Charting the Course: Using Data Visualization for Cyber Risk Management

Data-driven advisors can use Excel for risk analysis and risk assessment, highlighting how this ubiquitous tool can be employed to evaluate and manage various sources of cyber risk in an organization.

The usefulness of Excel and other business intelligence tools for risk management can involve more than just tables and formulas. Data visualization can inform critical cyber risk management decisions and even support intuitive understanding of how much is known and unknown about cyber threats and how to respond to them.

The Power of Data Visualization in Cyber Risk Management

Data visualization is an effective tool in the field of cyber risk management. It has the ability to transform abstract, complex, and otherwise unintuitive data into a format that is understandable, insightful, and actionable. By providing a visual representation of data, complex concepts and relationships can be grasped quickly and intuitively, allowing individuals across an organization – regardless of their technical expertise – to engage in meaningful discussions about cyber risk.

Different types of visualizations can serve distinct purposes. For instance, a pie chart may be used to show the proportion of different types of threats within the total risk landscape, while a bar graph could show the frequency or severity of specific threats. A line graph, meanwhile, could emphasize trends in the threat landscape over time. These examples are valuable ways to visualize data with a single quantitative variable. When dealing with two quantitative variables, such as in the case of inherent risk, a different approach is needed.

Inherent risk, in the context of cyber risk management, is typically characterized by two quantitative variables: the likelihood of a risk event occurring expressed as a probability and the potential impact of that event, financial or otherwise. Visualizations capable of expressing two or more quantitative variables, such as a scatter plot matrix or bubble chart, are particularly useful in this instance.

Scatter plots and bubble charts can be used to plot the likelihood of risk events on one axis and the potential financial impact on the other. Each risk event is represented by a point (or bubble) on the plot, providing a clear picture of where each event falls in terms of both likelihood and impact. This helps to differentiate between low-impact, high-probability events and high-impact, low-probability events.

Scatter plots are useful for useful for point estimates, such as a the intersection of a single value that represents likelihood and another single value for the estimate of impact. Bubble charts offer an additional dimension of information because they depict a range of values, rather than a single point. Therefore, bubble charts can be used to estimate a range of possibilities, portraying the inherent uncertainty of risk estimates.

Planning Data Visualizations for Cyber Risk Management

When planning data visualizations for cyber risk management, the ultimate goal is to create a tool that provides actionable insights. A well-planned visualization should not merely display data but should also guide decision-making, illuminate trends, and elucidate the relationships between risk factors.

When using scatter plots and bubble charts, the fundamental idea is to represent risk events based on two key dimensions: impact and likelihood.

Why the Y-Axis Should Represent Impact

The impacts of cyber events include financial and non-financial consequences; however, for the purpose of driving business decisions, converting all of these consequences to financial measures allows decision makers to compare different threats and events more effectively. Therefore, if an imposter website causes loss of time, impairment of reputation, and fees for a consultant to assist in remediation, converting each of these consequences to dollar-measured impact makes it comparable to an entirely different event, such as disruption from a hurricane.

Impacts measured in financial terms can be presented along the y-axis because it allows stakeholders to visualize the potential magnitude of damage a risk event could inflict on the organization, dependent upon the probability of the event’s occurrence. This positioning also supports our intuitive understanding of importance; just as things that are more important tend to be ranked higher in our prioritization and are thus situated higher, events with greater impacts are positioned higher on the visualization.

Choosing the Scale of the Axis

Choosing the scale of the y-axis (impact) can provide additional support for an accurate, intuitive interpretation of event outcomes. For example, the scale may be set such that the organization's risk tolerance for a single loss event is placed in the middle of the y-axis.

Risk tolerance, an important concept in risk management, refers to the level of risk an organization is willing to accept, given its business objectives, regulatory requirements, and stakeholder expectations.

By positioning risk tolerance in the middle, we create a clear visual distinction between scenarios that fall within an acceptable range and those that do not. This placement also allows for a meaningful separation of the visualization into quadrants for recommended risk responses.

Enriching the Visualization with Bubble Charts

While a scatter plot provides a clear overview of individual loss events, bubble charts can offer an additional dimension by displaying range estimates of impact and likelihood.

In a bubble chart, each risk event is represented by a bubble, and the size of the bubble corresponds to the range of potential impacts or likelihoods for that risk. Larger bubbles might indicate scenarios with a wider range of potential impacts or likelihoods, signaling greater uncertainty. This additional dimension can provide more nuance to the risk picture and assist in developing appropriate response strategies.

Planning the visualization in this manner creates an effective tool for understanding an organization's cyber risk landscape. Not only does it allow for the identification of the most pressing loss events, but it also supports response recommendations by categorizing events based on their potential impact and likelihood of occurrence by allowing for the depiction of a data-driven risk response matrix.

