Climate change, new technologies, and shifting governance are redefining how climate and environmental risks are understood and financed. The January 2026 special issue of The Geneva Papers on Risk and Insurance, edited by Maryam Golnaraghi, Swenja Surminski, and Chris Greig, gathers research on climate modelling, adaptation, and catastrophe management, spotlighting the innovations that will be vital for today’s fast-changing climate risk landscape.
Advancing climate risk modelling and forecasting
Agricultural insurance and climate variability: analysing soybean yield risks in Brazil using distributional regression models by Luiz Nakamura et al. examines how climate variability affects insurance claims using distributional regression models that integrate climatic indicators. The models reveal several non-linear relationships that traditional approaches cannot detect. Minimum temperature, dew point, geographic location, crop area, and wind speed significantly influence the likelihood of claim occurrence, while precipitation, crop size, and temperature shape claim amounts once losses occur. The results show that flexible distributional models improve risk assessment, premium calibration, and geographic portfolio management.
Laijuan Luo et al. develop a framework to predict monthly flood probabilities in China and assess how these risks may shift under future climate scenarios in Assessing regional flood risks under climate change: a machine learning and spatial clustering approach. Using historical climate, geographic, and socioeconomic data, the authors test four predictive models and find that the LightGBM model consistently provides the highest accuracy. They combine this model with the SKATER spatial clustering algorithm to enable more effective risk zoning across cities. The results show clear regional patterns: southern China exhibits persistently high flood risk, while northwestern and Tibetan Plateau regions are generally low risk. The authors project rising flood probabilities through 2100 – especially under high-emissions scenarios – in numerous provinces.
The article by Eric Vansteenberghe, Insurance supervision under climate change: a pioneer detection method, introduces the Pioneers Detection Method (PDM), a supervisory tool designed to help insurance regulators assess insurability and market stability amid climate-driven shifts in extreme losses. Because extreme events are rare and claims data is fragmented across firms, traditional opinion-pooling methods fail to identify which experts are learning fastest about the new risk environment. The PDM detects ‘pioneers’ – experts whose assessments initially deviate from the majority but toward whom others converge over time. Simulations show that the PDM outperforms linear, median, and other pooling techniques, particularly in early post-shock periods, improving supervisory estimates and welfare – especially in markets with few insurers and limited data.
Strengthening insurance design, catastrophe management, and risk transfer
Hang Gao et al. investigate basis risk – the mismatch between index-triggered payouts and actual losses – in weather parametric insurance in Managing basis risks in weather parametric insurance: a quantitative study of diversification and key influencing factors. Portfolio-level basis risk and basis risk volatility are found to decrease as the number of contracts increases, basis risk is shown to follow predictable patterns based on geospatial factors, and hazard severity has no meaningful impact on basis risk once trigger thresholds have been exceeded. These findings indicate that while basis risk is inherent, it can be effectively managed through portfolio diversification and geospatial optimisation.
In An examination of catastrophe insurance programs: elements that support program resilience, Mary Kelly et al. analyse design features that improve the resilience of catastrophe insurance programmes in the face of extreme or unexpected loss events. Drawing on global examples, the authors evaluate how public-private partnerships perform under stress and how programme structures evolve in response. Key determinants for resilience include whether coverage is mandatory, how governments participate in loss payments, the presence of risk-sharing pools, and solvency requirements for private insurers. The paper concludes that no programme can achieve complete resilience, but clearer pre-event rules, government backstops for tail risk, and investment in mitigation can substantially strengthen long-term sustainability amid escalating climate risks.
In Assessing the financial feasibility of municipal flood risk pooling in the Western Cape, South Africa, Kamleshan Pillay assesses whether a municipal flood risk pool could provide financially sustainable post-disaster liquidity in a region where traditional insurance coverage is limited and government relief is often delayed. The study examines how seed capital, reinsurance structure, spatial correlation, participation, and climate change affect pool solvency. It finds that seed capital is the dominant driver of financial viability – low allocations (USD 20–25 million) lead to very high ruin probabilities, even with proportional reinsurance. Non-proportional reinsurance improves solvency, but only when paired with sufficient capital reserves. Overall, the study concludes that a viable risk pool requires substantial upfront capital, careful reinsurance design, and explicit consideration of spatial and climate-driven risk dynamics.
Innovative insurance strategies for adaptation, prevention, and societal resilience
When does forecast-based insurance benefit? An economic analysis of drought risk anticipatory insurance by Vaibhav Anand et al. evaluates the economic value of forecast-based anticipatory insurance, using the African Risk Capacity’s pilot drought programme in Malawi and Zambia as a case study. Insurance pays out when drought forecasts exceed a trigger, enabling early interventions during the agricultural season and helping countries build operational capacity for forecast-based action. The authors identify when such insurance improves welfare relative to traditional ex post financing or self-funded early action, showing that product value mainly comes from capacity building, particularly for countries lacking the institutions, procedures, and liquidity needed for early response. Insurance mechanisms are found to add limited value when basis risk is high or early actions are cost-effective.
Closing the protection gap or prioritising prevention: alternative value creation strategies based on data-driven technologies in the context of insurance companies’ climate change actions by Margherita Tondi and Timo Rintamäki examines how insurers are rethinking value creation as climate change intensifies physical risks and undermines traditional insurance models. The authors propose a framework that shows how insurers innovate across products and markets, the value chain, and local clusters to close protection gaps and prioritise risk prevention. They show how data-driven technologies such as AI, IoT sensors, satellite data, big data analytics, and blockchain enable new forms of climate-related insurance solutions, from microinsurance and parametric products to automated underwriting, early warning systems, and community-level resilience initiatives.
Access the issue at SpringerLink (promotional free access to Special Edition until 20 April 2026, after which subscription required).
