ScholarGate
Assistent

Sammenlign metoder

Gjennomgå de valgte metodene side om side; rader som avviker, er uthevet.

Kredibilitetsteori×Bonus-Malus-system×
FagfeltAktuarvitenskapAktuarvitenskap
FamilieRegression modelRegression model
Opprinnelsesår19671995
OpphavspersonHans BühlmannJean Lemaire
TypeWeighted linear blend of individual and collective experienceActuarial experience-rating model
Opprinnelig kildeBühlmann, H. (1967). Experience rating and credibility. ASTIN Bulletin, 4(3), 199–207. DOI ↗Lemaire, J. (1995). Bonus-Malus Systems in Automobile Insurance. Kluwer Academic Publishers. ISBN: 978-0-7923-9545-5
AliasBühlmann Credibility, Experience Rating, Linear Credibility Estimator, Güvenilirlik TeorisiNo-Claim Discount System, Merit Rating System, Experience Rating in Automobile Insurance, Prim-Ceza Sistemi
Relaterte32
SammendragCredibility Theory is an actuarial framework for estimating the pure premium of an individual risk by blending its own observed loss experience with the collective (portfolio) mean. Introduced by Hans Bühlmann in 1967, the method derives the optimal linear combination—the credibility-weighted premium—that minimises mean squared error. It extends classical experience rating to a rigorous statistical footing rooted in Bayesian and linear estimation principles.A Bonus-Malus System (BMS) is an actuarial experience-rating mechanism used primarily in automobile insurance to adjust individual policyholders' premiums based on their personal claim history. Policyholders who remain claim-free receive premium discounts (bonus), while those who file claims are penalised with surcharges (malus). The framework was comprehensively formalised and analysed by Jean Lemaire in his landmark 1995 monograph, which remains the definitive reference for the design and evaluation of such systems worldwide.
ScholarGateDatasett
  1. v1
  2. 1 Kilder
  3. PUBLISHED
  1. v1
  2. 1 Kilder
  3. PUBLISHED

Gå til søk Last ned lysbilder

ScholarGateSammenlign metoder: Credibility Theory · Bonus-Malus System. Hentet 2026-06-18 fra https://scholargate.app/no/compare