Credibility Theory: New Developments and Applications

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (31 May 2018) | Viewed by 3453

Special Issue Editor

Department of Quantitative Methods and TIDES Institute, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas, Spain
Interests: distributions theory; Bayesian statistics; robustness; Bayesian applications in economics (actuarial, credibility, ruin theory)
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Special Issue Information

Dear Colleagues,

Credibility theory is a powerful statistical tool used in the actuarial sciences to accurately predict uncertain future events by using the classical and Bayesian approach. This methodology, apart from including a huge variety of attractive and nicely formulated mathematical structure (i.e. models are derive from different approaches, classical and Bayesian statistics, functional analysis -Hilbert spaces- of the classical regression -least squares method-, etc.), its implementation is straightforward. Its major field of application, although not limited to, is the calculation of insurance premiums (mainly in the automobile sector), bonus-malus systems, reinsurance, operational risks, etc. The main objective is to jointly use two fundamental sources of information, individual and collective information (insurance portfolio, which has a heterogeneous character) with the goal of computing a fair insurance rate. In recent years, mainly due to computer advances, classic and Bayesian regression models have also played a prominent role in this discipline.

This Special Issue is open to both original research articles and review articles within the area of credibility theory.

Prof. Dr. Emilio Gómez Déniz
Guest Editor

Manuscript Submission Information

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Keywords

  • Bayesian
  • Bonus-Malus
  • Claims and Loss Distribution
  • Non-Life Insurance
  • Premium
  • Reinsurance
  • Risk Measure.

Published Papers (1 paper)

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Research

11 pages, 319 KiB  
Article
Multivariate Credibility in Bonus-Malus Systems Distinguishing between Different Types of Claims
Risks 2018, 6(2), 34; https://doi.org/10.3390/risks6020034 - 11 Apr 2018
Cited by 12 | Viewed by 2764
Abstract
In the classical bonus-malus system the premium assigned to each policyholder is based only on the number of claims made without having into account the claims size. Thus, a policyholder who has declared a claim that results in a relatively small loss is [...] Read more.
In the classical bonus-malus system the premium assigned to each policyholder is based only on the number of claims made without having into account the claims size. Thus, a policyholder who has declared a claim that results in a relatively small loss is penalised to the same extent as one who has declared a more expensive claim. Of course, this is seen unfair by many policyholders. In this paper, we study the factors that affect the number of claims in car insurance by using a trivariate discrete distribution. This approach allows us to discern between three types of claims depending wether the claims are above, between or below certain thresholds. Therefore, this model implements the two fundamental random variables in this scenario, the number of claims as well as the amount associated with them. In addition, we introduce a trivariate prior distribution conjugated with this discrete distribution that produce credibility bonus-malus premiums that satisfy appropriate traditional transition rules. A practical example based on real data is shown to examine the differences with respect to the premiums obtained under the traditional system of tarification. Full article
(This article belongs to the Special Issue Credibility Theory: New Developments and Applications)
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