Cyber

OverVue™

Cyber OverVue™ is an analytics solution used to quickly evaluate cyber loss profiles through a comprehensive scoring system.

 

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Looking for a more effective, data-driven solution to help evaluate the cyber risk of an organization?

Cyber OverVue™ provides actionable intelligence.

  • Quickly evaluate cyber loss profiles through comprehensive scoring system
  • Understand frequency and severity drivers based on historical cyber losses
  • Enhance cyber insurance pricing based on the loss experience of an organization and its peers
  • Improve underwriting performance and profitability
  • Justify coverage recommendations and illustrate potential losses

HOW DOES CYBER OVERVUE WORK?

Users select a company (or industry and revenue range). OverVue generates three scores for frequency, severity, and insurance program benchmarking, where higher scores indicate higher risk profiles.

frequency-severity-benchmarking

Delve deeper into each of these scores with just one click to reveal the underlying details.

cyber-overvue-charts-2017-10-06

A series of charts and tables provide different views of the loss experience. Each analysis also displays the five most recent losses for the selected company or peer group.

FREQUENCY

The first chart, Industry Overview, displays a high-level comparison of the average number of incidents for the selected industry, as compared to all industries across various revenue ranges. Three additional charts—Type of Incident, Type of Loss, and Time Period—display the average number of incidents for the selected company, as compared to the average number of incidents experienced by its peer group.

SEVERITY

The Severity section features the same charts as Frequency—Industry Overview, Type of Incident, Type of Loss, and Time Period—analyzing the average number of records affected, as opposed to the average number of incidents.

BENCHMARKING

Charts provide context regarding how the cyber insurance program (premium, limit, retention) compares to its peers.

cyber-overvue-benchmarking

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