As civil unrest escalates globally, insurers are confronting a sharp reality: the old models no longer work.
A new analysis from Willis Towers Watson (WTW), How to Predict a Riot: Developing Risk-Based Loss Models for Social Unrest, outlines how traditional risk models fall short in tracking today’s volatile protest landscape and and how the promise of spatial analytics and social triggers are helping reshape the industry’s response.
According to WTW, insurance claims for strikes, riots, and civil commotion (SRCC) have surged over 3,000% in recent years, with billions in losses from events in South Africa, Chile, Colombia, and the United States. These losses increasingly trace back to deeper trends: worsening inequality, youth distrust in governments, and the viral speed of social media mobilization.
To unpack these developments, Risk Market News spoke with the article’s co-author, Weimeng Yeo, who leads terrorism and political violence analytics at WTW. In the Q&A below, Yeo explains how the modeling world is adapting to an era where a hashtag can spark a billion-dollar event.
Q&A With Weimeng Yeo
Risk Market News: Civil unrest doesn’t follow consistent historical patterns. How can risk models adapt in the face of that data challenge?
