Quantifying Uncertainty of Insurance Claims Based on Expert Judgments
In Bayesian statistics, prior specification has an important role in determining the quality of posterior estimates. We use expert judgments to quantify uncertain quantities and produce appropriate prior distribution. The aim of this study was to quantify the uncertainty of life insurance claims, es...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/13/2/245 |
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| Summary: | In Bayesian statistics, prior specification has an important role in determining the quality of posterior estimates. We use expert judgments to quantify uncertain quantities and produce appropriate prior distribution. The aim of this study was to quantify the uncertainty of life insurance claims, especially on the policy owner’s age, as it is the main factor determining the insurance premium. A one-day workshop was conducted to elicit expert judgments from those who have experience in accepting claims. Four experts from different insurance companies were involved in the workshop. The elicitation protocol used in this study was The Sheffield Elicitation Framework (SHELF), which produces four different statistical distributions for each expert. A linear pooling method was used to aggregate the distributions to obtain the consensus distribution among experts. The consensus distribution suggested that the majority of policy owners will make a claim at the age of 54 years old. |
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| ISSN: | 2227-7390 |