Literature DB >> 30682611

Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk.

Alexander G Rumson1, Stephen H Hallett2.   

Abstract

Insurance plays a crucial role in human efforts to adapt to environmental hazards. Effective insurance can serve as both a measure to distribute, and a method to communicate risk. In order for insurance to fulfil these roles successfully, policy pricing and cover choices must be risk-based and founded on accurate information. This is reliant on a robust evidence base forming the foundation of policy choices. This paper focuses on the evidence available to insurers and emergent innovation in the use of data. The main risk considered is coastal flooding, for which the insurance sector offers an option for potential adaptation, capable of increasing resilience. However, inadequate supply and analysis of data have been highlighted as factors preventing insurance from fulfilling this role. Research was undertaken to evaluate how data are currently, and could potentially, be used within risk evaluations for the insurance industry. This comprised of 50 interviews with those working and associated with the London insurance market. The research reveals new opportunities, which could facilitate improvements in risk-reflective pricing of policies. These relate to a new generation of data collection techniques and analytics, such as those associated with satellite-derived data, IoT (Internet of Things) sensors, cloud computing, and Big Data solutions. Such technologies present opportunities to reduce moral hazard through basing predictions and pricing of risk on large empirical datasets. The value of insurers' claims data is also revealed, and is shown to have the potential to refine, calibrate, and validate models and methods. The adoption of such data-driven techniques could enable insurers to re-evaluate risk ratings, and in some instances, extend coverage to locations and developments, previously rated as too high a risk to insure. Conversely, other areas may be revealed more vulnerable, which could generate negative impacts for residents in these regions, such as increased premiums. However, the enhanced risk awareness generated, by new technology, data and data analytics, could positively alter future planning, development and investment decisions.
Copyright © 2019 The Author(s). Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Adaptation; Big Data; Remote sensing; Risk analytics

Year:  2019        PMID: 30682611     DOI: 10.1016/j.scitotenv.2019.01.114

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  On the need for a new generation of coastal change models for the 21st century.

Authors:  Roshanka Ranasinghe
Journal:  Sci Rep       Date:  2020-02-06       Impact factor: 4.379

2.  Spatial-temporal potential exposure risk analytics and urban sustainability impacts related to COVID-19 mitigation: A perspective from car mobility behaviour.

Authors:  Peng Jiang; Xiuju Fu; Yee Van Fan; Jiří Jaromír Klemeš; Piao Chen; Stefan Ma; Wanbing Zhang
Journal:  J Clean Prod       Date:  2020-08-19       Impact factor: 9.297

  2 in total

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