Statistical Methods in Insurance and Actuarial Science

Statistical Methods in Insurance and Actuarial Science

by Philip J. Boland
     
 

ISBN-10: 1584886951

ISBN-13: 9781584886952

Pub. Date: 01/15/2007

Publisher: Taylor & Francis

Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science,
and finance. The book builds on students' existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods.…  See more details below

Overview

Statistical and Probabilistic Methods in Actuarial Science covers many of the diverse methods in applied probability and statistics for students aspiring to careers in insurance, actuarial science,
and finance. The book builds on students' existing knowledge of probability and statistics by establishing a solid and thorough understanding of these methods. It also emphasizes the wide variety of practical situations in insurance and actuarial science where these techniques may be used.

Although some chapters are linked, several can be studied independently from the others. The first chapter introduces claims reserving via the deterministic chain ladder technique. The next few chapters survey loss distributions, risk models in a fixed period of time, and surplus processes, followed by an examination of credibility theory in which collateral and sample information are brought together to provide reasonable methods of estimation. In the subsequent chapter, experience rating via no claim discount schemes for motor insurance provides an interesting application of
Markov chain methods. The final chapters discuss generalized linear models and decision and game theory.

Developed by an author with many years of teaching experience, this text presents an accessible, sound foundation in both the theory and applications of actuarial science. It encourages students to use the statistical software package R to check examples and solve problems.

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Product Details

ISBN-13:
9781584886952
Publisher:
Taylor & Francis
Publication date:
01/15/2007
Series:
Chapman & Hall/CRC Interdisciplinary Statistics Series
Edition description:
New Edition
Pages:
368
Product dimensions:
6.10(w) x 9.30(h) x 1.00(d)

Related Subjects

Table of Contents

PREFACE
INTRODUCTION
Claims Reserving and Pricing with Run-Off Triangles
The Evolving Nature of Claims and Reserves
Chain Ladder Methods
The Average Cost per Claim Method
The Bornhuetter-Ferguson or Loss Ratio Method
An Example in Pricing Products
Statistical Modeling and the Separation Technique
Problems
Loss Distributions
Introduction to Loss Distributions
Classical Loss Distributions
Fitting Loss Distributions
Mixture Distributions
Loss Distributions and Reinsurance
Problems
Risk Theory
Risk Models for Aggregate Claims
Collective Risk Models
Individual Risk Models for S
Premiums and Reserves for Aggregate Claims
Reinsurance for Aggregate Claims
Problems
Ruin Theory
The Probability of Ruin in a Surplus Process
Surplus and Aggregate Claims Processes
Probability of Ruin and the Adjustment Coefficient
Reinsurance and the Probability of Ruin
Problems
Credibility Theory
Introduction to Credibility Estimates
Classical Credibility Theory
The Bayesian Approach to Credibility Theory
Greatest Accuracy Credibility Theory
Empirical Bayes Approach to Credibility Theory
Problems
No Claim Discounting in Motor Insurance
Introduction to No Claim Discount Schemes
Transition in a No Claim Discount System
Propensity to Make a Claim in NCD Schemes
Reducing Heterogeneity with NCD Schemes
Problems
Generalized Linear Models
Introduction to Linear and Generalized Linear Models
Multiple Linear Regression and the Normal Model
The Structure of Generalized Linear Models
Model Selection and Deviance
Problems
Decision and Game Theory
Introduction
Game Theory
Decision making and Risk
Utility and Expected Monetary Gain
Problems
References
Appendix A: Basic Probability Distributions

Appendix B: Some Basic Tools in Probability and Statistics
Moment Generating Functions
Convolutions of Random Variables
Conditional Probability and Distributions
Maximum Likelihood Estimation
Appendix C: An Introduction to Bayesian Statistics
Bayesian Statistics
Appendix D: Answers to Selected Problems
Claims Reserving and Pricing with Run-Off Triangles
Loss Distributions
Risk Theory
Ruin Theory
Credibility Theory
No Claim Discounting in Motor Insurance
Generalized Linear Models
Decision and Game Theory

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