Wall Street Adopts Catastrophe Models for Conflict Risk

Bloomberg reports that catastrophe modelers who traditionally built models for natural disasters are adapting their methodology to help investors, banks, and insurers forecast military conflicts. Wall Street is racing to incorporate war into its risk scenarios. Per the Institute for Economics and Peace, since 2008 the number of countries engaged in external conflicts has nearly doubled to just over 100, and the economic impact of violence now stands at almost $22 trillion (Bloomberg).

Catastrophe models for natural hazards apply scenario-based probabilistic frameworks, geospatial exposure mapping, and tail-loss estimation. Adapting those frameworks to conflict involves integrating different data types - event datasets, political indicators, and real-time intelligence - and confronting greater structural uncertainty and lower historical frequency for comparable events compared to natural-hazard modeling.

Financial institutions face growing pressure to quantify non-market tail risks in portfolios and insurance books. Markets and insurers increasingly seek scenario-driven stress tests that capture correlated losses from supply-chain disruption, commodity shocks, and insured property damage tied to conflicts. That shift can change how underwriters price country risk and how investment teams incorporate geopolitical scenarios into risk limits.

Meaningful uptake will likely require transparent model assumptions, scenario governance, third-party backtests against historical conflict losses, and adoption by major reinsurers or regulatory stress-testing bodies.