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Model Quality Overview

Model Development Controls, Testing, and Validation

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Continuous Model Validation and Calibration for High-Quality Outputs

Learn more about how the Kovrr team validates and calibrates its CRQ models to ensure organizations receive accurate and precise forecasts. Watch now!

Importance of Model Quality

Cybersecurity risk modeling is the process of creating a variety of potential risk scenarios due to an organization’s cyber activities, assessing the likelihood and severity of each, and then quantifying the potential impacts if the scenario occurs. Leveraging a robust model is key when creating cyber mitigation strategies, as simple approaches are likely to render inaccurate results that obscure vulnerabilities.

Model Testing Processes

To ensure the accuracy of Kovrr's data modeling, inputs, and calculations, our team employs a top-down approach to testing our models. This process checks that the models generate realistic scenarios that an organization is likely to experience in the upcoming year so that executives can generate a risk management strategy that is reflective of the current risk environment.

Output Validation Approaches

Kovrr also applies model calculation testing and validation throughout the development process, which involves a series of automated tests to confirm that each aspect of the code has been implemented correctly.

Additionally, if a model change is proposed, the change to operations is first codified in a specification and reviewed internally to ensure high-level accuracy.

Exclusive Loss and Data Intelligence

Kovrr has exclusive access to large-scale insurance intelligence loss data and offerings, capturing an extremely broad range of scenarios and impacts to ensure the accuracy and precision of an organization's risk forecasts. Moreover, Kovrr's models have been validated and calibrated across 5 million companies, bolstering our models' outputs and data modeling capabilities.

Continuous CRQ Model Updates

Kovrr continuously validates and calibrates in models, nurturing a CRQ environment that can react quickly to any developments within a rapidly evolving cyber risk landscape. Moreover, this pragmatic approach allows our risk modeling experts to maintain a high level of confidence in the results, equipping CISOs with the forecasts necessary for building an accurate risk management framework. 

Kovrr’s Model Quality Overview FAQs

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What are the main components used to maintain CRQ model quality?

What are the controls and validation tests for the input and data pillar?

What are the controls and validation tests for the model calculations pillar?

What are the controls and validation tests for the outputs and results pillar?

Start Prioritizing Model Quality in Cybersecurity Risk Management

Modeling cyber risks is a crucial component of developing a robust cyber risk mitigation strategy, but not all modeling processes are reliable. Contact one of Kovrr’s cyber risk modeling experts today to learn more about our robust approach.

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