Actuarial Modelling of Claim Counts: Risk Classification, Credibility and Bonus-Malus SystemsJohn Wiley & Sons, 27 juil. 2007 - 384 pages 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:
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. |
Table des matières
| 1 | |
| 3 | |
2 Risk Classification | 49 |
Part II Basics of Experience Rating | 119 |
3 Credibility Models for Claim Counts | 121 |
4 BonusMalus Scales | 165 |
Part III Advances in Experience Rating | 217 |
5 Efficiency and Bonus Hunger | 219 |
6 MultiEvent Systems | 259 |
7 BonusMalus Systems with Varying Deductibles | 277 |
8 Transient Maximum Accuracy Criterion | 293 |
9 Actuarial Analysis of the French BonusMalus System | 325 |
| 345 | |
| 355 | |
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Expressions et termes fréquents
actuarial Age∗Power Ageph Agev algorithm annual claim frequency annual expected claim assume average bad driver Binomial distribution bonus rule bonus-malus scale bonus-malus system chapter claim amount claim costs claim numbers claim-free claims reported claims with bodily computed covariates credibility models deductible denoted Denuit distribution function expected claim frequency explanatory variables exponential loss function Gamma Gamma distribution Gender Gender∗Age given heterogeneity independent initial distribution large claims level occupied linear log-likelihood LogNormal loss function malus matrix maximum likelihood estimator mean mixed Poisson Negative Binomial Negative Binomial distribution number of claims obtained overdispersion p-value Panjer Pareto distribution Poisson distribution Poisson model Poisson process Poisson regression Poisson-Inverse Gaussian policyholder portfolio posteriori corrections Pr>Chi-sq Premium split priori ratemaking probability density function probability generating function probability mass function pure premium random effect random variables regression coefficients regression model risk classification special bonus rule Table values variance Walhin
Références à ce livre
Modern Actuarial Risk Theory: Using R Rob Kaas,Marc Goovaerts,Jan Dhaene,Michel Denuit Aperçu limité - 2008 |
