Articles | Volume 21, issue 8
https://doi.org/10.5194/nhess-21-2379-2021
https://doi.org/10.5194/nhess-21-2379-2021
Research article
 | 
11 Aug 2021
Research article |  | 11 Aug 2021

The potential of machine learning for weather index insurance

Luigi Cesarini, Rui Figueiredo, Beatrice Monteleone, and Mario L. V. Martina

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (06 May 2021) by Paolo Tarolli
AR by Luigi Cesarini on behalf of the Authors (10 May 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (17 May 2021) by Paolo Tarolli
RR by Anonymous Referee #1 (28 May 2021)
RR by Anonymous Referee #2 (10 Jun 2021)
ED: Publish subject to minor revisions (review by editor) (24 Jun 2021) by Paolo Tarolli
AR by Luigi Cesarini on behalf of the Authors (28 Jun 2021)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (01 Jul 2021) by Paolo Tarolli
AR by Luigi Cesarini on behalf of the Authors (07 Jul 2021)  Manuscript 
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Short summary
Weather index insurance is an innovative program used to manage the risk associated with natural disasters, providing instantaneous financial support to the insured party. This paper proposes a methodology that exploits the power of machine learning to identify extreme events for which a payout from the insurance could be delivered. The improvements achieved using these algorithms are an encouraging step forward in the promotion and implementation of this insurance instrument.
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