September 5, 2023
This is the second of a two part series on highlighting the power of cyber risk quantification, based on a webinar hosted by Kovrr’s Director of Product Management, Amir Kessler. Part two delves into the transformative potential of converting cyber risks from financial insights to actionable plans. Watch the full webinar here.
If effectively communicating organizational cyber risk to the boardroom is your goal, then implementing a cyber risk quantification (CRQ) model into your governance plan can no longer be considered a luxury—it's a necessity.
Part 2 of this series will further unravel the complexities of CRQ and its integral role in translating your enterprise’s security risk to executives and stakeholders. Indeed, utilizing CRQ in your next risk assessment enables you to effectively bridge the gaps between cybersecurity, finance, and a positive ROI.
Finally, long-term operational business success becomes intertwined with cybersecurity initiatives. .
Nowadays, cyber risk is inevitable. But what is the likelihood of a breach occurring, and what could be the severity of the consequences? If you’ve taken the probabilistic approach to assessing risk, you may already have a number associated with the answers to both of these questions.
Perhaps you’ve used percentages to measure the likelihood and assign a level of 1 through 5 associated with impact. The result of your assessment would most likely be a risk matrix, or risk diagram, that you present to the board. You might even choose to calculate Risk Magnitude, which is commonly done by multiplying the Risk Likelihood by the Risk Severity.
But after you’ve created your risk matrix and factored in industry benchmarks, annual revenue, and other risk determinant variants, who will interpret the findings? Undoubtedly, it will be a human member of the cybersecurity team approaching the assessment with his or her unique expertise.
Unfortunately, one is likely to find that consulting with three separate people on the team yields three distinct conclusions. Indeed, multiple studies highlight the risk of using qualitative risk matrices, pointing out that they consistently produce arbitrary results.
In fact, in a cybersecurity podcast, cyber risk expert Alex Sidorenko, Group Head of Risk of SVMP, highlights one research report that discovered even the most experienced risk employees produced assessments with double the amount of errors than those amateur engineers who used basic quantitative risk models.
Moreover, communicating these final numbers and interpretations to boardroom members and other key stakeholders will also prove challenging. Without objective data to leverage, justifying your conclusions will be virtually impossible. Keep in mind that when reporting KPIs to those who approve budgets, you must communicate in a language the audience understands.
When your scores are based on a unique methodology, it can be extremely difficult to have others grasp their severity (or insignificance). You’ll most likely end up spending more time explaining your numeric assignments than advocating for your budget. When it comes to risk assessment, subjectivity proves to be a hindrance rather than a tool.
It’s no mystery why, despite its implicit biases, many security teams prefer the qualitative approach to risk management. The process is fast and easy and usually requires little operational support outside of the CISO’s domain. However, the benefits of this evaluation methodology simply do not outweigh the disadvantages.
Firstly, there's no way to know whether a risk mitigation strategy is cost-effective. When transferring quantitative assessments into actionable plans, gauging the impact likewise is a subjective interpretation.
For example, suppose your organization moves from a risk level of 3 down to a 2 after an initiative has been implemented. How would you measure if the impact of this decrease in risk outweighs the resource investment? The short answer is that there is no way to calculate this metric with qualitative analyses, which results in a frustrated C-suite looking to optimize resource allocation.
The second major drawback rendering the qualitative approach futile is that the results cannot be aggregated. In many cases, cyber events are correlated, with one affecting the other (i.e., if you have a ransomware attack, it increases your risk of data breach). But without the ability to add the "sum" of these risks together, your assessment won't reflect the risk reality.
This inability also proves problematic when bringing your findings to the boardroom. In general, board members want to know the bottom line: What is the overall level of risk for the company today? These high-ranking figures don't have time for an in-depth presentation that outlines every type of potential event type and its relative level of risk. They want a quick understanding.
At first, quantitative assessment may seem intimidating, which is why many organizations have still not adopted them. Delving deeper into the process reveals that it’s not as scary as it looks.
As long as there is reliable data, a shared confidence in the chosen methodology, and the right tool for analysis, the process is highly manageable. Plus, once these three key points have been mastered, the quantitative assessment is easily replicated at scale.
Quantifying cyber risks in financial terms is the cornerstone of good decision making, making it possible for boards to comprehend the monetary repercussions of probable cyber incidents. Armed with an in-depth cyber risk assessment, board members can react prudently, effectively allocate resources, and bring cybersecurity efforts into line with wider corporate aims. Best of all, they’ll understand how cyber risks will affect their relative organizational areas and start to view cybersecurity as an essential aspect of their own departments.
While qualitative methods offer a subjective understanding of risks, quantitative approaches introduce accuracy and precision. The transition from subjective evaluations to data-driven precision is paramount.
At the core of financial quantification resides data. To best simulate the financial consequences of cyber risks, an organization should gather as much objective, measurable data as possible..
It’s critical that the data be measurable because it needs to be trustworthy. Stakeholders look for clear processes that allow them to verify the accuracy of the information. Remember that while you report to the stakeholders, they also have players they need to report to, too. CRQ ensures accuracy, consistent results, and the reliability to instill confidence in anyone reviewing the assessment..
A pivotal juncture in the CRQ journey is the transformation of abstract risks into tangible financial values. A level 4 risk based on qualitative assessment doesn’t have the same value to stakeholders as a 20% possibility of a $50 million loss. The symbiotic relationship between data, methodology, and tools harmonizes to manifest financial insights from theoretical risks, illuminating what really matters to the C-suite and investors.
