Cyber risk remains a top concern and key opportunity for insurers. However, many have little or no cyber risk data in-house and lack the ability to manage the risk effectively. The latest version of ARC, AIR’s cyber risk analytics and modeling platform, features AIR’s new probabilistic cyber model to support analysis of individual risks and insurance portfolios. Test views of risk, optimize strategies, and make more informed cyber risk management decisions with ARC.

Machine learning identifies drivers of cyber loss

AIR analyzed more than 77,000 cyber incidents sourced from public records and insurance claims to obtain a robust view of the risk associated with security breach and cloud service provider downtime incidents. With detailed data on the firmographics and technographics of businesses at risk, AIR applied machine learning techniques to identify the exposure attributes that have the greatest impact on probability of loss.

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Manage cyber risk globally

The cyber insurance market is growing beyond the United States to regions such as Europe, Australia, and Japan. The latest version of ARC expands the international component of its cyber industry exposure database by more than 40,000 organizations and includes both company-specific and regional industry average exposure data for organizations across the globe.

Watch the on-demand webinar for an overview of the model and a demo in ARC

Optimize the underwriting of attritional Risks

The AIR Probabilistic Cyber Model enables you to understand and quantify the risk from cyber security breaches, which have historically been one of the most frequent types of cyber incident. Underwriters can leverage the model’s unique ability to differentiate risk to improve their risk selection and identify the policy terms that deliver the best returns, while staying within risk appetites.

Manage portfolio tail risk

The widespread adoption of cloud computing services creates a major source of systemic risk that could cost the global economy billions in business interruption losses if a major downtime incident were to occur. Portfolio managers can use the AIR Probabilistic Cyber Model to quantify how some cloud providers are riskier than others and how systemic incidents can impact their book of business.

Rethinking systemic cyber risk—an approach for growth

Stay ahead of the rapidly evolving cyber risk landscape

Technology advancements, new regulatory regimes, and other factors are creating a shifting risk landscape that requires insurers to continuously test views of risk. Explore the drivers of loss by exposing the underlying metadata (including the complete catalog of simulated events, the technographic data used to differentiate risks, and the industry-specific vulnerability factors), and implement your own view of risk by adjusting key modeling parameters with ARC’s transparent and flexible framework.

Streamline your modeling workflow

The latest release of ARC includes several workflow enhancements designed to allow you to better focus on analyzing cyber risk and interpreting model results. Now you can automate ARC workflows. Other enhancements include improved exposure management functionality and new job management and reporting features.


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