological Tide The Evolution And Challenges Of Business Model Innovation

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Author : Bahaaeddin Alareeni
language : en
Publisher: Springer Nature
Release Date : 2024-07-31

Navigating The Technological Tide The Evolution And Challenges Of Business Model Innovation written by Bahaaeddin Alareeni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Technology & Engineering categories.

In an era defined by technological breakthroughs such as AI, blockchain, and IoT, this book offers a fresh and practical approach to Business Model Innovation (BMI). It delves into how technological advancements drive new business models and enhance operational efficiency, providing actionable insights and real-world examples for business leaders, strategists, operations managers, entrepreneurs, and students in business and technology disciplines. Encouraging diverse research methods, including theoretical, empirical, and multimethod studies, it welcomes manuscripts with clear managerial or policy implications. Aimed at students, scholars, researchers, professionals, executives, government agencies, and policymakers, this book equips readers with tools to succeed in today's dynamic business environment and supports multidisciplinary research to advance innovation management practices.

Intelligent And Other Computational Techniques In Insurance

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Author : L. C. Jain
language : en
Publisher: World Scientific
Release Date : 2003

Intelligent And Other Computational Techniques In Insurance written by L. C. Jain and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Business & Economics categories.

This book presents recent advances in the theory and implementation of intelligent and other computational techniques in the insurance industry. The paradigms covered encompass artificial neural networks and fuzzy systems, including clustering versions, optimization and resampling methods, algebraic and Bayesian models, decision trees and regression splines. Thus, the focus is not just on intelligent techniques, although these constitute a major component; the book also deals with other current computational paradigms that are likely to impact on the industry. The application areas include asset allocation, asset and liability management, cash-flow analysis, claim costs, classification, fraud detection, insolvency, investments, loss distributions, marketing, pricing and premiums, rate-making, retention, survival analysis, and underwriting. Contents: Insurance Applications of Neural Networks, Fuzzy Logic, and Genetic Algorithms; Practical Applications of Neural Networks in Property and Casualty Insurance; An Integrated Data Mining Approach to Premium Pricing for the Automobile Insurance Industry; Population Risk Management: Reducing Costs and Managing Risk in Health Insurance; Using Neural Networks to Predict in the Marketplace; Merging Soft Computing Technologies in Insurance-Related Applications; Robustness in Bayesian Models for BonusOCoMalus Systems; Using Data Mining for Modeling Insurance Risk and Comparison of Data Mining and Linear Modeling Approaches; System Intelligence and Active Stock Trading; The Algebra of Cash Flows: Theory and Application; and other papers. Readership: Graduate students, academics, researchers and practitioners involved with actuarial science, insurance, statistics and management science."

Generalized Linear Models For Insurance Data

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