How do you identify risks to vulnerable assets from strikes, riots and civil commotion?

Matt Hopwood

Man-Made Catastrophe Research Analyst

THE PROBLEM

Civil unrest is on the rise.

Global civil unrest events have risen by 55% between 2023 and 2024.
Often, urban protests or mass gatherings have a cascading impact, damaging property and interrupting business.

2023

2024

Traditional assessment methods often fall short of capturing the dynamic nature of these risks. Insurers require ever more sophisticated tools to understand the potential accumulation of risk.

This is where innovative solutions like crowd modelling tools come into play.

By simulating real-world scenarios, our modelling tools enable underwriters to pinpoint high-risk areas, identify vulnerable buildings and groups of potential target buildings. We then run tailored analyses of potential unrest which helps our underwriters to stay ahead of emerging risks.

THE SOLUTION

IQUW’s Catastrophe Research Analyst, Matt Hopwood, has developed a unique Non-Natural Catastrophe Crowd Modelling Tool to enhance SRCC (Strikes, Riots and Civil Commotion) risk assessment.

The model provides insights into crowd size and behaviour during riots or large gatherings.

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This analysis supports our team in preparing for civil unrest scenarios with data-driven insights to evaluate exposure effectively.

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Our tool is the first step towards creating a probabilistic framework for IQUW’s SRCC risk assessment. In future, we will incorporate probabilistic methods to refine our risk predictions, enabling us to anticipate and prepare for an even broader range of possible events.

Crowd Model Development

We’ve built an initial crowd footprint model to simulate how crowds move during civil unrest events such as protests, strikes, and riots. This forms the analytical core for understanding unrest dynamics.

Probabilistic Method Rollout

Building on the footprint generated by the crowd model, we’re introduce a probabilistic simulation layer. For every simulated event, we build a corresponding loss distribution to estimate potential impacts. These distributions capture property damage and are customisable by event intensity, or region. This allows us to not only model where and when events may occur, but also what their likely consequences are.

Expand Event Coverage

The model can capture a wide range of civil occurrences. The result is a more comprehensive, forward-looking understanding of civil unrest and its ripple effects.

Explore our products that offer SRCC cover

Direct & Facultative Property Find out more

Political Violence & Terrorism Find out more

Better modelling means
swifter underwriting decisions.

THE METHOD

How does the model work to analyse risk to nearby infrastructure?

WE LEVERAGE

We leverage open-source street network data

WE BUILD

Then build a mesh-work to analyse potential crowd density limits

WE ANALYSE

We widen the mesh’s footprint to review the impact were a crowd to spill to a wider area

WE OVERLAY

We overlay with existing coverages to understand portfolio impact

WE LEVERAGE

We leverage open-source street network data

WE BUILD

Then build a mesh-work to analyse potential crowd density limits

WE ANALYSE

We widen the mesh’s footprint to review the impact were a crowd to spill to a wider area

WE OVERLAY

We overlay with existing coverages to understand portfolio impact

THE BENEFITS

Approximates crowd footprint area

Enables calculation of an approximate area a crowd occupies on a street network, revealing its potential impact on surrounding areas.

Identifies building risk

Automatically highlights buildings within a defined proximity to the crowd, categorising them by risk levels based on distance and exposure.

Provides customisation and scenario analysis

Adjusts parameters like crowd size, or can simulate unrest across multiple locations, helping to model complex, real-world scenarios with precision.

Supports swift underwriting decisions

The model is fast and efficient, generating a static footprint in seconds.

CASE STUDY

Let’s look at a real-world example – the 2021 Capitol Riots. The model’s capabilities are highlighted through this real-world scenario, demonstrating how it assesses risk and exposure.

The Impact on Critical Infrastructure

In this example, the insurer covers a metro station one block from the Capitol, which could become unusable and more vulnerable to damage during such an event.

By integrating advanced crowd dynamics data into underwriting, IQUW’s enhanced SRCC exposure model provides deeper loss insights. This innovation enables informed decision-making, early identification of high-risk properties, effective risk mitigation, and tailored coverage solutions.