On the ordering of credibility factors

Ahn, Jae Youn; Jeong, Himchan; Lu, Yang

doi:10.1016/j.insmatheco.2021.10.005

Cited by 7 publications

(1 citation statement)

References 22 publications

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“…Furthermore, Landsman andMakov (1998, 1999) extended the results on the exponential family to the exponential dispersion family. The following key references are related to new developments in credibility estimation: Makov et al (1996), Christiansen and Schinzinger (2016), Tsai and Lin (2017), Gong et al (2018), Xacur and Garrido (2018), Tsai and Wu (2020), Tsai and Zhang (2019), Pitselis (2020, 2021), Youn et al (2021), Wang et al (2021), Yan and Song (2022), and Kim et al (2022).…”

Section: Related Workmentioning

confidence: 99%

Credibility Distribution Estimation with Weighted or Grouped Observations

Pitselis

2024

Risks

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In non-life insurance practice, actuaries are often faced with the challenge of predicting the number of claims and claim amounts to be incurred at any given time, which serve to implement fair pricing and reserves given the nature of the risk. This paper extends Jewell’s credible distribution in terms of forecasting the distribution of individual risk in cases where the observations are weighted or are grouped in intervals. More specifically, we show how empirical distribution functions can be embedded within Bühlmann’s and Straub’s credibility model. The optimal projection theorem is applied for credibility estimation and more insight into the derivation of the credibility distribution estimators is also provided. In addition, distribution credibility estimators are established and numerical illustrations are presented herein. Two examples of distribution credibility estimation are given, one with insurance loss data and the other with industry financial data.

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