Interpreting the Risk Visualization for Decision-Making with a Risk Response Matrix

The scatter plot or bubble chart, divided into four distinct quadrants, can serve as a recommendation tool for risk management approaches. By dividing the area of the visualization into four equal squares, each quadrant can represent a category of risk, defined by the likelihood of occurrence (x-axis) and the potential financial impact (y-axis). Risk response recommendations can be associated with each category.

• Upper-left Quadrant: Risk Transfer: The events that fall into this quadrant are those with a high financial impact but a relatively low likelihood of occurrence. These might include catastrophic events such as a highly destructive environmental event, like an earthquake or hurricane, which could significantly disrupt business operations and result in massive financial losses, albeit infrequently. Due to the potentially high financial impact but relatively low probability of such events, the preferred strategy is to transfer some or all of the consequences of these impacts, for example by purchasing insurance to cover potential losses, thus limiting the organization's financial exposure.

• Upper-right Quadrant: Risk Avoidance: Events positioned in this quadrant have both a high likelihood and high financial impact. For instance, if an organization operates in an service heavily used by cyber criminals, such as an anonymous-friendly cryptocurrency exchange, and a successful attack could lead to catastrophic financial losses, such a risk would fall into this quadrant. The recommended approach for these high-impact, high-probability events is avoidance. This might entail not engaging in certain business activities or entering into certain markets that would expose the organization to these events. If not possible to avoid, consider investing significantly in security controls to avoid the event from occurring.

• Lower-left Quadrant: Risk Acceptance: These events are characterized by a low financial impact and low likelihood. An example might be the risk of a minor data leak involving non-sensitive data, which would have limited repercussions and is unlikely to occur given the organization’s standard activities. An example might include an e-commerce business sending a marketing email to the wrong audience. Generally, these events can be accepted, as the cost of additional activities to mitigate or avoid the events may outweigh the potential impact. Accepting these events means acknowledging their existence while continuing business operations without further interventions.

• Lower-right Quadrant: Risk Mitigation: Events that have a high probability of occurrence but a low financial impact fall into this quadrant. An example could be frequent attempts of phishing attacks on sales team members’ laptops that could result in minor malware incidents. While these scenarios are more likely to occur, their financial impact may be low due to the nature of the assets involved. For these types of events, mitigation is usually the best approach. This might involve implementing additional preventive measures like employee awareness training, endpoint detection and response systems, and two-factor authentication to decrease the probability of successful attacks.

Incorporating Data Visualizations into Risk Management Communications and Decision-Making

Data visualizations, like scatter plot matrices and bubble charts, can play an essential role in risk management by turning abstract data into accessible and understandable visual representations. They can help facilitate clear, effective communication across various channels and events, providing critical insights to drive decision-making processes.

These visual tools should be tailored to different audiences and effectively incorporated into various organizational processes.

Tailoring Visualizations to Different Audiences

Different stakeholders will have unique needs, concerns, and levels of expertise when it comes to understanding risks. For instance, board members may be primarily interested in strategic outcomes that could significantly impact financial performance or the organization's viability. Operational managers, on the other hand, might be more concerned with routine scenarios that could disrupt daily operations or impact efficiency and productivity.

Data visualizations can be tailored to these varied audiences. By adjusting the representation and explanation of scatter plot matrices, bubble charts, or other visualization tools, advisors can ensure all stakeholders understand the scenarios most relevant to their roles and responsibilities. The visual nature of these tools aids both technical and non-technical audiences in grasping complex risk scenarios and their implications.

Utilizing Data Visualizations in Annual Risk Assessments and Budgeting Process

Data visualizations can be a crucial tool in annual risk assessments. By representing risk scenarios in terms of their likelihood and impact, these tools can help prioritize resources and guide strategic decisions about which risk management responses are advisable.

Similarly, during the budgeting process, data visualizations can provide valuable insights. Visual tools like scatter plot matrices or bubble charts that highlight the highest-impact and highest-likelihood risk scenarios can inform decisions about allocating resources to risk mitigation measures, insurance coverage, or other risk management approaches.

Supporting Internal Audit and Compliance Reporting with Data Visualizations

Data visualizations can also support internal audits. By providing a clear visualization of the organization's risk landscape, they can help auditors identify areas where controls may be insufficient or where risk management decisions may not align with the organization's risk appetite.

Furthermore, data visualizations can be effective for demonstrating compliance with risk management standards and regulations. When communicating with external auditors, regulators, or other stakeholders, these visualizations can provide clear, easily understandable evidence of your organization's risk management practices.

Conclusion

The combination of data visualization and cyber risk management is a potent mix, offering organizations a clearer perspective on the potential threats they face.

Incorporating data visualizations into an organization's risk management communications and decision-making processes can greatly enhance its overall risk management process. With a data-driven approach, organizations can enable more informed decision-making and improved operational resilience.