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      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Actuaria
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      Penentuan Retensi pada Reasuransi Stop Loss dengan Metode Optimasi Tail Value at Risk

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      Date
      2024
      Author
      Arum, Afrilia Nindya
      Setiawaty, Berlian
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      Abstract
      Perusahaan asuransi mengelola risiko dengan cara membagi risiko yang tidak dapat mereka tanggung kepada perusahaan asuransi lain yang dikenal sebagai reasuransi. Batas maksimum dari uang pertanggungan yang dapat ditanggung oleh perusahaan asuransi atas suatu risiko tertentu disebut dengan retensi. Penelitian kali ini bertujuan memperoleh retensi dan premi reasuransi pada reasuransi stop loss yang meminimumkan Tail Value at Risk (TVaR), serta menganalisis pengaruh safety loading factor terhadap retensi dan premi reasuransi. Data yang digunakan dalam penelitian ini merupakan data total besar klaim produk asuransi jiwa per bulan di suatu perusahaan asuransi jiwa pada rentang bulan Desember 2022 – Desember 2023. Sebaran yang paling sesuai untuk data total besar klaim pada penelitian ini menggunakan maximum likelihood estimator adalah log-normal (20.9693, 1.4955). Nilai minimum TVaR bergantung pada besarnya tingkat kepercayaan dan safety loading factor yang ditetapkan oleh perusahaan. Semakin tinggi nilai safety loading factor, nilai retensi dan minimum risiko TVaR juga akan semakin tinggi, tetapi premi reasuransi akan semakin rendah.
       
      Insurance companies manage risk by distributing or transferring risks they cannot bear themselves to other insurance companies, known as reinsurance. The maximum limit of the sum insured that can an insurance company cover for a specific risk is called retention. This study aims to determine the retention and reinsurance premium in stop loss reinsurance that minimizes the Tail Value at Risk (TVaR), as well as to analyze the impact of the safety loading factor on retention and reinsurance premiums. The data used in this study is secondary data on large claims for traditional life insurance products at a life insurance company in 2023. The most suitable distribution for the large claim data in this study using maximum likelihood estimator is log-normal (20.9693, 1.4955). The minimum TVaR value depends on the confidence level and safety loading factor established by the company. The higher the safety loading factor, the higher the retention value and the minimum TVaR risk, but the lower the reinsurance premium.
       
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      http://repository.ipb.ac.id/handle/123456789/157865
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      • UT - Actuaria [205]

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      Copyright © 2020 Library of IPB University
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      Indonesia DSpace Group 
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