MOLTO RE / RESEARCH
Connecting natural catastrophe risk to underwriting, portfolio strategy, and capital decisions.
THE RISK LANDSCAPE
Catastrophe risk crosses geographies, industries, and balance sheets. Our research framework considers the physical event, the assets exposed, their vulnerability, and the financial terms that determine how losses are shared.
Methods and data requirements vary by peril. Geophysical hazards such as earthquake and tsunami require distinct hazard inputs; climate trends are not a substitute for those models.
THE EVIDENCE
Each dataset answers a different question. The value comes from aligning them across time, location, exposure, and financial terms.
Study the conditions that shape catastrophe exposure over time. Historical records, satellite observations, reanalysis, and climate scenarios provide complementary views of changing hazard patterns.
Applications include drought persistence, heat stress, soil moisture, vegetation conditions, wildfire environments, and changes in the frequency or severity of extreme events.
Connect observed weather to the location, timing, and intensity of damaging events. Rainfall, wind, temperature, storm tracks, and event footprints help distinguish regional conditions from local exposure.
Applications include event reconstruction, accumulation monitoring, historical stress tests, and the design and evaluation of weather-based parametric triggers.
Evaluate how interest rates, inflation, macroeconomic cycles, credit conditions, and equity-market movements influence asset values, financing costs, and risk-bearing capacity. Assess how financial conditions interact with catastrophe losses, insurance liabilities, and capital deployment.
Then examine commodity-price exposure across agriculture, energy, and other sectors, including how weather and catastrophe events affect production, supply chains, input costs, revenues, and recovery costs. Applications include price-and-yield dependence and scenarios where physical losses coincide with adverse financial and commodity-market movements.
Use loss experience to test how hazards translate into insured outcomes. Where available, claims records are linked to events, exposure characteristics, and policy terms to examine frequency, severity, and development.
Applications include loss-cost analysis, experience calibration, reserving support, and evaluation of deductibles, limits, inflation, and changes in portfolio composition.
Bring the analysis back to the risks a client actually holds. Location schedules, insured values, policy terms, crop and acreage records, and portfolio bordereaux establish the financial context for each assessment.
Applications include data-quality review, geospatial enrichment, concentration analysis, coverage mapping, and evaluation of gross, ceded, and retained risk.
THE APPLICATION
Analytical work is scoped to the client’s portfolio, available evidence, and the decision at hand.
Assess risk differentiation, loss costs, coverage terms, and the sensitivity of results to exposure and hazard assumptions.
Identify geographic concentrations, dependencies across perils, and scenarios that can affect multiple locations or business lines together.
Evaluate attachment points, limits, retentions, and quota-share or excess-of-loss structures against portfolio objectives.
Explore measurable triggers, payout structures, historical performance, and basis risk, the gap between a payout and the loss experienced.
Data quality, historical coverage, model assumptions, and uncertainty are considered throughout. Historical experience and scenario results inform decisions; they do not guarantee future outcomes.
PRIVATE INSIGHTS
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