Prediction of Motor Vehicle Insurance Claims Using ARIMA-GARCH Models

https://doi.org/10.47194/orics.v5i3.331

Authors

  • Dwi Susanti
  • Nisrina Salsabila Maraya
  • sukono sukono
  • Jumadil Saputra Faculty of Business, Economics and Social Development, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia

Keywords:

Prediction, insurance claim, motor vehicle, ARIMA-GARCH

Abstract

Motorized vehicles are one of the means of transportation used by Indonesian people. As of 2021, the Central Statistics Agency (CSA) recorded the growth of motorized vehicles in Indonesia reaching 141,992,573 vehicles. Lack of control over the number of motorized vehicles results in losses for various parties, such as accidents, damage and other unwanted losses. The size of insurance claims has the potential to fluctuate, because it is influenced by several factors, such as policy changes, market conditions and economic conditions. This research aims to predict the size of motor vehicle insurance claims using the ARIMA-GARCH model which is used to predict the size of vehicle insurance claims by dealing with non-stationarity and heteroscedasticity in time series data. Based on research, the best model obtained is the ARIMA (2,1,3) - GARCH (1,0) model which produces seven significant parameters. Meanwhile, based on the MAPE value, it shows that the ARIMA (2,1,3)-GARCH (1,0) model is quite accurate. The results of this research can be taken into consideration in predicting the size of insurance claims in the future.

References

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Published

2024-09-29

How to Cite

Susanti, D., Maraya, N. S., sukono, sukono, & Saputra, J. (2024). Prediction of Motor Vehicle Insurance Claims Using ARIMA-GARCH Models. Operations Research: International Conference Series, 5(3), 86–92. https://doi.org/10.47194/orics.v5i3.331

Issue

Vol. 5 No. 3 (2024): Operations Research International Conference Series (ORICS), September 2024

Section

Articles
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