Search Results for "non-life-insurance-pricing-with-generalized-linear-models"

Non-Life Insurance Pricing with Generalized Linear Models

Non-Life Insurance Pricing with Generalized Linear Models

  • Author: Esbjörn Ohlsson,Björn Johansson
  • Publisher: Springer Science & Business Media
  • ISBN: 9783642107917
  • Category: Mathematics
  • Page: 174
  • View: 5938
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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.

Pricing in General Insurance

Pricing in General Insurance

  • Author: Pietro Parodi
  • Publisher: CRC Press
  • ISBN: 1466581441
  • Category: Business & Economics
  • Page: 584
  • View: 4609
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Based on the syllabus of the actuarial industry course on general insurance pricing — with additional material inspired by the author’s own experience as a practitioner and lecturer — Pricing in General Insurance presents pricing as a formalised process that starts with collecting information about a particular policyholder or risk and ends with a commercially informed rate. The main strength of this approach is that it imposes a reasonably linear narrative on the material and allows the reader to see pricing as a story and go back to the big picture at any time, putting things into context. Written with both the student and the practicing actuary in mind, this pragmatic textbook and professional reference: Complements the standard pricing methods with a description of techniques devised for pricing specific products (e.g., non-proportional reinsurance and property insurance) Discusses methods applied in personal lines when there is a large amount of data and policyholders can be charged depending on many rating factors Addresses related topics such as how to measure uncertainty, incorporate external information, model dependency, and optimize the insurance structure Provides case studies, worked-out examples, exercises inspired by past exam questions, and step-by-step methods for dealing concretely with specific situations Pricing in General Insurance delivers a practical introduction to all aspects of general insurance pricing, covering data preparation, frequency analysis, severity analysis, Monte Carlo simulation for the calculation of aggregate losses, burning cost analysis, and more.

Effective Statistical Learning Methods for Actuaries I

Effective Statistical Learning Methods for Actuaries I

GLMs and Extensions

  • Author: Michel Denuit,Donatien Hainaut,Julien Trufin
  • Publisher: Springer Nature
  • ISBN: 3030258203
  • Category: Business & Economics
  • Page: 441
  • View: 5635
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This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.

Effective Statistical Learning Methods for Actuaries III

Effective Statistical Learning Methods for Actuaries III

Neural Networks and Extensions

  • Author: Michel Denuit,Donatien Hainaut,Julien Trufin
  • Publisher: Springer Nature
  • ISBN: 3030258270
  • Category: Business & Economics
  • Page: 250
  • View: 6134
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This book reviews some of the most recent developments in neural networks, with a focus on applications in actuarial sciences and finance. It simultaneously introduces the relevant tools for developing and analyzing neural networks, in a style that is mathematically rigorous yet accessible. Artificial intelligence and neural networks offer a powerful alternative to statistical methods for analyzing data. Various topics are covered from feed-forward networks to deep learning, such as Bayesian learning, boosting methods and Long Short Term Memory models. All methods are applied to claims, mortality or time-series forecasting. Requiring only a basic knowledge of statistics, this book is written for masters students in the actuarial sciences and for actuaries wishing to update their skills in machine learning. This is the third of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.

ASTIN Bulletin

ASTIN Bulletin

  • Author: N.A
  • Publisher: N.A
  • ISBN: N.A
  • Category: Insurance
  • Page: N.A
  • View: 314
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Regression Modeling with Actuarial and Financial Applications

Regression Modeling with Actuarial and Financial Applications

  • Author: Edward W. Frees
  • Publisher: Cambridge University Press
  • ISBN: 0521760119
  • Category: Business & Economics
  • Page: 565
  • View: 6093
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This book teaches multiple regression and time series and how to use these to analyze real data in risk management and finance.

Encyclopedia of Actuarial Science: E-N

Encyclopedia of Actuarial Science: E-N

  • Author: Bjørn Sundt
  • Publisher: N.A
  • ISBN: N.A
  • Category: Insurance
  • Page: 1842
  • View: 8755
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Stochastic Claims Reserving Methods in Insurance

Stochastic Claims Reserving Methods in Insurance

  • Author: Mario V. Wüthrich,Michael Merz
  • Publisher: John Wiley & Sons
  • ISBN: 0470772727
  • Category: Business & Economics
  • Page: 438
  • View: 471
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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.

Encyclopedia of quantitative risk analysis and assessment

Encyclopedia of quantitative risk analysis and assessment

  • Author: Edward L. Melnick,Brian Everitt
  • Publisher: John Wiley & Sons Inc
  • ISBN: N.A
  • Category: Mathematical statistics
  • Page: 1954
  • View: 5835
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Statistical Theory and Method Abstracts

Statistical Theory and Method Abstracts

  • Author: N.A
  • Publisher: N.A
  • ISBN: N.A
  • Category: Statistics
  • Page: N.A
  • View: 7165
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