The current fixed car-year pricing of auto insurance is inefficient and actuarially inaccurate since motorists in the same risk class pay the same amount of premium regardless of the number of miles covered by the different vehicles. In this paper, a simple alternative, the pay as you drive insurance, was proposed whereby motorists only pay for the mileage covered by their vehicles. The main objective was to find a suitable probability distribution that would be used to model the per kilometer risk premiums for the total aggregate claims cost. A case study was done for a company in Kiambu county. The data collected consisted of 5 variables in 194 categories whereby the total aggregate claims cost was the dependent variable. The data collection technique was via a census. The most appropriate model was found to be the zero inflated negative binomial model. The significant factors were found to be the make of the vehicle, annual mileage, and present value of the vehicle. In addition to this, mileage was also found to be positively correlated to the total aggregate claims cost.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 4, Issue 6) |
| DOI | 10.11648/j.ajtas.20150406.23 |
| Page(s) | 527-533 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2015. Published by Science Publishing Group |
Pay As You Drive, Generalized Linear Model, Risk Premium, Vehicle Insurance, Total Claims Cost, Correlation, Premium Pricing
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APA Style
Charity Mkajuma Wamwea, Benjamin Kyalo Muema, Joseph Kyalo Mung’atu. (2015). Modelling a Pay-As-You-Drive Insurance Pricing Structure Using a Generalized Linear Model: Case Study of a Company in Kiambu. American Journal of Theoretical and Applied Statistics, 4(6), 527-533. https://doi.org/10.11648/j.ajtas.20150406.23
ACS Style
Charity Mkajuma Wamwea; Benjamin Kyalo Muema; Joseph Kyalo Mung’atu. Modelling a Pay-As-You-Drive Insurance Pricing Structure Using a Generalized Linear Model: Case Study of a Company in Kiambu. Am. J. Theor. Appl. Stat. 2015, 4(6), 527-533. doi: 10.11648/j.ajtas.20150406.23
AMA Style
Charity Mkajuma Wamwea, Benjamin Kyalo Muema, Joseph Kyalo Mung’atu. Modelling a Pay-As-You-Drive Insurance Pricing Structure Using a Generalized Linear Model: Case Study of a Company in Kiambu. Am J Theor Appl Stat. 2015;4(6):527-533. doi: 10.11648/j.ajtas.20150406.23
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Download@article{10.11648/j.ajtas.20150406.23,
author = {Charity Mkajuma Wamwea and Benjamin Kyalo Muema and Joseph Kyalo Mung’atu},
title = {Modelling a Pay-As-You-Drive Insurance Pricing Structure Using a Generalized Linear Model: Case Study of a Company in Kiambu},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {4},
number = {6},
pages = {527-533},
doi = {10.11648/j.ajtas.20150406.23},
url = {https://doi.org/10.11648/j.ajtas.20150406.23},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150406.23},
abstract = {The current fixed car-year pricing of auto insurance is inefficient and actuarially inaccurate since motorists in the same risk class pay the same amount of premium regardless of the number of miles covered by the different vehicles. In this paper, a simple alternative, the pay as you drive insurance, was proposed whereby motorists only pay for the mileage covered by their vehicles. The main objective was to find a suitable probability distribution that would be used to model the per kilometer risk premiums for the total aggregate claims cost. A case study was done for a company in Kiambu county. The data collected consisted of 5 variables in 194 categories whereby the total aggregate claims cost was the dependent variable. The data collection technique was via a census. The most appropriate model was found to be the zero inflated negative binomial model. The significant factors were found to be the make of the vehicle, annual mileage, and present value of the vehicle. In addition to this, mileage was also found to be positively correlated to the total aggregate claims cost.},
year = {2015}
}
TY - JOUR T1 - Modelling a Pay-As-You-Drive Insurance Pricing Structure Using a Generalized Linear Model: Case Study of a Company in Kiambu AU - Charity Mkajuma Wamwea AU - Benjamin Kyalo Muema AU - Joseph Kyalo Mung’atu Y1 - 2015/10/30 PY - 2015 N1 - https://doi.org/10.11648/j.ajtas.20150406.23 DO - 10.11648/j.ajtas.20150406.23 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 527 EP - 533 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20150406.23 AB - The current fixed car-year pricing of auto insurance is inefficient and actuarially inaccurate since motorists in the same risk class pay the same amount of premium regardless of the number of miles covered by the different vehicles. In this paper, a simple alternative, the pay as you drive insurance, was proposed whereby motorists only pay for the mileage covered by their vehicles. The main objective was to find a suitable probability distribution that would be used to model the per kilometer risk premiums for the total aggregate claims cost. A case study was done for a company in Kiambu county. The data collected consisted of 5 variables in 194 categories whereby the total aggregate claims cost was the dependent variable. The data collection technique was via a census. The most appropriate model was found to be the zero inflated negative binomial model. The significant factors were found to be the make of the vehicle, annual mileage, and present value of the vehicle. In addition to this, mileage was also found to be positively correlated to the total aggregate claims cost. VL - 4 IS - 6 ER -
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