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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.
This handbook presents the basic aspects of actuarial loss reserving. Besides the traditional methods, it also includes a description of more recent ones and a discussion of certain problems occurring in actuarial practice, like inflation, scarce data, large claims, slow loss development, the use of market statistics, the need for simulation techniques and the task of calculating best estimates and ranges of future losses. In property and casualty insurance the provisions for payment obligations from losses that have occurred but have not yet been settled usually constitute the largest item on the liabilities side of an insurer's balance sheet. For this reason, the determination and evaluation of these loss reserves is of considerable economic importance for every property and casualty insurer. Actuarial students, academics as well as practicing actuaries will benefit from this overview of the most important actuarial methods of loss reserving by developing an understanding of the underlying stochastic models and how to practically solve some problems which may occur in actuarial practice.
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.
The paper reviews the development of loss reserving models over the past, classifying them according to an elementary taxonomy. The taxonomic components include (1) the algebraic structure of the model, (2) the form of its parameter estimation, (3) whether or not it is explicitly stochastic, and (4) whether or not its parameters evolve over time. Particular attention is given to one of the higher species of model, involving complex structure, optimal estimation, and evolutionary parameters. A generalisation of the Kalman filter is considered as a basis of adaptive loss reserving in this case. Real life numerical examples are provided.Some implications of this type of data analysis for loss reserving are discussed, with particular reference to the form of data set used. The use of triangular arrays is questioned, and alternatives examined. Again, real life numerical examples are provided.
This is a single comprehensive reference source covering the key material on this subject, and describing both theoretical and practical aspects.
Inspired by the website that the New York Times hailed as "redefining mourning," this book is a fresh and irreverent examination into navigating grief and resilience in the age of social media, offering comfort and community for coping with the mess of loss through candid original essays from a variety of voices, accompanied by gorgeous two-color illustrations and wry infographics. At a time when we mourn public figures and national tragedies with hashtags, where intimate posts about loss go viral and we receive automated birthday reminders for dead friends, it’s clear we are navigating new terrain without a road map. Let’s face it: most of us have always had a difficult time talking about death and sharing our grief. We’re awkward and uncertain; we avoid, ignore, or even deny feelings of sadness; we offer platitudes; we send sympathy bouquets whittled out of fruit. Enter Rebecca Soffer and Gabrielle Birkner, who can help us do better. Each having lost parents as young adults, they co-founded Modern Loss, responding to a need to change the dialogue around the messy experience of grief. Now, in this wise and often funny book, they offer the insights of the Modern Loss community to help us cry, laugh, grieve, identify, and—above all—empathize. Soffer and Birkner, along with forty guest contributors including Lucy Kalanithi, singer Amanda Palmer, and CNN’s Brian Stelter, reveal their own stories on a wide range of topics including triggers, sex, secrets, and inheritance. Accompanied by beautiful hand-drawn illustrations and witty "how to" cartoons, each contribution provides a unique perspective on loss as well as a remarkable life-affirming message. Brutally honest and inspiring, Modern Loss invites us to talk intimately and humorously about grief, helping us confront the humanity (and mortality) we all share. Beginners welcome.