The potential of machine learning for weather index insurance

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

doi:https://doi.org/10.5194/nhess-21-2379-2021

Articles | Volume 21, issue 8

https://doi.org/10.5194/nhess-21-2379-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Groundbreaking technologies, big data, and innovation for...

https://doi.org/10.5194/nhess-21-2379-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 8

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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Final revised paper (published on 11 Aug 2021)
Preprint (discussion started on 10 Aug 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review of nhess-2020-220', Anonymous Referee #1, 24 Aug 2020
- AC1: 'Reply on RC1', Luigi Cesarini, 17 Apr 2021
RC2: 'Review of nhess-2020-220 nhess-2020-220', Anonymous Referee #2, 23 Mar 2021
- AC2: 'Reply on RC2', Luigi Cesarini, 17 Apr 2021

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

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.