Sharing Economy, Platforms, and Crowds
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Paper Number
2442
Paper Type
Completed
Description
Peer-to-peer (P2P) insurance uses new technology to connect policyholders and brings about disruptive innovation. While P2P insurance serving people with relatively high degrees of social connection, like friends and relatives, has been theoretically and practically underpinned, there is a lack of understanding about its viability or efficiency in serving strangers with few to no social ties as moral hazard may be substantial. In this paper, we bridge the gap by empirically measuring moral hazard in a P2P auto insurance where the insured individuals are strangers. Our research findings remove an obstacle that may hinder a broad application of the P2P insurance model among large groups of individuals. Moreover, we investigate factors that mitigate moral hazard and study the impact of transparency in premium balance on driving safety. We show that the transparency allows people to learn vicariously from peers’ lessons and lets them drive more safely.
Recommended Citation
Zhang, Yuxin; du, yalei; Zhang, Yuanyuan; and Zhang, Quan, "Moral Hazard and Transparency in Peer-to-Peer Auto Insurance with Telematics" (2023). ICIS 2023 Proceedings. 19.
https://aisel.aisnet.org/icis2023/sharing_econ/sharing_econ/19
Moral Hazard and Transparency in Peer-to-Peer Auto Insurance with Telematics
Peer-to-peer (P2P) insurance uses new technology to connect policyholders and brings about disruptive innovation. While P2P insurance serving people with relatively high degrees of social connection, like friends and relatives, has been theoretically and practically underpinned, there is a lack of understanding about its viability or efficiency in serving strangers with few to no social ties as moral hazard may be substantial. In this paper, we bridge the gap by empirically measuring moral hazard in a P2P auto insurance where the insured individuals are strangers. Our research findings remove an obstacle that may hinder a broad application of the P2P insurance model among large groups of individuals. Moreover, we investigate factors that mitigate moral hazard and study the impact of transparency in premium balance on driving safety. We show that the transparency allows people to learn vicariously from peers’ lessons and lets them drive more safely.
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