Parametric Reinsurance

✅ Context: Facing an increasing appetite for homeowner business in Florida, a carrier sought to augment its traditional reinsurance procurement with USD 140m in parametric capacity.

✅ Solution Design: Working closely with the broker, Descartes assigned distinct insured values to each ZIP code. The structure utilized a refined loss model where individual payouts were calculated based on the distance to the hurricane track and sustained wind speeds. The aggregate losses included a modelled reimbursement from the Florida Hurricane Catastrophe Fund and a modelled primary reinsurance layer of USD 75m.

✅ Results: A USD 140m XS 75m structure demonstrated its efficacy during the 2024 season. Had this been in place during Hurricane Milton, it would have triggered a prompt recovery of nearly USD 40m, proving its value as a cost-efficient tool for capital management.

✅ Context: A commercial property cedent in Turkiye was looking for excess reinsurance capacity to cover their peak earthquake perils. 

✅ Solution Design: Their broker’s Alternative Risk Transfer (ART) team engaged Descartes to design a solution that would mirror actual loss patterns while ensuring rapid liquidity to fund reinstatement premiums. Our underwriters and data scientists engineered a structure that calculated payouts based on the magnitude of the seismic event and the proximity of the portfolio’s assets to the fault line.

✅ Results: With an USD 80m XS 200m remote parametric layer, the cedent successfully optimized their capital requirements, securing a reliable mechanism for swift compensation following a major earthquake.

✅ Context: A Texas homeowner insurer faced mounting earnings volatility due to high-frequency Severe Convective Storm (SCS) events that frequently eroded the retention but failed to reach traditional reinsurance attachment points.

✅ Solution Design: To solve this, the broker placed a parametric aggregate cover based on Descartes’ proprietary modeled loss index. This index converts hail, tornado, and wind data into estimated loss values, calibrated to align with the client’s internal vendor model outputs. The client secured a USD 50m XS 100m aggregate cover at competitive rates, where traditional markets fell short of expectations.

✅ Results: Following an active hailstorm season with USD 130m in modeled losses, the insurer would have received a USD 30m payout within weeks of the policy period ending.

✅ Context: Seeking to reduce an AUD 200m flood retention, an insurer with a significant Australian home and motor book found traditional market offerings too rigid. 

✅ Solution Design: With the support of Descartes’ technological capabilities, the broker designed a parametric flood index using satellite-based rainfall measurements and gridded exposure data. This collaboration ensured the product was precisely calibrated to the insurer’s historical loss data and geographic footprint.

✅ Results: By purchasing an AUD 100m XS 100m policy, the insurer achieved a significant reduction in retained exposure, optimizing earnings stability in a region defined by high flood frequency.

✅ Context: A Californian insurer with high accumulation in a specific neighborhood in the Los Angeles urban area required a bespoke solution to manage localized wildfire risk. They struggled to find such a bespoke, location-specific product in the traditional reinsurance market.

✅ Solution Design: In partnership with the broker, Descartes designed a tailor-made wildfire protection. Utilizing high-resolution satellite imagery, any wildfire entering the defined perimeter of the neighborhood triggers a payout proportional to the burned area and the predefined insured values.

✅ Results: During events similar to the January 2025 LA fires, this structure ensures the cedent receives critical liquidity in a matter of weeks, rather than the months or years typical of traditional claims adjustment.

✅ Context: As part of a government-subsidized scheme supporting Indian farmers, an insurer required a mechanism to cap portfolio-level losses across multiple states. The broker sought to place a 70% XS 120% Stop-Loss in the reinsurance market.

✅ Solution Design: Through an in-depth analysis of multi-peril weather and Nat Cat risks affecting the specific agricultural regions, Descartes was able to confidently underwrite the risk and provide reinsurance capacity at an adequate price. 

✅ Results: This stop-loss structure provides the insurer with an essential safety net, ensuring the sustainability of their agricultural portfolio.