| Title of Article |
Bayesian Bonus-Malus Premium with Poisson-Lindley Distributed Claim Frequency and Lognormal-Gamma Distributed Claim Severity in Automobile Insurance |
| Date of Acceptance |
7 September 2020 |
| Journal |
| Title of Journal |
WSEAS Transactions on Mathematics |
| Standard |
SCOPUS |
| Institute of Journal |
World Scientific and Engineering Academy and Society |
| ISBN/ISSN |
2224-2880 |
| Volume |
|
| Issue |
|
| Month |
|
| Year of Publication |
2021 |
| Page |
443-451 |
| Abstract |
The traditional automobile insurance bonus-malus system (BMS) merit-rating depends on the number of claims. An insured individual who makes a small severity claim is penalized unfairly compared to an insured person who makes a large severity claim. A model for assigning the bonus-malus premium was
proposed. Consideration was based on both the number and size of the claims that were assumed to follow a Poisson-Lindley distribution and a Lognormal-Gamma distribution, respectively. The Bayesian method was applied to compute the bonus-malus premiums,
integrated by both frequency and severity components based on
the posterior criteria. Practical examples using a real data set are provided. This approach offers a fairer method of penalizing all policyholders in the portfolio. |
| Keyword |
Automobile insurance, Bayesian method, Bonus-malus system, Claim severity, Number of claims, Poisson-Lindley distribution, Lognormal-Gamma distribution |
| Author |
|
| Reviewing Status |
มีผู้ประเมินอิสระ |
| Status |
ตีพิมพ์แล้ว |
| Level of Publication |
นานาชาติ |
| citation |
false |
| Part of thesis |
true |
| Attach file |
|
| Citation |
0
|
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Publication
Journal Publication
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