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All Journal Epsilon: Jurnal Matematika Murni dan Terapan
Nadya Pratiwi
Program Studi Matematika Fakultas MIPA Universitas Lambung Mangkurat
Decision Sciences, Operations Research & Management Transportation

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Journal : Epsilon: Jurnal Matematika Murni dan Terapan

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PERHITUNGAN UKURAN RISIKO UNTUK MODEL KERUGIAN AGREGAT Nadya Pratiwi; Aprida Siska Lestia; Nur Salam
EPSILON: JURNAL MATEMATIKA MURNI DAN TERAPAN Vol 14, No 1 (2020): JURNAL EPSILON VOLUME 14 NOMOR 1
Publisher : Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (291.189 KB) | DOI: 10.20527/epsilon.v14i1.2200

Abstract

In the case of nonlife insurance, insurance companies are very potential to get losses if claims submitted by customers (policyholders) exceeds the reserves of budgeted claims. It is the risk that have to managed properly by insurance companies . One possible disadvantage is the aggregate loss model. The aggregate loss model is a random variable that states the total of all losses incurred in an insurance policy block. This kind of loss can be modeled using a collective risk approach where the number of claims is a discrete random variable and the size of claim is a continuous random variable. The purpose of this study is to determine risk measure of standard deviation premium principle, value at risk (VaR), and conditional tail expectation (CTE) of the aggregate loss model. Standard deviation premium principle risk measure of aggregate loss model is determined analytically by substituted it expected value and varians. Meanwhile, VaR risk measure is determined using numerical method by Monte Carlo method, then the quantile value and it confidence interval for the actual value will estimate. In the CTE calculation, based on the loss data obtained in the Monte Carlo method, the CTE value is estimated by calculating the average loss that exceeds the VaR value. If the data size is large enough, the CTE value estimation will converge to the actual value.Keywords: Aggregate Loss Model, Standard Deviation Premium Principle, Value at Risk (VaR), Conditional Tail Expectation (CTE).
Co-Authors Lestia, Aprida Siska Nur Salam