Preprints
https://doi.org/10.5194/egusphere-2026-1169
https://doi.org/10.5194/egusphere-2026-1169
31 Mar 2026
 | 31 Mar 2026
Status: this preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).

Short-Term Management of Water-Damage Claim Risk Using Ensemble Precipitation Forecasts

Håkon Otneim, Etienne Dunn-Sigouin, Sondre Hølleland, Mahsa Gorji, and Geir Drage Berentsen

Abstract. Insurers are increasingly challenged by weather-related claims arising from property damage, yet they lack adequate tools for near-term planning because traditional actuarial models do not incorporate real-time weather forecasts. This study demonstrates that incorporating ensemble precipitation forecasts improves short-range (1–4 days ahead) predictions of property insurance claim counts, thereby enabling proactive risk management. We present a forecasting framework for two Norwegian cities, Bergen and Oslo, using precipitation forecasts to predict days exceeding operationally significant thresholds. The models are evaluated by their forecast skill and reliability in predicting claim surges, as well as by their economic value in a cost-loss decision context, illustrating the potential reduction in expected costs when early warning triggers are in place. Results show that weather-informed models substantially outperform baseline models based on climatology, improving discrimination of claim events and yielding up to 30–50 % reduction in expected daily costs under various ideal warning scenarios. Two case studies of extreme events highlight how weather forecasts translated into early claims warnings could guide resource allocation and customer advisories. Overall, the presented framework highlights the practical benefit of integrating meteorological forecast information into insurance operations and offers a template for insurers to enhance climate resilience through improved risk communication and short-term decision support.

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Håkon Otneim, Etienne Dunn-Sigouin, Sondre Hølleland, Mahsa Gorji, and Geir Drage Berentsen

Status: open (until 12 May 2026)

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Håkon Otneim, Etienne Dunn-Sigouin, Sondre Hølleland, Mahsa Gorji, and Geir Drage Berentsen

Model code and software

Data and code for reproducing results Sondre Hølleland https://github.com/holleland/ForecastingInsuranceClaims

Håkon Otneim, Etienne Dunn-Sigouin, Sondre Hølleland, Mahsa Gorji, and Geir Drage Berentsen

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Short summary
This study investigates whether short-range rain forecasts can help insurers prepare for bursts of water-damage claims. Using claim records and weather forecasts from Bergen and Oslo, Norway, we find that forecast-based models can identify risky days much more effectively than models without weather information. The models potentially cut expected daily costs by about 30 to 50 percent, helping insurers warn customers earlier, plan staffing, and improve resilience to heavier rainfall.
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