Special Issue "Credibility Theory: New Developments and Applications"
A special issue of Risks (ISSN 2227-9091).
Deadline for manuscript submissions: 31 May 2018
Prof. Dr. Emilio Gómez Déniz
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
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Risks is an international peer-reviewed open access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Claims and Loss Distribution
- Non-Life Insurance
- Risk Measure.
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Multivariate Credibility in Bonus-Malus Systems. Applications with Emphasis in Regression and Premiums
Author: E. Gomez–Deniz a and E. Calderın–Ojeda b
Affiliations: a Department of Quantitative Methods in Economics and TiDES Institute, University of Las Palmas de Gran Canaria, 35017-Las Palmas de G.C., Spain
b Centre for Actuarial Studies, Department of Economics, University of Melbourne, Australia
Abstract: In the classical bonus-malus system the premium assigned to each pol- icyholder 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 ex- tent 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 trivari- ate discrete distribution. This approach allows us to discern between three types of claims depending wether the claims are above, between or below a 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 sat- isfy appropriate traditional transition rules. Two generalized linear models are derived for the basic and mixture models respectively. A practical example based on real data is shown to examine the differ- ences of the factors that affect to the three types of claims by using these generalized linear models.
Keywords: Bayesian, Bonus-Malus System, Claim, Claim Size, Conjugate Distribution, Regression.
Mathematics Subject Classification (2010): 62-07, 62P05, 62E99