Exploring Functional Patterns of Driving Records by Interacting with Major Classes and Territory Using Generalized Additive Models

Shengkun Xie, Anna Lawniczak, Clare Chua-Chow

2023

Abstract

Studying the safe driver index, such as Driving Records (DR), is essential to auto insurance regulation. Part of the auto insurance regulation aims to estimate the relativity of major risk factors, including DR, to provide some benchmark values for auto insurance companies. The risk relativity estimate of DR is often through either an assessment via empirical loss cost or a statistical modelling approach such as using generalized linear models. However, these methods are only able to give an estimate on an integer level of DR. This work proposes a novel approach to estimating the risk relativity of DR via generalized additive models (GAM). This method makes the integer level of DR continuous, making it more flexible and practical. Extending the generalized linear model to GAM is critical as investigating this new method could enhance applications of advanced statistical methods to the actuarial practice. Thus, making the proposed methodology of analyzing the safe driver index more statistically sound. Furthermore, exploring functional patterns by interacting with major classes or territories allows us to find statistical evidence to justify the existence of correlations between risk factors. This may help address the issue of potential double penalties in insurance pricing and call for a solution to overcome this problem from a statistical perspective.

Paper Citation

in Harvard Style

Xie S., Lawniczak A. and Chua-Chow C. (2023). Exploring Functional Patterns of Driving Records by Interacting with Major Classes and Territory Using Generalized Additive Models. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 271-278. DOI: 10.5220/0012068900003541

in Bibtex Style

@conference{data23,
author={Shengkun Xie and Anna Lawniczak and Clare Chua-Chow},
title={Exploring Functional Patterns of Driving Records by Interacting with Major Classes and Territory Using Generalized Additive Models},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={271-278},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012068900003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Exploring Functional Patterns of Driving Records by Interacting with Major Classes and Territory Using Generalized Additive Models
SN - 978-989-758-664-4
AU - Xie S.
AU - Lawniczak A.
AU - Chua-Chow C.
PY - 2023
SP - 271
EP - 278
DO - 10.5220/0012068900003541
PB - SciTePress