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Cited by 70Probability and Risk ModelsInsurance and Financial Risk ManagementProbability and Statistical Research

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Statistical concepts of a priori and a posteriori risk classification in insurance

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Antonio, Katrien, Valdez, Emiliano A.·2012·AStA Advances in Statistical Analysis
DOI 10.1007/s10182-011-0152-7
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Abstract

Everyday we face all kinds of risks, and insurance is in the business of providing us a means to transfer or share these risks, usually to eliminate or reduce the resulting financial burden, in exchange for a predetermined price or tariff. Actuaries are considered professional experts in the economic assessment of uncertain events, and equipped with many statistical tools for analytics, they help formulate a fair and reasonable tariff associated with these risks. An important part of the process of establishing fair insurance tariffs is risk classification, which involves the grouping of risks into various classes that share a homogeneous set of characteristics allowing the actuary to reasonably price discriminate. This article is a survey paper on the statistical tools for risk classification used in insurance. Because of recent availability of more complex data in the industry together with the technology to analyze these data, we additionally discuss modern techniques that have recently emerged in the statistics discipline and can be used for risk classification. While several of the illustrations discussed in the paper focus on general, or non-life, insurance, several of the principles we examine can be similarly applied to life insurance. Furthermore, we also distinguish between a priori and a posteriori ratemaking. The former is a process which forms the basis for ratemaking when a policyholder is new and insufficient information may be available. The latter process uses additional historical information about policyholder claims when this becomes available. In effect, the resulting a posteriori premium allows one to correct and adjust the previous a priori premium making the price discrimination even more fair and reasonable.

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References 44 · Cited by 70

Research works printed but not linked: 38

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Metadata

Authors
Antonio, K., & Valdez, E. A.
Affiliations
  • University of Amsterdam (NL)
  • University of Connecticut (US)
Corresponding author
Antonio, Katrien
ORCID
Venue
AStA Advances in Statistical Analysis
Publisher
Springer Science and Business Media LLC
Published
2011-02-02
Volume
96
Issue
2
Pages
187-224
ISSN
  • 1863-8171 (ISSN-L)
  • 1863-818X
DOI
10.1007/s10182-011-0152-7
OpenAlex
W2148290418
Cited by
70
References
44
Citations by year
2026: 3 · 2025: 2 · 2024: 4 · 2023: 5 · 2022: 6 · 2021: 4 · 2020: 5 · 2019: 2 · 2018: 7 · 2017: 3 · 2016: 6 · 2015: 10 · 2014: 7 · 2013: 3 · 2012: 2
FWCI
5.65
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • AStA Advances in Statistical Analysis (publishedVersion, cc-by-nc)
  • UvA-DARE (University of Amsterdam) (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Lirias (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
Funders
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Probability and Risk Models
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Insurance and Financial Risk Management
  • Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
Keywords
risk classification, ratemaking, price discrimination, non-life insurance, life insurance, actuarial science, premium adjustment

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