Stochastic Loss Reserving Using Generalized Linear Models
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Stochastic Loss Reserving Using Generalized Linear Models
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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
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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.
Bayesian Claims Reserving Methods In Non Life Insurance With Stan
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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.
Claims Reserving In General Insurance
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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.
Claim Models
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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.
Actuarial Sciences And Quantitative Finance
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Author : Jaime A. Londoño
language : en
Publisher: Springer
Release Date : 2017-10-24
Actuarial Sciences And Quantitative Finance written by Jaime A. Londoño and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-24 with Business & Economics categories.
Developed from the Second International Congress on Actuarial Science and Quantitative Finance, this volume showcases the latest progress in all theoretical and empirical aspects of actuarial science and quantitative finance. Held at the Universidad de Cartagena in Cartegena, Colombia in June 2016, the conference emphasized relations between industry and academia and provided a platform for practitioners to discuss problems arising from the financial and insurance industries in the Andean and Caribbean regions. Based on invited lectures as well as carefully selected papers, these proceedings address topics such as statistical techniques in finance and actuarial science, portfolio management, risk theory, derivative valuation and economics of insurance.
Loss Reserving
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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.
Modern Problems Of Stochastic Analysis And Statistics
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Author : Vladimir Panov
language : en
Publisher: Springer
Release Date : 2017-11-21
Modern Problems Of Stochastic Analysis And Statistics written by Vladimir Panov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-21 with Mathematics categories.
This book brings together the latest findings in the area of stochastic analysis and statistics. The individual chapters cover a wide range of topics from limit theorems, Markov processes, nonparametric methods, acturial science, population dynamics, and many others. The volume is dedicated to Valentin Konakov, head of the International Laboratory of Stochastic Analysis and its Applications on the occasion of his 70th birthday. Contributions were prepared by the participants of the international conference of the international conference “Modern problems of stochastic analysis and statistics”, held at the Higher School of Economics in Moscow from May 29 - June 2, 2016. It offers a valuable reference resource for researchers and graduate students interested in modern stochastics.
Loss Reserving
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Author : Gregory Clive Taylor
language : en
Publisher:
Release Date : 2003
Loss Reserving written by Gregory Clive Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Insurance categories.
Machine Learning In Insurance
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Author : Jens Perch Nielsen
language : en
Publisher: MDPI
Release Date : 2020-12-02
Machine Learning In Insurance written by Jens Perch Nielsen and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-02 with Business & Economics categories.
Machine learning is a relatively new field, without a unanimous definition. In many ways, actuaries have been machine learners. In both pricing and reserving, but also more recently in capital modelling, actuaries have combined statistical methodology with a deep understanding of the problem at hand and how any solution may affect the company and its customers. One aspect that has, perhaps, not been so well developed among actuaries is validation. Discussions among actuaries’ “preferred methods” were often without solid scientific arguments, including validation of the case at hand. Through this collection, we aim to promote a good practice of machine learning in insurance, considering the following three key issues: a) who is the client, or sponsor, or otherwise interested real-life target of the study? b) The reason for working with a particular data set and a clarification of the available extra knowledge, that we also call prior knowledge, besides the data set alone. c) A mathematical statistical argument for the validation procedure.