Actuarial Modelling of Claim Counts: Risk Classification, Credibility and Bonus-Malus Systems (Hardcover)

by Michel Denuit (Author), Xavier Marechal (Author), Sandra Pitrebois (Author), Jean-Francois Walhin (Author)
Key Phrases: annual claim frequency, special bonus rule, expected claim frequency, Negative Binomial, Actuarial Modelling of Claim Counts, Poisson-Inverse Gaussian (more...)

Editorial Reviews

Product Description
There are a wide range of variables for actuaries to consider when calculating a motorist’s insurance premium, such as age, gender and type of vehicle. Further to these factors, motorists’ rates are subject to experience rating systems, including credibility mechanisms and Bonus Malus systems (BMSs).

Actuarial Modelling of Claim Counts presents a comprehensive treatment of the various experience rating systems and their relationships with risk classification. The authors summarize the most recent developments in the field, presenting ratemaking systems, whilst taking into account exogenous information.

The text:

• Offers the first self-contained, practical approach to a priori and a posteriori ratemaking in motor insurance.
• Discusses the issues of claim frequency and claim severity, multi-event systems, and the combinations of deductibles and BMSs.
• Introduces recent developments in actuarial science and exploits the generalised linear model and generalised linear mixed model to achieve risk classification.
• Presents credibility mechanisms as refinements of commercial BMSs.
• Provides practical applications with real data sets processed with SAS software.

Actuarial Modelling of Claim Counts is essential reading for students in actuarial science, as well as practicing and academic actuaries. It is also ideally suited for professionals involved in the insurance industry, applied mathematicians, quantitative economists, financial engineers and statisticians.

From the Back Cover
Michel Denuit – Institut de Statistique, Université Catholique de Louvain, Belgium

Xavier Maréchal – Reacfin, Spin-off of the Université Catholique de Louvain, Belgium

Sandra Pitrebois – Secura, Belgium

Jean-François Walhin – Fortis, Belgium

There are a wide range of variables for actuaries to consider when calculating a motorist’s insurance premium, such as age, gender and type of vehicle. Further to these factors, motorists’ rates are subject to experience rating systems, including credibility mechanisms and Bonus Malus systems (BMSs).

Actuarial Modelling of Claim Counts presents a comprehensive treatment of the various experience rating systems and their relationships with risk classification. The authors summarize the most recent developments in the field, presenting ratemaking systems, whilst taking into account exogenous information.

The text:

• Offers the first self-contained, practical approach to a priori and a posteriori ratemaking in motor insurance.
• Discusses the issues of claim frequency and claim severity, multi-event systems, and the combinations of deductibles and BMSs.
• Introduces recent developments in actuarial science and exploits the generalised linear model and generalised linear mixed model to achieve risk classification.
• Presents credibility mechanisms as refinements of commercial BMSs.
• Provides practical applications with real data sets processed with SAS software.

Actuarial Modelling of Claim Counts is essential reading for students in actuarial science, as well as practicing and academic actuaries. It is also ideally suited for professionals involved in the insurance industry, applied mathematicians, quantitative economists, financial engineers and statisticians.

See all Editorial Reviews

Product Details

• Hardcover: 384 pages
• Publisher: Wiley-Interscience (October 8, 2007)
• Language: English
• ISBN-10: 0470026774
• ISBN-13: 978-0470026779
• Product Dimensions: 9.7 x 6.8 x 1.1 inches
• Shipping Weight: 1.9 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars See all reviews (1 customer review)
• Amazon.com Sales Rank: #1,334,042 in Books (See Bestsellers in Books)

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Customer Reviews

Most Helpful Customer Reviews

1 of 1 people found the following review helpful:

5.0 out of 5 stars An excellent book for actuarial researchers, October 8, 2008

By	Genevieve Hayes (Australia) - See all my reviews (REAL NAME)

First a warning, if you are a student studying to become an actuary, then this book is not for you. I am a lecturer in actuarial studies at an Australian university who teaches students from first year up to Masters level, and most of the content of this book would be way over the heads of my students. Furthermore, I don't even think this book was designed to be used for teaching, as there are no exercises at the end of each chapter, as you would expect in such a book. However, for anyone interested in conducting research into any areas of actuarial science (particularly in general or non-life insurance), then this book is a must.

"Actuarial Modelling of Claim Counts" provides a detailed, yet easy to follow, summary of three major areas in insurance: the modelling of claim counts (including over-dispersion models); experience rating using credibility models; and bonus-malus systems. All concepts are described both using statistical theory and using practical numerical examples, and numerous references are given throughout to allow readers to pursue any of these ideas further if they so desire. If you were conducting research into one of these areas, then it probably would be necessary to look up many of the references given, since there is a limit to the amount of information that can be included in a 356 page book. Nevertheless, the information given is thorough enough so that, if you do need to do further research, then you won't be going into it blind, but armed with a high level understanding of the main points involved. I have just finished a PhD on a topic which included the modelling of claim counts and I wish that I had discovered this book sooner, since this book would have made my research a whole lot easier. I cannot recommend this book enough.