Penerapan Metode Limited-Fluctuation Credibility dalam Menentukan Premi Murni pada Asuransi Kendaraan Bermotor di PT XYZ

Mira Zakiah Rahmah, Aceng Komarudin Mutaqin

Abstract

Abstract. This paper discusses the method of limited-fluctuation credibility, also known as classic credibility. Credibility theory is a technique for predicting future premium rates based on past experience data. Limited fluctuation credibility consists of two credibility, namely full credibility if Z = 1 and partial credibility if Z <1. Full credibility is achieved if the amount of recent data is sufficient for prediction, whereas if the latest data is insufficient then the partial credibility approach is used. Calculations for full and partial credibility standards are used for loss measures such as frequency of claims, size of claims, aggregate losses and net premiums. The data used in this paper is secondary data recorded by the company PT. XYZ in 2014. This data contains data on the frequency of claims and the size of the policyholder's partial loss claims for motor vehicle insurance products category 4 areas 1. Based on the results of the application, the prediction of pure premiums for 2015 cannot be fully based on insurance data for 2014 because the credibility factor value is less than 1. So based on the limited-fluctuation credibility method, the prediction of pure premiums for 2015 must be based on manual values for pure premiums as well as insurance data for 2014. If manual values for pure premium is 2,000,000 rupiah, then the prediction of pure premium for 2015 is 1,849,342 rupiah.

Keywords: limited fluctuation credibility, full credibility, partial credibility and partial loss

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References

Purwandari, N. Pemodelan Distribusi Exponentiated Inverted Weibull Pada Data Besar Klaim Asuransi Motor Indonesia. Skripsi S1 Jurusan Statistika Universitas Islam Bandung. 2019.

Nazmi, N. Pemodelan Distribusi Binomial Negatif Poisson-Lindley Diboboti Pada Data Frekuensi Klaim Asuransi Kendaraan Bermotor Di Indonesia. Skripsi S1 Jurusan Statistika Universitas Islam Bandung. 2019.

Grize, Y-L. Applications of Statistics in The Field of General Insurance: An Overview. International Statistical Review, 1-21. 2014.

Klugman, S.A., Panjer, H.H., dan Wilmot, G. Loss Models. From Data to Decisions. Willey Interscience. New York. 2012.

Tse, Y-K. Nonlife Actuarial Models: Theory, Methods, and Evaluation. Cambridge University Press. United Kingdom. 2009.

Herzog, T. N. Introduction to Credibility Theory (4th ed.). ACTEX Publications. USA. 2010.

Otoritas Jasa Keuangan. Perasurasian. OJK Jakarta. 2016.

Ayu, D. Penentuan Distribusi Kerugian Agregat Tertanggung Asuransi Kendaraan Bermotor Di Indonesia Menggunakan Metode Rekursif Panjer. Skripsi S1 Jurusan Statistika Universitas Islam Bandung. 2017.

Akritas, M. Probability and Statistics with R For Engineers and Scientists. Pearson Education. USA. 2016.

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