On IoT‐enabled risk prevention and insurance: A systematic literature review

Ion Cimbru et al.

Risk Management and Insurance Review2025https://doi.org/10.1111/rmir.70025article
ABDC C
Weight
0.37

What the paper says

Abstract The insurance market is increasingly adopting connected insurance offerings, such as telematics, wearables, and parametric products, enabled by Internet of Things (IoT) technologies. These innovations generate granular, observable risk data and support the delivery of preventive services. While connected insurance has gained research attention, the role of IoT‐enabled prevention and its impact on insurance, in particular on demand, remain underexplored. To address this gap, we conducted a systematic literature review following the PRISMA guidelines. From 5764 records identified across databases, journals, and industry sources, we analyzed 56 academic and 18 practitioner studies. The results include a comprehensive analysis of how IoT expands risk prevention and insurance mechanisms, as well as the additional benefits and costs introduced to connected insurance solutions, such as discounts, rewards, real‐time services, technology expenses, privacy loss, and cyber risks. This evolution makes the cost–benefit structure broader and more complicated and introduces new drivers of insurance demand, such as technology affinity and the willingness to share data. We argue that existing demand models should be revisited to reflect these dynamics and outline implications for insurers' evolving role, from risk financiers to partners in risk management.

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https://doi.org/https://doi.org/10.1111/rmir.70025

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@article{ion2025,
  title        = {{On IoT‐enabled risk prevention and insurance: A systematic literature review}},
  author       = {Ion Cimbru et al.},
  journal      = {Risk Management and Insurance Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1111/rmir.70025},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.