Verisk releases first-of-kind predictive SRCC data model for political violence insurers

The model, developed for political violence underwriters, exposure analysts, modellers, and speciality reinsurers, is unlike anything currently available. It offers insurers an entirely new approach to assessing and pricing these risks.

“Insured losses linked to major bouts of unrest have reached new highs in recent years,” said Sam Haynes, head of risk analytics at Verisk Maplecroft. “Our data tells us that in the last 12 months, SRCC risks have risen in over 50% of countries.”

The model is based on Verisk Maplecroft’s extensive experience in quantifying political violence. It uses machine learning to validate its predictions against actual insured losses. It draws on geospatial data covering the size of recent protests, concentrations of economic value, demographics, and a range of political risk, climate, and socio-economic indicators.

The SRCC Predictive Model will help political violence insurers in several ways. It will:

• Improve visibility on the frequency, location, and size of SRCC events.
• Make better, more informed decisions to price policies.
• Quickly identify portfolio exposure to unfolding SRCC events.
• Anticipate potential future SRCC-related losses.
• The model is available via Verisk platforms and through API.

The release of the SRCC Predictive Model comes when the insurance industry is increasingly focused on the risks posed by political violence. Unforeseen losses and ongoing global political and economic uncertainty highlight the need for enhanced solutions to help insurers anticipate where large-scale, damaging events may occur.

The SRCC Predictive Model is a significant development in political violence risk assessment. It offers insurers a valuable tool to help them better manage these risks and protect their businesses from losses.