Implementation of a Quantile Regression Model for the Loss Reserve of Vehicle Insurance Company XYZ

DOI

10.2991/icbmr-18.2019.38How to use a DOI?

Keywords

claim reserve, vehicle insurance, quantile regression, claim model

Abstract

The issue of claim reserves on insurance companies is one that insurance businesses need to cope with. The availability of such reserves within a company is fundamental for them to maintain their business activities. They are also required in precise calculations regarding the allocation of funds owned by the company based on the sale of products issued, in order to generate profits. Based on the limitations of the traditional models, this paper intends to introduce an alternative model for estimating claim reserves, called the quantile regression model. According to Chan (2015), the quantile regression model is considered to have the ability to calculate claim reserves against data with heterogeneous variance and with no clear distribution, which is mostly insurance data known for. The main purpose of the research is to attempt to calculate an estimation for claim reserves by adopting the quantile regression model, and to observe whether the model can be applied to the context of the XYZ insurance company in Indonesia. The data used in the research are the claims data of XYZ company for motor vehicle insurance products from 2013 to 2015.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ariandy Dena Putra
AU  - Bona C. Siahaan
PY  - 2019/03
DA  - 2019/03
TI  - Implementation of a Quantile Regression Model for the Loss Reserve of Vehicle Insurance Company XYZ
BT  - Proceedings of the 12th International Conference on Business and Management Research (ICBMR 2018)
PB  - Atlantis Press
SP  - 231
EP  - 235
SN  - 2352-5428
UR  - https://doi.org/10.2991/icbmr-18.2019.38
DO  - 10.2991/icbmr-18.2019.38
ID  - Putra2019/03
ER  -