Issue |
ITM Web Conf.
Volume 58, 2024
The 6th IndoMS International Conference on Mathematics and Applications (The 6th IICMA 2023)
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Article Number | 04005 | |
Number of page(s) | 13 | |
Section | Statistics | |
DOI | https://doi.org/10.1051/itmconf/20245804005 | |
Published online | 09 January 2024 |
Measurement Claim Reserving Insurance Contract in Accordance with IFRS 17 using Stochastic State Space Model
Department of Mathematic, Universitas Gadjah Mada, Yogyakarta, DI Yogyakarya, Indonesia
* Corresponding author: adhityaronnie@ugm.ac.id
International Financial Reporting Standard 17 (IFRS 17) is a global accounting standard developed by the International Accounting Standards Board (IASB). It guides the accounting treatment of insurance contracts in financial statements. In IFRS 17, claim reserving is vital for measuring insurance contracts and determining the Contractual Service Margin (CSM). The claim reserving process involves estimating expected claim payouts over the contract’s duration. These estimates are crucial for calculating the liability for incurred claims and determining the CSM, representing unearned profit. Claim data is treated as ordered data by sorting the run-off triangle row-wise, resulting univariate time series with missing values. The state space model provides a framework for modeling time series, assuming system development over time. By taking the log of claim data so that the data is normally distributed, the lognormal state space model, along with Kalman recursion algorithms, can be applied for Incurred but Not Reported (IBNR) projections. The lognormal state space model’s IBNR reserve estimate is more precise and sufficient to compensate loss than the chain ladder method. Furthermore, the performance of the lognormal state space model outperforms the chain ladder method by means of model validation using RMSE, MAE, RSE, and R2.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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