Office Hours with Jack Freund, PhD - Monthly Product Review - February/March 2024
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The Era of Operationalizing Cyber Risk Quantification
Gaining the Necessary Cyber Data
When leveraging statistical models, there needs to be enough data. Although in its early stages, much of this essential data was missing, today, on-demand cyber risk quantification solutions have access to millions upon millions of data points. Over the past few decades, cyber risk analysts have acquired insurance intelligence, benchmarks, and event frequencies, continuously feeding the models for accurate outputs.
Leveraging CRQ Outputs Strategically
The more data available, the more accurate and precise model outputs are. The latest adaptations of on-demand cyber risk quantification tools, therefore, offer targeted information that can be harnessed during the stratification process and ensure resources are invested into the most vulnerable cyber risk areas. Cybersecurity leaders can feel confident in the choices they make regarding mitigation prioritization.
Exploring Cyber Loss Exceedance Curves
On-demand cyber risk quantification platforms like Kovrr's take into account an organization's unique characteristics to produce an aggregated loss exceedance curve. This curve illuminates the range of loss severities a company may experience due to cyber activity along with the likelihood. For example, the loss exceedance curve may reveal that a business has a 21% chance of experiencing a loss of $40 million.
Discovering Cyber Risk Drivers
Kovrr's cyber risk quantification solution, as showcased by Dr. Freund, illuminates the attack vectors most likely to be exploited in a cyber event. Our CRQ models quantify this information by running Monte Carlo simulations. Based on the results, cyber risk managers can understand the vulnerabilities, such as human error, that are most likely to lead to a damaging incident.
Evaluating Cyber Risk Over Time
Keeping track of how an organization's cyber risk posture evolves is not only important, but it can also serve as a valuable metric for demonstrating success. Kovrr's CRQ solution comes equipped with the Cyber Risk Progression feature, which documents this progress. Dr. Jack Freund explains how and why these metrics change over time and how our models are adjusted based on the current risk landscape.
Office Hours February/March 2024 FAQs
Speak to an Expert to Learn MoreHow accurate are Kovrr’s models’ outputs and financial forecasts?
What are the actionable cybersecurity insights I can glean from CRQ?
How can I learn more about the cyber insurance evaluation feature?
How do the Monte Carlo simulations work to produce a loss curve?
Want to Know More About Kovrr’s Data Calibration and Validation?
Kovrr conducts extensive validation and calibration tests to ensure our CRQ models maintain the highest-quality outputs. We employ a top-down approach involving backtesting, sensitivity testing, benchmarking, and change analysis. Want to learn more about this process?
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