With so many threats facing modern companies, knowing which threats to address first can be challenging. Risk quantification is a technique that assigns a numerical value to threats, so you can prioritize issues that are most likely to occur or cause the most significant harm.
This method does not work for all cyber attacks. Quantifiable risks can be expressed in monetary value (say, lost profits), while non-quantifiable or qualitative risks are more anecdotal. A quantitative risk assessment (QRA) can help you figure out what risks your business faces and how to measure them.
While risk quantification originated in the financial sector, it’s becoming increasingly common in cybersecurity. Risk quantification can be a beneficial strategy for many security teams. Knowing the pros, cons, and best practices will help you determine whether it’s viable for your organization.
Why Is Quantifying Cyber Risk Important?
Quantifying risk can be a valuable exercise for many organizations. For starters, standard metrics are a great way to explain your risk landscape to C-suite executives and other stakeholders.
As your firm grows and expands, this information can be helpful for financial planning, mergers, and questions about cybersecurity investment. In addition, having a “single language” to communicate your company’s risk mitigation activities to all employees is always a good idea.
Moreover, publicly traded companies in the United States must now disclose their approach to cyber risk management in their annual reports, to show investors that the company is indeed trying to tame cyber risk. Risk quantification is one such approach. Disclosing a short summary of it in your annual report can help with regulatory compliance obligations.
Quantifiable data also allows you to chart your progress on risk management over time. With this data, you’ll have definitive proof of whether your risk management efforts are sufficient and your cost estimates are correct. Data doesn’t lie; it will be valuable for creating your risk register and developing a successful risk management plan at your company.
How Do You Quantify Cyber Risk?
Risk quantification in cybersecurity is a burgeoning field, and establishing best practices can be challenging. Assessing the suitability of risk quantification for your company involves several steps. Among them:
Use a model that meets your needs
Any quantification model your firm employs will attempt to assess the amount of damage each cyber risk could cause, referred to as “value at risk” or VaR. That said, various approaches exist to model risk and arrive at your desired datasets. Carefully consider the differences among these models when creating your risk assessment matrix.
For example, one common model is the Monte Carlo analysis (or Monte Carlo simulation), which allows you to explore all possible outcomes of a specific risk. Other models exist as well, and you should select one with the methodology that suits your business and facilitates decision-making.
Understand that quantifying risk is only the first step
The primary benefit of quantification is the ability to rank your most significant risks by dollar value, which allows you to prioritize security efforts accordingly. Don’t ignore that prioritization part.
Use your quantitative risk analysis predictions and associated metrics to create a cyber risk management program that correctly allocates your resources and gives you the most vigorous possible defense in the fastest possible time frame.
Communicate risk throughout your organization
Risk reduction efforts, cybersecurity audits, and overall management processes are most successful when fully integrated throughout the organization. Once you’ve determined which risks are the most critical, you need to make sure everyone at your company — across all operating units, from top to bottom — understands that information.
All employees can make more informed decisions day-to-day when business leaders regularly present risk metrics, risk scenarios, and financial impacts.
Challenges of Risk Quantification
Cybersecurity risk quantification can be a complicated initiative. The effort can be expensive, and some organizations don’t have the resources to execute the assessment process properly.
The technique also has some drawbacks. For example, one might be tempted to depend on proven data and formulas, which can result in false correlations and equivalencies that misdirect your security efforts. Also, the data collection used for quantification is based on past events. As such, it can’t always account for new risks that may arise in the future.
This rigidity may prevent you from understanding the whole picture and result in misplaced complacency. Focusing too much on predicting likely loss events can result in a “black swan event” — a statistically unlikely event with repercussions more severe than you expected.
To that end, remember the value of qualitative risk assessments and the need to identify emerging risks. Threat actors and hackers are increasingly skilled and clever. It’s critical for security leaders to also be innovative and forward-looking to avoid data breaches and protect the company’s data.
Steps for Improving Cyber Risk Quantification
Companies that have mastered cyber risk quantification usually have one thing in common: they understand how to integrate their cyber risk model with their enterprise risk model and overall data-driven risk management. When cyber risk quantification fails to produce results, it’s usually because this integration is insufficient or some basic capabilities are missing.
The following five mutually reinforcing characteristics pave the path to more accurate cyber risk estimation.
1. Start with governance
The organization needs a consistent, enterprise-wide approach to handling cyber threats as the business grows over time. This is achieved through governance. First, define an operating model that aligns with the company’s risk appetite and goals. Then create functional groups to address cyber risk and compliance; that includes defining roles and responsibilities to manage risk and oversight committees to assure that cybersecurity operations are keeping pace with evolving threats and compliance duties.
