The rise of active assailant risk is no longer a fringe concern in political violence portfolios.
It is becoming one of the most complex and pressing challenges facing specialty underwriters today.
In a recent episode of The Political Risk Podcast – geopolitics, insured, hosted by David Benyon, Concirrus’ Gamze Tekin joins Joshua Watson, Senior Underwriter at Markel International, to unpack how this peril is evolving and what it demands from underwriting.
This is not just another emerging risk. It is a shift in how risk itself behaves, and how it needs to be understood. Increasingly, this is driving demand for AI-native underwriting platforms that can process data, assess risk, and support faster decision-making.
Active assailant risk refers to targeted, human-driven attacks that are typically smaller in scale than traditional terrorism events, but more frequent, less predictable, and often high in impact.
A Peril That Doesn’t Behave Like the Others Active assailant risk sits uncomfortably within traditional political violence frameworks.
Unlike large-scale terrorism events, it is:
- More frequent
- Less predictable
- Often smaller in scale, but high in impact
- Driven by different motivations and triggers
This creates a disconnect. Traditional underwriting approaches, built around historical events and physical damage, struggle to keep pace with a risk that is dynamic, human-driven, and increasingly localised.
The podcast explores this tension in depth, highlighting how underwriters are being asked to assess something that does not follow the same patterns as legacy perils.
The Data Problem Is the Underwriting Problem One theme comes through clearly. The challenge is not just the risk itself.
It is the lack of usable, structured, and timely data.
Active assailant risk exposes several gaps:
- Limited historical datasets to model frequency and severity
- Difficulty quantifying non-damage business interruption
- Challenges in understanding human and behavioural triggers
- A lack of real-time visibility into exposure and aggregation
This aligns with broader market findings. Political violence is becoming more frequent, more varied, and harder to define, with traditional approaches increasingly seen as outdated .
In short, underwriters are being asked to make decisions with incomplete information, on risks that are evolving faster than their tools.
Aggregation and Exposure Are Getting Harder
to Control One of the most critical challenges discussed is aggregation.
Active assailant events may be smaller individually, but their frequency introduces new portfolio-level risks. Multiple incidents across locations, sectors, or timeframes can create unexpected accumulation.
This raises difficult questions: how do you monitor exposure across a distributed portfolio, how do you identify hidden concentrations of risk, and how do you price for events that are not easily modelled without real-time exposure management?
- How do you monitor exposure across a distributed portfolio?
- How do you identify hidden concentrations of risk?
- How do you price for events that are not easily modelled?
Without real-time visibility, these risks remain hidden until they materialise.
Regulation and Demand Are Moving in Parallel The rise in incidents is being matched by increased scrutiny and regulatory pressure, particularly in the US.
At the same time, corporate buyers are becoming more aware of their exposure. Protection gaps are widening, especially where traditional policies fail to respond to non-physical losses.
This combination is driving demand for:
- Broader, more responsive cover
- Better risk understanding
- Faster underwriting decisions
It is also accelerating the need for tools that can support this shift.
From Static Underwriting to Real-Time Decisioning The final part of the discussion focuses on what needs to change.
The answer is not incremental improvement. It is a move towards real-time risk visibility, data-driven decisioning, and AI-enabled workflows, often delivered through an underwriting workbench that connects data, exposure, and decision-making in one place.
- Real-time risk visibility
- Data-driven decisioning
- AI-enabled underwriting workflows
- Portfolio-aware underwriting, not just individual risk assessment
This is where the industry is heading.
Underwriting can no longer rely solely on static datasets and retrospective analysis. It needs to operate with live signals, connected data, and the ability to adapt as risk evolves.
Why This Matters Now Active assailant risk is not an isolated trend. It is part of a broader shift in political violence and specialty risk.
Events are becoming:
- More frequent
- More decentralised
- More complex in their impact
At the same time, expectations on underwriters are increasing. Faster response times, better pricing accuracy, and stronger portfolio control are no longer optional.
The gap between risk and underwriting capability is widening.
Closing that gap will define the next phase of specialty insurance.
