Risks are part of everyday life, particularly in industries and businesses. But with the right analytics and mindset, risks can be managed, minimized, and mitigated. One such effective solution is the use of Factor Analysis of Information Risk or FAIR, a highly specialized form of quantitative risk analysis and quantitative risk assessment.
If an incident or situation can be measured, it can then be analyzed. With such analysis, there can be ways to minimize its impact. This is the reasoning behind quantitative risk assessment. Let’s take a more in-depth look.
Paint by Numbers
Quantification is the process by which an entity understands a situation using numbers. In quantitative risk analysis, numbers from statistics, studies, and analytics are used as the primary data to understand risk.
It is similar to painting. A painter captures a particular moment in time using colors and a canvas. In quantitative risk assessment, we understand the impact of risk through measurable data.
The FAIR (Factor Analysis of Information Risk) model is a system that organizations can use as a reference to conduct a quantitative risk analysis. It provides a taxonomy or a list of factors that can contribute to risk and how they affect each other.
Asking the Right Questions to Understand Risk
FAIR is a framework. The actual quantitative risk assessment has to be accomplished within the organization before minimizing risks. There must be work done first; it does not magically solve problems. What FAIR can help is to ask the right questions that will give companies more understanding of risks.
No one wants to endure unnecessary damages and risks that can disrupt the operations of a company. This can come in data breaches, unauthorized system entry, and cyber-attacks that can translate to legal violations, hefty penalties, and reputational damage.
FAIR gives you a fighting chance to ensure that your cybersecurity is complying with industry and legal standards. This framework lists the best practices that can help an organization.
With FAIR as a reference, the quantitative risk analysis will effectively ask the following questions:
- What are the primary cyber-crime risks that the organization is facing?
- How much exposure do these risks affect the vulnerability of the company?
- What cyber risk management investment is the most important to make?
- Are there enough resources invested in cyber risk management?
Implicit or Explicit?
It is the instinct of companies to manage risk for their survival. In one way or another, there are steps done to eliminate these risks. But the more important question to ask is whether the risk management system was implicitly or explicitly achieved.
In an implicit approach to cyber risk management, the organization may align its policies with a reputable framework such as the NIST CSF (National Institute for Standards and Technology Cyber-Security Framework). It may also be doing an annual enterprise risk assessment as required by law.
But from this perspective, the cybersecurity staff will only work to address the findings, mainly if there are deficiencies. It is only a reactionary move and not a long-term program to protect the organization and to anticipate potential problems down the road.
It is better to have an explicit risk management program with a particular and quantified risk target. The cybersecurity staff will then perform active management relating to these targets. Potential problems can be analyzed and anticipated.
Risks may not be a numerical value in the beginning. But these can be quantified.
Using the FAIR quantitative risk analysis model, we can understand risk management better with this definition: “the combination of personnel, policies, processes, and technologies that enable an organization to achieve and maintain an acceptable level of loss exposure cost-effectively.”
Let’s take a look at some essential keywords from the definition:
In doing a quantitative risk analysis, the risk experts must do so in a cost-effective manner. The wise use of resources will empower the organization to see risk management as a benefit to the company and not as an additional nuisance.
“Achieving and Maintaining”
By using the term “achieving” implies that the organization has objectives and plans in place. They do not act on a whim and react to problems as they arrive. There are concrete steps to anticipate issues and incidents before they occur to minimize or even eliminate risks.
By including the word “maintaining,” there is an understanding that there is a baseline reference. This is a configuration or situation where there are zero risks that the organization is striving for. In risk management, the assessment should always start from this baseline reference in making quantifications and comparisons.
Acceptable Level of Loss Exposure
The acceptable level of loss exposure is the range that an organization is striving to eradicate any drastic consequence that a damaging risk can cause. By managing it to acceptable levels, there is the belief that the bet will not be that significant.
Five Foundations of Risk Management
Conducting the quantitative risk analysis starts with laying the right foundation within an organization. To achieve and maintain reliable and robust risk management, a company will need the following five elements:
Cost-effective risk management.
The program must make wise use of its financial and human resources to build a risk management scheme that will outweigh its costs. It must be seen as a positive asset in protecting the company and not a liability.
Decisions are central to avoiding the adverse effects of risks. Companies must make choices based on empirical data and careful analysis.
For well-informed decisions, the information used as a basis should come from careful analysis of available options and scenarios. Comparisons can provide valuable insight and data when assessing and analyzing the potential impact of a risk. To accomplish this, there must be a baseline reference or a set of factors that can be used for comparison should an incident happen.