While we’ve discussed an overview of the methodology and data involved in the CRQ process, we haven’t covered the mechanism. What do organizations do with all that data after the collection process is complete? In the labyrinth of cybersecurity, CRQ platforms emerge as the answer..
But it’s important to choose the solution that can help bring the final calculations to light. Platforms like Kovrr’s offer visualizations that communicate cyber risks in universally understood monetary terms. In the related webinar, Product Director Amir Kessler displays Kovrr’s various pie and bar charts that highlight the difference a single mitigation effort could make in terms of financial savings. By bridging the chasm between technicalities and strategic discussions, CRQ platforms empower decision-makers with a comprehensive grasp of cyber risks.
If you need any more convincing that CRQ is the most cost-effective, practical solution to secure your enterprise, let's consider an illustrative example. Imagine estimating potential damage from a cyber event in financial terms. Leveraging probabilistic methods further enriches this process, allowing you to prioritize tasks as you tackle the more probable and significant risks first.
Need a quick sign-off on this decision? Visualization of the annual loss of the cyber event enables stakeholders to grasp the overarching ramification much more easily, putting everyone on the same page of what needs to be accomplished.Quantification becomes communication as CRQ converts the abstract into the palpable.
The transition from abstract risk scores to tangible financial estimates marks a pivotal shift in the cyber risk management sector. This transformation brings the language of risk into harmony with the wider conversation about fiscal consequences. By embracing financial language, cybersecurity teams empower themselves to convey the gravity of cyber risks with precision.
In an increasingly threatening digital landscape, the ability to quantify progress and exposure assumes paramount significance. CRQ equips organizations with a toolkit to objectively measure risk exposure and the effects of your security team’s reduction efforts. The quantified approach enables organizations to track their journey towards cybersecurity maturity, firmly grounded in monetary terms.
Upgrading cybersecurity is one of the smartest investments a company can make, both in terms of ensuring a more secure ecosystem and promoting a positive ROI. But communicating the financial returns can be challenging. How can a CISO prove that spending more money on security controls will lead to great savings?
One option is to leverage a cyber risk quantification tool with features that can specifically calculate the financial effect of increasing security levels within a given framework. For instance, when working with the CIS Controls Implementations Groups, there are three levels: IG1, IG2, and IG3. In the webinar, Kessler demonstrated that upgrading an organization’s controls from IG2 to IG3 would result in $97,106 in savings. In short, tighter security means less risk, which leads to less overall loss.
With a CRQ model, security teams no longer need to try to justify their risk mitigation efforts in confusing technical terms. Instead, they can use the quantification solution to explain their action plans, and, in the example above, show that a security update can reduce financial vulnerability by nearly $100,000. With only a few data inputs required, a CISO instantly has the ability to illuminate the financial power of creating a safer cyber environment.
Pleas for budget increases often encounter skepticism from the C-suite and boardroom members. However, when the CISO is armed with a projected ROI of nearly 400%, their argument suddenly becomes compelling, if not incredibly persuasive. This rapid transformation is the embodiment of CRQ's ability to transition abstract, subjective cybersecurity needs into quantifiable financial business gains.
Discussing cyber insurance is another area often riddled with complexities, marked by premium fluctuations and difficult policy terms. Cybersecurity is a relatively new component within an established industry, which typically results in high premiums that organizations have little choice but to comply with.
However, once armed with CRQ, these same organizations can better scrutinize policy terms through the lens of their financial risk exposure levels. For example, Kovrr’s process of Insurance Terms Stress Testing reveals coverage gaps and areas of redundancy, making policy discussions more aligned with the reality of an organization’s risk, rather than a situation based on irrelevant scenarios.
To illustrate this powerful feature within Kovrr’s CRQ platform, Amir Kessler showed an organization’s annual exposure within the framework of their insurance policy. In the webinar, we saw that the demo company’s policy only covers what’s in the dark purple, leaving the risk cost incurred in the light purple uncovered.
In addition to the visual, the platform also highlights crucial facts based on the initial risk assessment. For instance, there is a 5% chance that annual losses will exceed the aggregate limit and a 28% chance that annual losses will exceed the deductible. With this powerful information, organizations are now seamlessly able to adjust coverage parameters that more accurately mirror their quantified risk landscape, leading to more cost-effective policies.
CRQ's influence on cyber insurance transcends cost mitigation; it signifies a pivotal shift in approaching insurance as a strategic financial asset. Indeed, Kessler revealed, one of the main use cases at Kovrr is the reduction of insurance premiums through stress testing strategic goals. The solution has a myriad of ways of producing a great overall return on investment.
In the symphony of cybersecurity, CRQ's resonance echoes profoundly in boardrooms.
The ability to quantify cyber risks and translate them into financial terms marks a paradigm shift in risk management. With the marriage of data, methodology, and CRQ platforms, the once abstract realm of risk becomes tangible, paving the way for a future in which cybersecurity's language is spoken in financial terms.
Kovrr makes it easy to embrace CRQ, helping organizations stand poised to transform adversity into insight and uncertainty into strategy. Book a free demo with our team to get started today.
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Risk Progression feature empowers CISOs and CRQ users to inspect and understand the changes in their cyber risk over time.