Drawing from the Experience of Nat Cat Modeling
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Security Indicators

Generating Lift with Critical Factors

In an era and market environment where vast amounts of data and analytics are available, it is critical to cut through the noise and focus on signals which provide the strongest predictive power to aid portfolio underwriting and account pricing activities.

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In an era and market environment where vast amounts of data and analytics are available, it is critical to cut through the noise and focus on signals which provide the strongest predictive power to aid portfolio underwriting and account pricing activities.

This report presents the latest findings in CyberCube’s continuous effort to identify, understand, and improve the data and analytics we present to our clients.

The goal of this study is to provide insight into the relationships between a selection of cyber risk signals available within CyberCube’s single risk underwriting tool, Account Manager, their relationship to cyber incidents, establish which are most meaningful, and quantify the relative value of each.