The scale and cost of cyberincidents have risen dramatically. In fact, according to Cyentia Institute, since 2008, attacks have become 7.5 times more frequent and 15 times more expensive, reaching a median cost of US$3 million.1 While not every breach leads to business insolvency, the upward trajectory reflects how serious cyberrisk has become for modern enterprises.
Confronting this trend and recognizing the central role cybersecurity now plays in market stability, regulators worldwide have introduced legislation that attempts to reshape how organizational stakeholders govern and manage their cyberexposure. Mandates such as the NIS 2 Directive from the European Union, for instance, place direct accountability on top leadership to both oversee and, more critically, understand and approve cyberrisk management strategies.2
This elevated standard of executive responsibility reflects a broader transformation in corporate governance practices. Regardless of whether an organization is indeed subject to one of the new ordinances or not, stakeholders worldwide are beginning to recognize that board-level involvement with cybersecurity matters has become a baseline expectation for maintaining investor trust and long-term competitiveness.
Still, much of the executive engagement taking place remains limited in depth. Boardrooms may now be in more regular contact with governance, risk, and compliance (GRC) teams, but the substance of these interactions is dependent upon traditional, spreadsheet-based risk registers built for documentation rather than fostering insight.
These registers typically rely on subjective likelihood and vague categorization labels, diminishing the ability to evaluate risk in concrete terms. As a result, communication stalls and there is often no real understanding amongst leaders regarding which cyberloss scenarios pose the greatest threat, which mitigation strategies will yield the most impact, or how to optimize cybersecurity resources in general.
The Operational Shortcomings of Traditional Cyberrisk Registers
Traditional registers persist in part because the pace of change in the cyber GRC field has outstripped the evolution of available tools and in part because they continue to satisfy core business needs such as audit readiness and structured reporting. In today's environment, however, that legacy is no longer sufficient to support modern GRC teams who are expected to deliver high-level, strategic value.
Even if kept meticulously updated, these risk registers only offer limited support. Their structure does not allow for consistent comparisons across operational areas, nor does it provide a reliable mechanism for evaluating how specific mitigation efforts will affect the organization's exposure. Most critically, they fail to incorporate objective risk modeling, leaving leadership without clear answers about how certain scenarios might translate into revenue loss or regulatory penalties.
Without such capabilities, traditional registers contribute very little to the types of cross-functional discussions that GRC leaders are increasingly expected to facilitate. Consequently, communication with executives remains fragmented and shallow, and, although officially presented in the boardroom, cyberrisk continues to be treated as a siloed issue rather than an essential business concern.
Until cyberrisk registers evolve to adopt the more tangible language used to describe enterprise value, they will remain static documentation tools that are useful for compliance but inadequate for advancing organizational goals.
The CRQ Upgrade: Turning Logs Into Leverage
The gaps may be significant, but they are not insurmountable. On the contrary, immediate progress can be made by integrating quantification models into the risk register, allowing for objective and repeatable loss scenario analysis. Cyberrisk quantification (CRQ) solutions that continuously ingest threat intelligence and have access to insurance-grade data specifically offer GRC teams a methodology that can assess relative exposure levels in financial terms, allowing risk to be classified according to urgency and communicated based on its tangible implications.
Unlike the more conventional approaches used to measure and communicate risk likelihoods and impacts, such as risk matrices, CRQ platforms employ advanced statistical models to translate complex threat and organizational data into probabilistic loss ranges that more accurately capture both the frequency and potential severity of events. This enhancement replaces deterministic, subjective scoring and vague classifications with an objective, data-driven view of business exposure.
Moreover, augmenting risk register workflows with continuously updated CRQ enhances their practicality exponentially across the enterprise. When risk scenarios are expressed in financial terms, such as an annualized likelihood of a US$5 million loss due to a ransomware event, they become more accessible to other executives, including the chief financial officer (CFO) and the organization’s head of legal, regardless of their technological expertise, fostering greater transparency that results in optimized governance.
Incorporating CRQ into the register also ensures that cyberrisk is no longer filtered solely through a technical lens. The enterprise-oriented framing equips GRC teams to shift the conversation away from control implementations for compliance and toward more actionable cost-benefit analyses, thereby creating the conditions necessary for senior leadership to be actively engaged in cyberrisk management and ensure it is embedded within the ERM strategy.
Until cyberrisk registers evolve to adopt the more tangible language used to describe enterprise value, they will remain static documentation tools that are useful for compliance but inadequate for advancing organizational goals.Implementing CRQ In Practice
For organizations ready to upgrade their cyberrisk registers with quantification, the most effective implementations follow established practices from the broader risk management discipline. The foundation of this process starts with a structured, scenario-based approach that defines the distinct loss events the organization could realistically face. From there, GRC leaders can determine the variables that influence the scenarios' likelihoods and impacts and then apply a repeatable modeling process that quickly generates results in financial and operational terms.
