Preprints
https://doi.org/10.5194/egusphere-2023-2862
https://doi.org/10.5194/egusphere-2023-2862
11 Jan 2024
 | 11 Jan 2024

Exploring the use of seasonal forecasts to adapt flood insurance premiums

Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Boutzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz

Abstract. Insurance is an important element of flood risk management providing financial compensation after disastrous losses. In a competitive market, insurers need to base their premiums on the most accurate risk estimation. To this end, (recent) historic loss data is used. However, climate variability can substantially affect flood risk, and anticipating such variations could provide a competitive gain. For instance, for a year with higher flood probabilities, the insurer might raise premiums to hedge against the increased risk or communicate the increased risk to policyholders encouraging risk-reduction measures. In this explorative study, we investigate how seasonal flood forecasts could be used to adapt flood insurance premiums on an annual basis. In an application for Germany, we apply a forecasting method that predicts winter flood probability distributions conditioned on the catchment wetness in the season ahead. The deviation from the long-term is used to calculate deviations in Expected Annual Damage which serve as input into an insurance model to compute deviations in household insurance premiums for the upcoming year. Our study suggests that the temporal variations in flood probabilities are substantial, leading to significant variations in flood risk and premiums. As our models are based on a range of assumptions and as the skill of seasonal flood forecasts is still limited, particularly in Central Europe, our study is seen as first demonstration of how seasonal forecasting could be combined with risk and insurance models to inform the (re-)insurance sector about upcoming changes in risk.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Boutzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-2862', Anonymous Referee #1, 03 Feb 2024
    • AC1: 'Reply on RC1', Viet Dung Nguyen, 27 May 2024
  • RC2: 'Comment on egusphere-2023-2862', Anonymous Referee #2, 20 Mar 2024
    • AC2: 'Reply on RC2', Viet Dung Nguyen, 27 May 2024
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Boutzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Boutzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz

Viewed

Total article views: 418 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
280 112 26 418 15 14
  • HTML: 280
  • PDF: 112
  • XML: 26
  • Total: 418
  • BibTeX: 15
  • EndNote: 14
Views and downloads (calculated since 11 Jan 2024)
Cumulative views and downloads (calculated since 11 Jan 2024)

Viewed (geographical distribution)

Total article views: 423 (including HTML, PDF, and XML) Thereof 423 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Jun 2024
Download
Short summary
Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.