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A Comparison of Underwriting Decision Making Between Telematics-Enabled UBI and Traditional Auto Insurance

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  • Chiang Ku Fan
  • Wei-Yuan Wang

Abstract

Because of telematics-enabled UBI (usage-based insurance), real driving information can be collected and provided to underwriters. It promises more efficient pricing of risks, with widespread benefits expected to accrue to insurers, consumers and society. From the perspective of auto insurance underwriters, compare to the driving data collected by a traditional auto insurance application form , the underwriting data collected from a telematics devices more effective or not is a question and to answer. By employing prior literature reviewing and grey relational analysis, this study found most of driving behavior data collected from telematics devices is very helpful for auto insurance underwriting, some traditional data collected by an application form is still necessary for underwriters to make a well underwriting decision. The implication is, in order to improve the effective of an underwriting decision making, insurance companies need to take advantage of IoT(Internet of Things) tech to collect more helpful underwriting data as well as adjust their underwriting policy accordingly.JEL classification numbers: O32Keywords: usage-based insurance, auto insurance, telematics, Underwriting

Suggested Citation

  • Chiang Ku Fan & Wei-Yuan Wang, 2017. "A Comparison of Underwriting Decision Making Between Telematics-Enabled UBI and Traditional Auto Insurance," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 7(1), pages 1-2.
    • Handle: RePEc:spt:admaec:v:7:y:2017:i:1:f:7_1_2
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    Citations

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    Cited by:

    1. Montserrat Guillen & Jens Perch Nielsen & Ana M. Pérez‐Marín, 2021. "Near‐miss telematics in motor insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 569-589, September.
    2. Chao Ma, 2021. "Be Cautious In The Last Month: The Sunk Cost Fallacy Held By Car Insurance Policyholders," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(3), pages 1199-1236, August.
    3. Ma, Yu-Luen & Zhu, Xiaoyu & Hu, Xianbiao & Chiu, Yi-Chang, 2018. "The use of context-sensitive insurance telematics data in auto insurance rate making," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 243-258.

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