Some teams will take a gradual, manual approach to incorporating CRQ, combining internal data with external intelligence and subsequently applying statistical methods to develop quantified scenarios over time. Others opt for software as a service (SaaS) platforms designed to operationalize these steps at scale within the register, similarly equipping users to create custom or select commonly known loss scenarios, run probabilistic models, and view the forecasted financial and operational implications within minutes.
While both approaches move an organization toward quantification, only the latter option of integrating with a SaaS-enabled CRQ solution makes it practicable to keep registers continuously updated with organizational and threat data, as it will apply objective modeling techniques that reflect the full range of possible outcomes and ensure quantified results are readily available during governance discussions. When structured in this way, the register becomes a decision-supporting resource that helps stakeholders link cybersecurity programs to broader business objectives.
Making GRC Actionable at the Executive Level
Once cyberrisk has been quantified, illuminating event likelihoods and potential operational and financial consequences, and the data has been integrated into the risk register, the tool’s role within the organization changes entirely. Instead of being a convoluted document that the board does not have the time to examine in detail, it becomes a solution that facilitates high-stakes trade-off analysis and better-informed capital allocation.
For example, imagine stakeholders at a global financial services institute who want to understand the potential losses they face due to a data breach driven by a phishing scam. Without the quantified outputs, the risk might be communicated as "high" and supplemented only with vague assumptions that describe the reputation impact or monetary implications. With a CRQ-powered cyberrisk register, however, the GRC team can clearly identify that the scenario has an annual occurrence likelihood of 10% and an average loss expectancy of US$ 190,000.
Leveraging this objective data, the leadership team then weighs it against the 2 mitigation strategies that are available to them: expanding phishing simulation training at the cost of US$ 20,000 to reduce these exposure levels by 30% or deploying a behavioral threat detection system priced at US$2 million that, while demonstrably effective, only reduces forecasted financial losses by 5%. The CRQ model reveals that while both options minimize damages, the training program is more cost-effective and better complements fiscal priorities.
This form of structured, defensible decision making is precisely what regulations, such as NIS 2 and the US Securities and Exchange Commission (SEC) cybersecurity disclosure rules, have begun to prescribe.3 In 2023, public enterprises in the United States were required not only to disclose material cyberincidents (the facet of the regulations most publicized) but also to relay the specific mechanisms used for risk oversight and board involvement. A risk register powered by CRQ models equips organizations to meet this standard, providing traceable data-backed reasoning for how risk is prioritized and governed.
Perhaps most consequential, the upgraded quantified register reframes the nature of the GRC function, transitioning it away from its traditional compliance silo and ensuring it delivers enterprise-wide strategic value. When GRC leaders present cyberrisk and relevant issues in terms that better facilitate business decisions, they emerge as key partners that actively contribute to building the organization's resilience and long-term performance.
A Cyberrisk Register Reimagined for Resilience
As regulatory mandates intensify and cyberthreats exert broader financial and operational pressure, the limitations of conventional cyberrisk registers have proven themselves to be increasingly counterproductive to building organizational resilience and strategic alignment. Spreadsheet-based, qualitative tools may be simple enough to fulfil audit requirements, but they offer very little in terms of information capital deployment or executive oversight.
The inclusion of cyberrisk quantification addresses these shortcomings by furnishing the risk register with analytic, data-driven rigor. CRQ models allow GRC teams to rank loss scenarios according to their financial impact and likelihood, map them against the organization's risk appetite, and develop cost-effective mitigation strategies. In short, the quantitative information allows organizations to prioritize the initiatives that will have the greatest impact and defend these decisions with confidence.
With its advanced capabilities, the CRQ-powered cyberrisk register turns into a strategic instrument that fuels smarter enterprise governance. It enables GRC leaders to help the organization meet regulatory expectations and position cybersecurity as a driver of operational and financial resilience, affirming cyberrisk management's role as a critical business function that multiplies long-term value.
Endnotes
1 Cyentia Institute, Information Risk Insights Study (IRIS), 2025
2 European Commission,”NIS2 Directive: Securing Network and Information Systems”
3 U.S. Securities and Exchange Commission (SEC), “Cybersecurity Risk Management, Strategy, Governance, and Incident Disclosure,” USA, 5 September 2023
Yakir Golan
Is the CEO and co-founder of Kovrr. He started his career in the Israeli intelligence forces. Following his military service, he acquired multidisciplinary experience in software and hardware design, development and product management. For the past few years, he has been focused on bringing cyberrisk management solutions based on advanced machine learning and artificial intelligence to the market. He holds a BSc in electrical engineering from the Technion, Israel Institute of Technology and an MBA from IE Business School, Madrid, Spain.