Cyber insurance policies are difficult to evaluate without knowing how much cyber risk your organization carries. Quantifying your top risk scenarios and mapping those to the loss types in your policy gives you a concrete picture of whether your coverage adequately transfers your cyber and technology risk. It also equips CISOs to communicate risk exposure clearly to the teams responsible for procuring insurance.
Quantifying your loss exposure by scenario and loss type gives you the ability to evaluate whether your policy matches your risk profile. It highlights coverage gaps and where exclusions may leave the organization exposed, and creates a shared language between CISOs, risk managers, and the teams negotiating with brokers and insurers. Instead of relying on market benchmarks, you tie coverage decisions directly to your own risk data.
C-Risk uses FAIR and the FAIR Materiality Assessment Model (FAIR-MAM™) to quantify your cyber loss exposure by loss type to be able to map it against your current policy or a new policy. This gives you a clear view of where coverage aligns with your risk scenarios and where it falls short, so you can make informed decisions about limits, exclusions, and renewal terms.
Define the risk scenarios that matter most to your organization and review your current cyber insurance policy.
Quantify probable loss across your priority scenarios using FAIR-MAM™, breaking down exposure by loss type to match how insurance policies pay out.
Map your quantified loss exposure against your current coverage to identify where the policy adequately transfers risk and where gaps or overlaps exist.
Deliver financially justified coverage recommendations that support renewal negotiations and align your insurance strategy to your risk appetite.
Better coverage starts with a quantitative approach to understanding your risk. Measure your loss exposure, map it to policy terms, and move from assumptions to evidence.
A quantified understanding of your loss scenarios gives you the evidence to evaluate your policy, close coverage gaps, and negotiate terms that match your risk appetite. C-Risk helps CISOs bring financial clarity to insurance decisions, so coverage reflects what the business actually needs.
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CISOs have the deepest understanding of the organization's threat landscape, control environment, and risk exposure. When they can contribute quantified risk data to the insurance discussion, coverage decisions are more likely to reflect the organization's actual risk profile. Without that input, policies are often shaped by broker recommendations and market benchmarks alone, which may not account for how the business actually operates or where its most significant exposures lie.
A cyber insurance policy may show a high aggregate limit, but that number can be misleading. Most policies apply separate sub-limits to specific loss types like business interruption, regulatory fines, or crisis communications. If your quantified risk scenarios show significant exposure in a loss category where the sub-limit is low, your effective coverage for that scenario may be far less than the headline figure suggests. Evaluating coverage per loss type against your actual risk exposure gives you a more accurate picture of how well the policy protects the business.
Most cyber insurance policies cover first-party costs such as incident response, forensic investigation, business interruption, data restoration, and crisis communications. They also cover third-party liabilities including regulatory fines, legal defense, and notification costs. However, policies vary significantly in their exclusions, sub-limits, and conditions. Common exclusions include nation-state attacks, failure to maintain minimum security standards, and losses related to unpatched vulnerabilities. Understanding these details relative to your own risk scenarios is essential for evaluating whether your coverage is adequate.
FAIR-MAM (Materiality Assessment Model) is an extension of the FAIR model that provides detailed loss magnitude analysis across ten primary loss modules, including business interruption, proprietary data loss, and regulatory fines. FAIR-MAM was built in collaboration with cyber insurers to align with generally accepted claims categories, making it particularly useful for mapping your quantified loss exposure to insurance policy terms.