Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves

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Bibliographic Information
Journal Journal of Asian Multicultural Research for Economy and Management Study
Title Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves
Author(s) Suwandani, Ria Novita, Yogo Purwono
Volume 2
Issue 1
Year 2021
Pages 38-48
DOI 10.47616/jamrems.v2i1.77
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Keywords Claims Reserves, Gaussian Process Regression, Motor Vehicle Insurance
Chicago 16th Suwandani, Ria Novita, Yogo Purwono. "Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves." Journal of Asian Multicultural Research for Economy and Management Study 2, no. 1 (2021).
APA 6th Suwandani, R. N., Purwono, Y. (2021). Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves. Journal of Asian Multicultural Research for Economy and Management Study, 2(1).
MHRA Suwandani, Ria Novita, Yogo Purwono. 2021. 'Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves', Journal of Asian Multicultural Research for Economy and Management Study, 2.
MLA Suwandani, Ria Novita, Yogo Purwono. "Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves." Journal of Asian Multicultural Research for Economy and Management Study 2.1 (2021). Print.
Harvard SUWANDANI, R. N., PURWONO, Y. 2021. Implementation of Gaussian Process Regression in Estimating Motor Vehicle Insurance Claims Reserves. Journal of Asian Multicultural Research for Economy and Management Study, 2.

Abstract

This study aims to calculate the allowance for losses by applying Gaussian Process regression to estimate future claims. Modeling is done on motor vehicle insurance data. The data used in this study are historical data on PT XYZ's motor vehicle insurance business line during 2017 and 2019 (January 2017 to December 2019). Data analysis will be carried out on the 2017 - 2019 data to obtain an estimate of the claim reserves in the following year, namely 2018 - 2020. This study uses the Chain Ladder method which is the most popular loss reserving method in theory and practice. The estimation results show that the Gaussian Process Regression method is very flexible and can be applied without much adjustment. These results were also compared with the Chain Ladder method. Estimated claim reserves for PT XYZ's motor vehicle business line using the chain-ladder method, the company must provide funds for 2017 of 8,997,979,222 IDR in 2018 16,194,503,605 IDR in 2019 amounting to Rp. 1,719,764,520 for backup. Meanwhile, by using the Bayessian Gaussian Process method, the company must provide funds for 2017 of 9,060,965,077 IDR in 2018 amounting to 16,307,865,130 IDR, and in 2019 1,731,802,871 IDR for backup. The more conservative Bayessian Gaussian Process method. Motor vehicle insurance data has a short development time (claims occur) so that it is included in the short-tail type of business.

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