TY - GEN
T1 - Forecasting Premium Adequacy to Claim Paid Ratio in Life Insurance Industry with COVID-19 Effect using Multilayer Perceptron Neural Network
AU - Ulyah, Siti Maghfirotul
AU - Rifada, Marisa
AU - Ana, Elly
AU - Andreas, Christopher
AU - Rahmayanti, Ilma Amira
AU - Apsariny, Salsabylla Nada
N1 - Publisher Copyright:
© 2022 American Institute of Physics Inc.. All rights reserved.
PY - 2022/10/11
Y1 - 2022/10/11
N2 - The Covid-19 pandemic has had a significant impact on the global economic system, including the insurance industry. In Indonesia, the performance of the life insurance industry experienced negative growth during 2020. Moreover, claim payments up to September 2020, particularly for life insurance products, have increased compared to the last year period. Maintaining the adequacy ratio of premiums to claim payments is very important to do to avoid the risk of failure to meet obligations (default) and maintain the sustainability of the insurance industry. Therefore, this study aims to predict the ratio of premium adequacy to payment of claims in the insurance industry in Indonesia with the effect of the COVID-19 pandemic. The method used in this study is the Artificial Neural Network multilayer perceptron. The fitted model has two hidden layers with lag 1 up to 3 and a dummy variable of COVID-19. The results show that the model fits the ratio data with an out-of-sample MSE of 0.027.
AB - The Covid-19 pandemic has had a significant impact on the global economic system, including the insurance industry. In Indonesia, the performance of the life insurance industry experienced negative growth during 2020. Moreover, claim payments up to September 2020, particularly for life insurance products, have increased compared to the last year period. Maintaining the adequacy ratio of premiums to claim payments is very important to do to avoid the risk of failure to meet obligations (default) and maintain the sustainability of the insurance industry. Therefore, this study aims to predict the ratio of premium adequacy to payment of claims in the insurance industry in Indonesia with the effect of the COVID-19 pandemic. The method used in this study is the Artificial Neural Network multilayer perceptron. The fitted model has two hidden layers with lag 1 up to 3 and a dummy variable of COVID-19. The results show that the model fits the ratio data with an out-of-sample MSE of 0.027.
UR - http://www.scopus.com/inward/record.url?scp=85140209639&partnerID=8YFLogxK
U2 - 10.1063/5.0111946
DO - 10.1063/5.0111946
M3 - Conference contribution
AN - SCOPUS:85140209639
T3 - AIP Conference Proceedings
BT - 3rd International Conference on Mathematics and Sciences, ICMSc 2021
A2 - Nugroho, Rudy Agung
A2 - Allo, Veliyana Londong
A2 - Siringoringo, Meiliyani
A2 - Prangga, Surya
A2 - Wahidah, null
A2 - Munir, Rahmiati
A2 - Hiyahara, Irfan Ashari
PB - American Institute of Physics Inc.
T2 - 3rd International Conference on Mathematics and Sciences 2021: A Brighter Future with Tropical Innovation in the Application of Industry 4.0, ICMSc 2021
Y2 - 12 October 2021 through 13 October 2021
ER -