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<p>Climate change poses a dual threat to the insurance industry, affecting both assets (transition risk) and liabilities (physical risk). This study advances the 2024 EU-wide climate stress test by addressing its exclusion of reactive management actions. To bridge this gap, it develops a framework for proactive asset allocation, identifying CO<sub>2</sub> concentration thresholds that trigger divestment from corporate bonds and equities exposed to transition risks. Using a model based on climate-induced financial risks for insurers, we optimize divestment thresholds to balance risk and profit until 2030. The model incorporates stochastic projections of flood and cyclone claims, linked to CO<sub>2</sub> concentration trends with scenario-dependent distributions and correlations from NGFS forecasts. Crucially, our analysis demonstrates that remaining invested in brown assets beyond a CO<sub>2</sub> concentration of 439&#xa0;ppm is no longer favorable from a risk or return perspective. Consequently, the identified, scenario-specific thresholds serve as a forward-looking basis for strategic asset allocation, outperforming static strategies by mitigating extreme tail risks in disorderly transitions.</p>

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Scenario-based CO2 thresholds for strategic asset allocation and climate stress testing in insurance

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月12日

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  • Benedikt Funke,
  • Onur Özdil

摘要

Climate change poses a dual threat to the insurance industry, affecting both assets (transition risk) and liabilities (physical risk). This study advances the 2024 EU-wide climate stress test by addressing its exclusion of reactive management actions. To bridge this gap, it develops a framework for proactive asset allocation, identifying CO2 concentration thresholds that trigger divestment from corporate bonds and equities exposed to transition risks. Using a model based on climate-induced financial risks for insurers, we optimize divestment thresholds to balance risk and profit until 2030. The model incorporates stochastic projections of flood and cyclone claims, linked to CO2 concentration trends with scenario-dependent distributions and correlations from NGFS forecasts. Crucially, our analysis demonstrates that remaining invested in brown assets beyond a CO2 concentration of 439 ppm is no longer favorable from a risk or return perspective. Consequently, the identified, scenario-specific thresholds serve as a forward-looking basis for strategic asset allocation, outperforming static strategies by mitigating extreme tail risks in disorderly transitions.