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Eswar Prem

Publications

When the Risk Becomes Uninsurable

The global insurance industry is built on the principle that risk is estimable. Historical patterns, actuarial tables, and statistical models have allowed our profession to price uncertainty with reasonable confidence for over a century. Climate change is systematically dismantling that confidence. We are witnessing simultaneous pressures from three directions: the physical intensification of weather-related perils, the economic disruption triggered by the low-carbon transition, and the growing wave of climate litigation creating novel liability exposures. No segment of the industry is untouched — from property catastrophe underwriting to long-tail liability lines, from investment portfolios to reserving assumptions. This paper synthesizes the current state of knowledge on how climate change is reshaping global insurance, with particular attention to emerging markets and India's evolving regulatory landscape. Our central argument is that the insurance industry faces not a single climate challenge but a tripartite risk structure that demands simultaneously updated modelling frameworks, product innovation, and regulatory coordination. Practitioners who treat climate risk as a single-dimensional pricing adjustment will consistently underestimate both their exposure and their opportunity.

EPSS
Eswar Prem +1Jul 31, 2026 · 10 min read

Quantifying Climate Risk

Every major P&C insurance market is grappling with the same uncomfortable truth: the tools we built our profession on historical loss triangles, stable frequency assumptions, stationary tail distributions were designed for a world whose climate was, by and large, predictable. That world is receding. Rapid attribution science now links individual extreme events directly to anthropogenic warming. Climate models show not merely a shift in average temperatures but a fundamental reshaping of the entire loss distribution with the most consequential changes concentrated in the tail. When the distribution shifts, the actuarial assumptions underpinning reserving adequacy, pricing relativities, and capital sufficiency shift with it. The question facing our community is not whether to respond to climate risk, but how to measure it with enough precision to act. Our thesis is straightforward: by combining publicly available climate scenario data, open geospatial datasets, and modern machine learning methods, actuaries can produce peril-specific climate risk scores that integrate directly into existing underwriting, pricing, and reserving workflows even in markets where proprietary data is scarce.

EPSS
Eswar Prem +1Jul 31, 2026 · 9 min read