2. Formalize cyber risk monitoring
If you want to rely on data-driven decision-making, you must have good data and review it regularly, so establish a structured, repeatable procedure to monitor cyber risk data. Monitor key performance indicators (KPIs) and create a reporting structure for the board of directors or risk committees based on customizable criteria.
3. Risk classification
You must first identify and characterize cyber hazards before you can quantify them. After that, work with stakeholders together to align priorities. Then you can implement necessary internal controls more easily.
4. Accelerate the evaluation process
Evaluating risk correctly depends on discipline and rigor; use a cybersecurity risk framework to achieve that level of performance. The most popular security frameworks come from the National Institute of Standards and Technology (NIST), and other frameworks are widely available as well.
Following a framework will allow you to develop accurate, consistent risk management plans for the entire organization, and it will pave the way for automation of risk management processes, too.
5. Embrace technology
Risk management software tools combine data and disparate risk management tasks for a more holistic, data-driven program. These tools integrate your quantitative and qualitative data for comprehensive risk assessments and reports on overall risk exposure.
What Is the FAIR Model for Cyber Risk Quantification?
The FAIR Risk Model, developed by the FAIR Institute and recognized as an international standard by the Open Group, is a tool for organizations to evaluate cyber risks unique to their operations. This model, rooted in quantifiable risk analysis, uses statistical methods to estimate operational risks in a clear and measurable manner.
The primary goal of the FAIR framework is to deconstruct risk into distinct factors that can be measured and understood as probabilities. By examining specific risk scenarios and pinpointing relevant data for quantification, organizations can gain insights into the relationships between these risk factors.
Unlike predictive models, the FAIR model takes a probabilistic approach. It defines risk as the likely frequency and magnitude of future losses, focusing on a combination of Loss Event Frequency (LEF) and Loss Magnitude (PLM). This perspective ties the occurrence and impact of a loss to a particular asset.
According to FAIR, identifying assets and their values is pivotal for risk assessment. Assets are any valuable organizational elements, such as devices, data, or other components susceptible to losses. These losses can take various forms, including:
- Productivity setbacks
- Money spent responding to risks
- Asset replacements
- Damage to reputation
- Loss of competitive advantage
- Legal judgments and regulatory penalties
In the FAIR framework, any event or circumstance with the potential to harm an asset and trigger any of the aforementioned losses is termed a “threat agent” or “threat community.” This includes situations such as natural disasters or malicious attacks. Through this comprehensive approach, the FAIR Risk Model provides a structured way for organizations to better understand and assess their cyber risks.
Best Practices for Cyber Risk Quantification for the Future
In the fast-evolving digital landscape, staying ahead of cyber threats requires a strategic approach. Here are some smart practices to consider when quantifying cyber risks for the future.
Create comprehensive risk profiles
Crafting detailed risk profiles is akin to making a map before setting off on a journey. You have to identify your organization’s unique vulnerabilities and potential points of attack. By understanding where your weak spots are, you can develop targeted defenses that safeguard your digital assets more effectively.
Build an objective list of cybersecurity definitions
Clarity is key in cybersecurity. Jargon and vague terms can lead to confusion, which can prove costly. By establishing a clear and concise list of cybersecurity definitions, you assure that everyone in your organization speaks a common language when discussing potential risks. This minimizes misunderstandings, and mitigation steps can be taken confidently.
Assign criticality ratings
Not all risks are created equal. Some vulnerabilities could lead to minor inconveniences, while others might result in severe breaches. To prioritize your efforts, consider assigning criticality ratings. This lets you focus on the most significant risks first, helping you allocate resources where they matter the most.
Document your efforts
Documenting risk quantification lets you track your progress, review your decisions, and learn from your experiences. This documentation becomes a valuable reference point, helping you refine your approach over time and keeping key decision-makers in the loop.
Focus on the biggest cyber threats
In a sea of potential risks, it’s essential to identify the sharks. Concentrate on the most significant cyber threats that could have the most substantial impact on the organization. By dedicating your attention and resources to these major threats, you create a robust defense strategy that’s built to withstand tomorrow’s challenges
Protect Your Business from Cyber Risks with ZenGRC
If you’re unsure how to implement risk management within your company’s cybersecurity program, the RiskOptics ZenGRC Platform can help. Integrate your quantitative and qualitative risk management initiatives to make informed decisions based on real-time contextual insights.
Get off to a quick start with ZenGRC guided set-up process and a built-in library of frameworks. Automated workflows, risk scoring, and metrics give time back to your teams by eliminating manual, tedious tasks. It also delivers actionable insights and visual dashboards to prioritize investments and stay ahead of hackers, improving security posture.
Schedule a demo today to see how the ZenGRC Platform can help you create a cyber risk management program that works for you.