Publication:
FORECASTING MODELS FOR FIRST YEAR PREMIUM OF LIFE INSURANCE

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Abstract

The objective of this research is to study forecasting models for the first year premium of life insurance. The premium data are gathered from the Office of Insurance Commission (OIC) during January 2003 to November, 2021. The data are divided into 2 sets. The first set from January, 2003 to December 2020 is used for constructing and selection the forecasting models. The second one from January 2021 to November 2021 is used for computing the accuracy of the forecasting model. The forecasting models are chosen by considering the minimum Root Mean Square Error (RMSE). The Mean Absolute Percentage Error (MAPE) is used to measure the accuracy of the model. The results showed that the multiplicative model with initial values from 18 years Decomposition method give the appropriate model for the first year premium of life insurance and yields the MAPE = 17.29%

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ANN, Box-Jenkins method, Forecasting, Holt-Winters method, Ordinary Life Insurance

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Proceedings European Council for Modelling and Simulation Ecms, 2022-May, 90-95, 2022

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