Comparison of general insurance claims reserving methods in Malaysia: Basic Chain Ladder method vs. Over-dispersed Poisson model

The adoption of stochastic claims reserving methods has become increasingly prevalent in the General Insurance (“GI”) business to quantify uncertainty. The research study will compare two methodologies: the Basic Chain Ladder (“BCL”) method, which is a deterministic approach, and the Over-Dispersed Poisson (“ODP”) model, which is a stochastic approach. These methodologies provide varying levels of accuracy in estimating claims reserves. Nonetheless, the absence of a thorough and comparative examination regarding implementing these methods within Malaysia’s GI sector, encompassing both conventional and Takaful insurance, provide a clear understanding of which model is suitable for distinct operational contexts and objectives within the compliance framework of GI companies. With a data analysis between a general conventional insurer and a general Takaful operator in Malaysia, the study has found that the hypotheses tested in this study have significant differences. Both methods can easily approach the prediction reserves. However, the ODP model provides statistical information, for example, prediction error (also known as root mean square error, which is also discussed in this research), an advantage the BCL does not have. This research will give decision-makers the information to make educated choices in selecting claim reserves prediction methods.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-31
DOI
https://doi.org/10.5281/zenodo.14928661
Primary Topic
Probability and Risk Models
Type
article
Field-Weighted Citation Impact
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article

Comparison of general insurance claims reserving methods in Malaysia: Basic Chain Ladder method vs. Over-dispersed Poisson model

Zenodo (CERN European Organization for Nuclear Research)
Probability and Risk Models
article

Comparison of general insurance claims reserving methods in Malaysia: Basic Chain Ladder method vs. Over-dispersed Poisson model

article en

Abstract

The adoption of stochastic claims reserving methods has become increasingly prevalent in the General Insurance (“GI”) business to quantify uncertainty. The research study will compare two methodologies: the Basic Chain Ladder (“BCL”) method, which is a deterministic approach, and the Over-Dispersed Poisson (“ODP”) model, which is a stochastic approach. These methodologies provide varying levels of accuracy in estimating claims reserves. Nonetheless, the absence of a thorough and comparative examination regarding implementing these methods within Malaysia’s GI sector, encompassing both conventional and Takaful insurance, provide a clear understanding of which model is suitable for distinct operational contexts and objectives within the compliance framework of GI companies. With a data analysis between a general conventional insurer and a general Takaful operator in Malaysia, the study has found that the hypotheses tested in this study have significant differences. Both methods can easily approach the prediction reserves. However, the ODP model provides statistical information, for example, prediction error (also known as root mean square error, which is also discussed in this research), an advantage the BCL does not have. This research will give decision-makers the information to make educated choices in selecting claim reserves prediction methods.

Zenodo (CERN European Organization for Nuclear Research)
Asia Pacific University of Technology & Innovation (MY), Quest International University Perak (MY)
Openalex Percentile: Top 49%
Probability and Risk Models
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