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All Journal Science and Technology Indonesia Emerging Science Journal
Moumeesri, Adisak
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Physics

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Modelling of Claim and Pricing of Motor Insurance Based on Bonus-Malus System Considering the Frequency and Severity of Claims Hengcharoensuk, Jiramet; Phanmai, Konlawat; Moumeesri, Adisak
Science and Technology Indonesia Vol. 9 No. 4 (2024): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2024.9.4.904-913

Abstract

This article proposes new distributions for claim frequency and severity, specifically tailored for a bonus-malus system in automobile insurance. The mixed Poisson with weighted quasi Lindley distribution is recommended for modeling claim frequency, while the mixed exponential with weighted quasi Lindley distribution is suggested for modeling claim severity. To estimate insurance premiums, the Bayesian method is employed, incorporating both frequency and severity distributions. The study validates the proposed models using real data from an Australian insurance company, which includes 67,856 policies. The assessment of model adequacy indicates that the Poisson-weighted quasi Lindley distribution is a suitable fit for modeling claim frequency, while the exponential-weighted quasi Lindley distribution is appropriate for modeling claim severity. Overall, the results suggest that the proposed models offer optimal premium estimations, considering both claim frequency and severity, which can lead to fairer pricing and increased customer appeal during claim occurrences compared to conventional models.
Estimating Ruin Probability in an Insurance Risk Model Using the Wang-PH Transform Through Claim Simulation Ieosanurak, Weenakorn; Moumeesri, Adisak
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-011

Abstract

The accurate estimation of ruin probability is a fundamental challenge in non-life insurance, impacting financial stability, risk management strategies, and operational decisions. This study aims to propose an approach for estimating ruin probability using claim simulation enhanced by the Wang-PH transform to fit various loss distributions, including Gamma, Weibull, Lognormal, Log-logistic, Inverse Weibull, and Inverse Gaussian, to actual claim data. Methods involve the transformation of loss distributions via the Wang-PH transform and rigorous evaluation to select the optimal distribution model that best reflects actual claim characteristics. This model serves as the foundation for estimating finite-time ruin probability through claim simulation, employing the acceptance-rejection technique to generate random samples. Additionally, a regression-based methodology estimates the minimum capital reserve required to safeguard against financial risk. Findings indicate the proposed method's computational efficiency, making it a valuable tool for insurers and risk analysts in assessing and mitigating financial risks in the non-life insurance sector. The novelty of this study lies in the integration of the Wang-PH transform with empirical data fitting and simulation techniques, applied to estimating ruin probability and determining capital reserves. Doi: 10.28991/ESJ-2025-09-01-011 Full Text: PDF
Co-Authors Hengcharoensuk, Jiramet Ieosanurak, Weenakorn Phanmai, Konlawat