AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home International Journal of Crowd Science Article
PDF (818.4 KB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Open Access

Ratemaking Model of Usage Based Insurance Based on Driving Behaviors Classification

Zhishuo Liu1( ), Mengjun Hao1, Fang Tian2
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100091, China
Business Administration Division, Seaver College, Pepperdine University, Malibu, CA 90263, USA
Show Author Information

Abstract

Based on the present situation of usage based insurance (UBI) research and application, this paper puts forward the UBI rating model based on driving behavior classification, and applies the technology of data mining to the evaluation of driving behavior. The actual driving behavior data and the risk data of 400 drivers are used as experimental data. Finally, an example shows that the driving behavior classification model is superior to the driving behavior score model for the identification of accident risk, which can make UBI rate more scientific and reasonable.

Keywords

vehicle insurance ratesusage based insurance (UBI)telematicsdriving behaviorsclassification algorithm

References

1
S. Zhu, Research on the model and method of vehicle insurance rate determination based on UBI under the environment of Internet of vehicles, MA dissertation, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China, 2015.
2
J. Boxbaum, Mileage-based user fee demonstration project: Pay-as-you-drive experimental findings, Tech. Rep. MN/RC – 2006-39A, Minnesota Department of Transportation, St. Paul, MN, USA, 2006.
3

W. Vickrey, Automobile accidents, tort law, externalities, and insurance: An economist’s critique, Law and Contemporary Problems, vol. 33, no. 3, pp. 464–487, 1968.
Crossref Google Scholar
4
A. Roberts, Developments in the pricing of vehicle insurance based upon driving behaviors, https://iiky.org/wp-content/uploads/2015/06/Pricing_Driving_Behavior_Roberts.pdf, 2014.
5

J. Zantema, D. H. V. Amelsfort, M. C. J. Bilemer, and P. H. L. Bovy, Pay-as-you-drive strategies: Case study of safety and accessibility effects, Transportation Research Record, vol. 2078, no. 1, pp. 8–16, 2008.
Crossref Google Scholar
6
Strategic Highway Research Program 2, Revised safety research plan: Making a significant improvement in highway safety, https://trid.trb.org/view/1231172, 2012.
7
P. Desyllas and M. Sakob, Profiting from business model innovation: Evidence from pay-as-you-drive auto insurance, Research Policy, vol. 42, no. 1, pp. 101–116, 2013.https://doi.org/10.1016/j.respol.2012.05.008
Crossref
8
I. W. H. Parry, Is pay-as-you-drive insurance a better way to reduce gasoline than gasoline taxes? American Economic Review, vol. 95, no. 2, pp. 288–293, 2005.https://doi.org/10.1257/000282805774670482
Crossref
9
T. Litman, Pay-as-you-drive pricing and insurance regulatory objectives, Journal of Insurance Regulation, vol. 23, no. 3, pp. 35−53, 2006.
10
T. Litman, Pay-as-you-drive insurance recommendations for implementation, Victoria Transport Policy Institute, https://www.vtpi.org/payd_rec.pdf, 2011.
11
J. F. Jiang, Research on design and pricing of vehicle insurance products based on driving behaviors, Huaqiao University, MA dissertation, School of Economics and Finance, Huaqiao University, Quanzhou, China, 2020.
12
J. Y. Bian, Research on UBI vehicle insurance pricing strategy based on driving behaviors data analysis, MEng dissertation, School of communication and information engineering, Nanjing University of Posts and Telecommunications, Nanjing, China, 2020.
13
S. Jiang, X. Li, and Q. Zheng, Data Mining Principle and Practice (in Chinese). Beijing, China: Electronic Industry Press, 2011.
14
M. Wu, Research on attribute selection algorithm based on SVM and information gain, (in Chinese), Journal of Hangzhou University of Electronic Science and technology, vol. 28, no. 6, pp. 143–146, 2008.
15
F. Samadzadegan, A. Soleymani, and R. A. Abbaspour, Evaluation of genetic algorithms for tuning SVM parameters in multi-class problems, in Proc. 2010 11thInternational Symposium on Computational Intelligence and Informatics (CINTI), Budapest, Hungary, 2010, pp. 323–328.https://doi.org/10.1109/CINTI.2010.5672224
Crossref
International Journal of Crowd Science
Volume 6 Issue 2,
June 2022
Pages 98-109
DOI: 10.26599/IJCS.2022.9100012
Cite this article:
Liu Z, Hao M, Tian F. Ratemaking Model of Usage Based Insurance Based on Driving Behaviors Classification. International Journal of Crowd Science, 2022, 6(2): 98-109. https://doi.org/10.26599/IJCS.2022.9100012

637

Views

78

Downloads

3

Crossref

3

Scopus

Altmetrics
Received: 15 March 2022
Revised: 15 April 2022
Accepted: 18 April 2022
Published: 30 June 2022
© The author(s) 2022

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
Return