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Diver Risk Assessment Model Considering Trip Characteristics Using Insurance Data System.

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Title: Diver Risk Assessment Model Considering Trip Characteristics Using Insurance Data System.
Authors: Soltani, Majid1 msnsoltani@gmail.com, Seyedabrishami, Seyedehsan2, Mamdoohi, Amirreza2, Kordehdeh, Vadood Alyari1
Source: Procedia Engineering. 2016, Vol. 161, p1160-1165. 6p.
Subjects: Risk assessment, Insurance databases, Logits, Socioeconomics, Insurance companies
Geographic Terms: Iran
Abstract: Risky drivers impose a lot of damages to insurance companies, thus insurance providers usually may offer high-risk drivers coverage with higher prices. High-risk drivers are identified in terms of violations and accidents history. This paper investigates the impact of drivers’ trip characteristics in addition to personal and socio-economic characteristics on drivers’ riskiness. In case of non-accessibility to the history of drivers’ violations or accidents, the impact model can be helpful for insurance providers to measure drivers’ risk-taking attitudes. Then, high-risk driver coverage will be more expensive than the standard coverage. Insurance data from ASIA, the largest auto insurance company in Iran, for 506 drivers randomly selected are obtained using ASIA data system and interviewing with drivers at ASIA insurance claim centres. An ordered logit model has been utilized as driver risk assessment model. The dependent variables ware the number of accidents on insurance records and traffic ticket. The results show that drivers often use private vehicles for non-mandatory purposes are riskier than mandatory purposes. Furthermore, drivers usually traveling on rural roads are high-risk for drivers comparing to urban roads. The findings show that insurance providers may suggest expensive coverage for rural road drivers with non-mandatory purposes. [ABSTRACT FROM AUTHOR]
Copyright of Procedia Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: Diver Risk Assessment Model Considering Trip Characteristics Using Insurance Data System.
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  Data: <searchLink fieldCode="JN" term="%22Procedia+Engineering%22">Procedia Engineering</searchLink>. 2016, Vol. 161, p1160-1165. 6p.
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  Data: <searchLink fieldCode="DE" term="%22Risk+assessment%22">Risk assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Insurance+databases%22">Insurance databases</searchLink><br /><searchLink fieldCode="DE" term="%22Logits%22">Logits</searchLink><br /><searchLink fieldCode="DE" term="%22Socioeconomics%22">Socioeconomics</searchLink><br /><searchLink fieldCode="DE" term="%22Insurance+companies%22">Insurance companies</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Iran%22">Iran</searchLink>
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  Data: Risky drivers impose a lot of damages to insurance companies, thus insurance providers usually may offer high-risk drivers coverage with higher prices. High-risk drivers are identified in terms of violations and accidents history. This paper investigates the impact of drivers’ trip characteristics in addition to personal and socio-economic characteristics on drivers’ riskiness. In case of non-accessibility to the history of drivers’ violations or accidents, the impact model can be helpful for insurance providers to measure drivers’ risk-taking attitudes. Then, high-risk driver coverage will be more expensive than the standard coverage. Insurance data from ASIA, the largest auto insurance company in Iran, for 506 drivers randomly selected are obtained using ASIA data system and interviewing with drivers at ASIA insurance claim centres. An ordered logit model has been utilized as driver risk assessment model. The dependent variables ware the number of accidents on insurance records and traffic ticket. The results show that drivers often use private vehicles for non-mandatory purposes are riskier than mandatory purposes. Furthermore, drivers usually traveling on rural roads are high-risk for drivers comparing to urban roads. The findings show that insurance providers may suggest expensive coverage for rural road drivers with non-mandatory purposes. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Procedia Engineering is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.proeng.2016.08.532
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        Text: English
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      – SubjectFull: Logits
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      – SubjectFull: Insurance companies
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      – SubjectFull: Iran
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      – TitleFull: Diver Risk Assessment Model Considering Trip Characteristics Using Insurance Data System.
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