After useful comparisons have been accomplished, this is now an excellent opportunity to gather usable quantitative measurements that stakeholders can understand. When using the right methodology, numbers will not lie. They can provide a perfect snapshot of risk situations, enabling decision-makers to find the right course of action.
As stated above, data gathering is beneficial for decision making when guided by scalable and correct risk models of explicit risk management. The FAIR quantitative risk analysis model was designed to be a reliable reference point for meaningful measurements. It is the only international standard Value at Risk (VaR) model for operational risks and cybersecurity.
The Components of a Robust Risk Management System
The FAIR assessment model focuses its management of risks by understanding its three key elements:
- Risk. These are factors that initiate loss exposure. It is the dynamics among threats and vital assets of the company. Other aspects also affect risk, such as legislation.
- Risk Management. These are centered on the core decisions and implementations of the organizations when responding to cybersecurity.
- Feedback Loop. This is the mechanism that focuses on the conditions of asset-level controls and threat metrics.
Aided by Software
Several software companies have been using the FAIR model to build platforms that streamline data gathering and risk computations.
These software platforms can help risk experts to conduct quantitative risk analysis or quantitative risk assessment using the FAIR model. The results range from data points collected from the business to pre-populated loss tables.
Aided by technology, decision-makers do not have to sort through piles of information and numbers. The application will run the data through the FAIR model and create summary outputs that are easy to understand and assess. Risk exposure is usually expressed in financial terms for better readability.
With this information in hand, decision-makers can analyze if the risk is on an upward trend or if it has been effectively mitigated. The numbers will reflect this comprehensively.
The FAIR Institute
Emerging as the premier Value at Risk (VaR) framework for cybersecurity, the FAIR (Factor Analysis of Information Risk) cyber risk framework has its roots from the FAIR Institute.
The FAIR Institute is a non-profit professional organization that has committed to the discipline of measuring and managing information risk. Their dedication to the best practices of risk management has led to expanding a community of experts on innovation and education.
Benefits of a FAIR Quantitative Risk Analysis
When done correctly, a FAIR quantitative risk assessment will vastly improve the cybersecurity of a company. This risk model provides several benefits, including the following:
Accuracy of IT solutions
Because of technical complexity, IT managers may have simplified the quantitative findings of previous risk management techniques. The FAIR assessment model has solved this problem with a framework that is easy to understand even if decision-makers such as CEOs do not have a software engineer’s training.
Identification of risk tolerance
Risks can never be eliminated to zero levels. There will always be risk probabilities in every industry. The key to the FAIR quantitative is that there is a prioritization of resources and business strategies to overcome significant risks.
The risk tolerance of an organization will be identified explicitly with the help of the quantitative risk analysis. There may be vulnerabilities, but with a dedicated focus on countering these risks, the Loss of Magnitude of these risks will be shallow. The quantitative risk analysis will also help the organization to monitor these potential weaknesses comprehensively.
Penetration testing is actionable when implemented using the FAIR assessment model. The risk experts can report these findings, as complicated as they may appear because of its numerical expressions, and let the FAIR model translate these results into jargon that decision-makers can easily understand.
Efficiently comprehending the data is half the battle won. It will equip the decision-makers with all the correct information they need to act on cybersecurity threats.
This FAIR risk model can provide both a bird’s eye view of the cyber risk situation or a case study slice that will reveal the potential incident’s intricacies. Both perspectives give decision-makers better options to tackle the risk.
The FAIR risk model’s metrics and analytics are reliable as they both incorporate qualitative and quantitative aspects.
From a quantitative perspective, they can specify a number that will accurately describe a system’s situation, such as breach attempts or data capacity.
From a qualitative point of view, these situations can be expressed in frequency (Loss Event Frequency) or magnitude (Loss Magnitude).
The FAIR assessment model will report on these findings in a definite manner that will make it easier to decide and respond to these incidents. It will also be more efficient in locating these threats when they happen within the network and determining their severity and volume.
Professional Guidance in Quantitative Risk Analysis
An organization can provide a robust defense for its cybersecurity by employing a quantitative risk management system such as the FAIR assessment model. Whether the company is just emerging or has a global scale, this model can analyze the impact of cyber-attacks.
RSI Security will help your organization meet this quantitative risk analysis model’s compliance standards to embrace the FAIR assessment model’s benefits fully. With our years of expertise, we can help protect your data and networks’ integrity even before cyberattacks strike. In this day and age of ever-evolving threats, trust RSI Security to help you be one step ahead of the game.