Application of the Collective Risk Model to the Number of Claims with a Negative Binomial Distribution and the Size of Claims with a Discrete Uniform Distribution

Syavira Syifausufi, Aulianda Anisa Putri

Abstract


An insurance claim is a form of request from the policy holder to obtain protection against financial losses due to a risk that occurs. Claims that occur every time there is a risk are called individual claims, while the total of individual claims during one insurance period is called aggregate claims. Claims are an important factor in optimizing insurance company expenses, where one of the calculations that insurance companies need to know based on claims is aggregate loss. Aggregate loss is the total loss in a period experienced by policy holders covered by an insurance company. This study aims to determine the average and variance of claims for the number of claims (frequency) with a Negative Binomial distribution and the amount of claims (severity) with a Discreate Uniform distribution in claim payments according to all types of guarantees and the nature of PT injuries. Jasa Raharja (Persero) Purwakarta Representative during the 2018-2020 period. This research uses a collective risk model and the help of Easyfit software to determine the best distribution for the number and size of claims. The results of the research show that from the recapitulation data of claim payments according to all types of coverage and nature of injury in PT. Jasa Raharja (Persero) Purwakarta Representative during the 2018-2020 period, with the number of claims having a Negative Binomial distribution and the amount of claims having a Discrete Uniform distribution, the average aggregate claim occurrence was IDR  with a variance of IDR  during the 2018-2020 insurance period.


Keywords


Negative binomial distribution, discrete uniform distribution, aggregate loss claims model, collective risk model

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References


Bruno, M. G., Camerini, E., Manna, A., & Tomassetti, A. (2006). A new method for evaluating the distribution of aggregate claims. Applied mathematics and computation, 176(2), 488-505.

Espinoza, E., Saputri, U., Fadilah, F. H., & Devianto, D. (2021, June). Modeling the count data of public health service visits with overdispersion problem by using negative binomial regression. In Journal of Physics: Conference Series (Vol. 1940, No. 1, p. 012021). IOP Publishing.

Godfrey, J. S. (1996). The effect of the Indonesian throughflow on ocean circulation and heat exchange with the atmosphere: A review. Journal of Geophysical Research: Oceans, 101(C5), 12217-12237.

Jorion, P. (1997). In defense of VaR. Derivatives Strategy, 2(4), 20-23.

Kartikasari, M., D. (2017). Premium Pricing of Liability Insurance Using Random Sum Model, 17(1), 46-54.

Pak, R. J. (2014). Estimating loss severity distribution convolution approach. J. Math. Statist, 10(3), 247-254.

Saputra, A., & Rusyaman, E. (2018, March). Risk adjustment model of credit life insurance using a genetic algorithm. In IOP Conference Series: Materials Science and Engineering (Vol. 332, No. 1, p. 012007). IOP Publishing.

Sukono, S. S., Mamat, M., & Bon, A. T. (2020, August). Model for determining natural disaster insurance premiums in indonesia using the black scholes method. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Detroit, Michigan, USA.




DOI: https://doi.org/10.47194/ijgor.v5i2.303

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