Climate Conditioned ILW Strategy Can Outperform: Reask / LGT ILS Partners Research

Why It Matters

Seasonal climate signals are now proven to be actionable, giving ILS managers a quantifiable edge in pricing and capital allocation. This shifts the industry from static risk assumptions toward data‑driven, volatility‑reducing strategies.

Key Takeaways

• Climate-conditioned ILW strategy outperformed static benchmark over 40 years
• Average returns up to 30% higher versus traditional models
• Risk‑adjusted returns improved by up to 40%, volatility lowered
• Drawdowns reduced by up to 50% during high‑loss years
• Seasonal forecasts like El Niño now actionable for ILS allocations

Pulse Analysis

The insurance‑linked securities (ILS) market has long relied on static catastrophe models that assume a stationary climate. While these models provide a baseline, they ignore the year‑to‑year variability driven by phenomena such as El Niño or La Niña. As climate change intensifies the frequency and severity of extreme events, investors demand more responsive tools. Incorporating seasonal forecasts into loss projections represents a logical evolution, aligning ILS pricing with the same meteorological data used by the broader reinsurance community.

In the joint Reask‑LGT ILS Partners study, a climate‑conditioned framework combined ECMWF’s SEAS5 seasonal forecasts with Reask’s Climate‑Based Risk Adjuster (CBRA). The team applied the model to 36 regional ILWs, using stochastic loss tables and historical insured hurricane data to simulate capital allocations each year. Compared with a traditional static approach, the dynamic strategy generated average returns up to 30% higher and a compound annual growth rate 35% greater for low‑to‑mid risk tolerances. Moreover, risk‑adjusted returns rose by as much as 40%, while drawdowns during severe loss years were cut by half, indicating both higher upside and lower downside volatility.

The findings have immediate implications for ILS investors and portfolio managers. By treating seasonal climate signals as actionable inputs, firms can fine‑tune exposure, improve capital efficiency, and potentially attract a broader base of risk‑averse capital. The research also signals a shift toward more granular, data‑driven underwriting across the broader insurance sector, encouraging the integration of advanced climate analytics into legacy risk models. As the market digests these results, we can expect a wave of new products and strategies that embed real‑time climate intelligence, reshaping the risk‑return landscape of catastrophe‑linked investments.