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A slight change of 2% when modeling the likelihood of suffering from a cyber event can cause up to 30-40% increase in an annual overall loss.
A core aspect of Kovrr’s cyber risk modeling data pipeline combines unique data sources to better inform the model.
Kovrr distinguishes between systemic, targeted, and attritional events in the model and creates a separate event catalog for each type.
Kovrr has created slides to ease the process and assist other stakeholders’ buy-in journey.
Kovrr uses a Monte Carlo simulation in which the following year is simulated 10,000 times.