Risks are inevitable. But it doesn’t have to cause damage to company operations all the time. If these situations can be analyzed, they can be managed. This is the reasoning behind FAIR or Factor Analysis of Information Risk. But is it for your organization? Let’s weigh it with these FAIR pros and cons.
A brainchild of Jack A. Jones of the FAIR Institute, the Factor Analysis of Information Risk is a framework that expresses risks as numerical values or quantitative factors. When these numbers are measured and crunched, cybersecurity risk can be evaluated and analyzed.
Understanding FAIR in a Nutshell
The FAIR framework is a reference point — a map, if you will — that helps organizations navigate the uncharted and treacherous waters of cybersecurity. With all the technical jargon involved in this field, the FAIR framework is a reference point that will help an organization to determine what to measure — and how to measure these.
And when measurements are done, the framework also gives inputs on understanding and getting meaning from these data.
What risks should be prioritized? What solutions to devote most of the company’s resources? FAIR helps ask and answer these questions. The framework does it in an easily understandable way — a great benefit to decision-makers who may not be very technologically savvy.
The Advantages of FAIR
Now that we are beginning to discuss the benefits of FAIR, we will tackle the Factor Analysis of Information Risk framework’s comprehensive advantages.
Easier Vernacular for Information Risk
For non-specialists, information risk may sound complicated at first. It involves a lot of technical definitions and complex concepts. But the FAIR framework has been written by a community of experts in an easily understandable manner.
The belief is that with an easier understanding, decision-makers can come up with more effective choices.
The Factor Analysis of Information Risk framework streamlines the process of outlining the building blocks of information risk. Here are examples of basic terms that can be encountered within the framework.
- Risk. A situation that will expose a company to loss. It can be expressed both in terms of frequency (how often it can happen) or magnitude (how wide is its impact on the company).
- Speculative Risk. A type of risk that has an uncertain or unpredictable level of loss if it comes to fruition.
- Pure Risk. A risk situation that will end up with a loss.
- Operational Risk. A potential risk that results as a consequence of doing business provided that safeguards and internal processes fail.
Including the terms mentioned above, the FAIR framework has an established taxonomy of technical terms that can be explained easily.
The framework improves the teamwork of a company because it translates the technical details into understandable language. This language lends a unified voice to the organization.
A Standardized Process of Measurement
Risks are interpreted as mathematical principles. Numbers can paint a comprehensive and definitive picture of a situation or incident. It is through this lens that the FAIR framework gets most of its strength.
The FAIR framework is specific when it comes to the numerical terms that must describe information risk. It must contain precision and accuracy.
- Precision. The numerical data must not make any estimates or guesses. It has to be expressed in an explicit numerical value to be precise.
- Accuracy. This is the attribute of quantitative data that focuses on its factual basis. The data may be precise and pinpoint in its numerical value, but that doesn’t automatically mean the data is correct. For specific data to be useful, it has to be accurate first and foremost.
The FAIR framework also differentiates between probabilities and possibilities. Consider the following:
- Probability. It is the numerical likelihood that an outcome will happen.
- Possibility. It is a simple decision between whether an incident will happen or not.
Risks are prevalent and unpredictable. It is not easy to specify its possibility if it will happen or not. The FAIR framework concentrates on understanding risk as a range of numbers that indicate probability.
For instance, when picking a card from a complete deck of 52 cards, you can’t predict which card you can select, but there is a 50% probability that you will get either a red or a black card. This probability is definite. But it is not a prediction. There is no surefire way of knowing what card you can pick at any given time.
Factor Analysis of Information Risk makes it easier to understand the relationships of risks when expressed as quantifiable probabilities.
This use of analytics enables FAIR to identify risk ratings.
The Scalability of FAIR
Another advantage of FAIR is that it is not restricted to the limits of scalability. Whether an organization is starting, emerging, or established, the framework can sense its information risk with a scalable model.
The measurement of risks can also happen at any level within the organization’s model, enabling utmost flexibility in its use. It can also accommodate authentic scientific development because of its loss disclosures.
No matter how complex an organization’s digital environment may be, the FAIR framework can find a way to make sense of it with expandable definitions of risks, vulnerabilities, and threats.
No stones are left unturned when it comes to Factor Analysis of Information Risk. Its analysis enables the clear identification of factors within an organization that will significantly impact cybersecurity.
With this guidance, decision-makers can develop better risk management decisions that will maximize the company’s resources. There will be an optimization of the ROI or the Return on Investment.
The FAIR framework can translate the resources that have been devoted to it into results that can bolster the cybersecurity defense of an organization. This sustained success will make risk management a priority that can protect a company and not as a nuisance wherein resources are wasted.
If there are existing risk management frameworks within an organization, the FAIR framework can also easily plug in and enhance the installed system’s functionality.
There is no need to radically scrap the cybersecurity defense in favor of the FAIR framework. It can seamlessly boost the success of the programs such as OCTAVE, COSO, ISO/IEC 27002, ITIL, COSO, and many others.
Since risks cannot be avoided altogether, an organization can just pick its poison. The FAIR framework will help the company decide which risk factors to prioritize or to tolerate.
What risk factors should take precedence? What can other risk factors be managed and supervised with minimal resources? Factor Analysis of Information Risk can identify which is which.
With analytics, the FAIR framework can effectively outline a totem pole of priorities that an organization can pursue to risk response. They can guide decision-makers about the loss probabilities the organization faces, and what of these probabilities can count as an acceptable risk.
The risk tolerance window is critical because if a risk has breached that point, it can be prioritized for troubleshooting or mitigation. The FAIR framework allows the analysis of multiple risk conditions, leading to numerous what-if evaluations to assess risks.
The Disadvantages of Factor Analysis of Information Risk
As robust as the FAIR framework’s advantages are, it has its fair share of critics that have pointed downsides to using Factor Analysis of Information Risk.
Even though its primary function is to simplify the technical specifications of information risk, some users have still pointed out that the FAIR framework is difficult to use. One of its pitfalls is that there is not a thorough body of documentation to its methods.
Because it has emerged only recently, there are claims that the framework has no access to existing research methodology that outlines its processes. A lack of documentation has made it difficult for several would-be users to catch up with its drift.
Not Suitable for Risk Assessments
By design, the FAIR framework is not a magic bullet that will solve all risk management problems. It is primarily a reference guide that can help explain the relationships of risks within an organization.
It must work in a complementary manner to an actual risk management methodology. Relevant laws can also help in the conduct of risk assessments by auditors.
A Bevy of Guesswork
The FAIR framework deals with a lot of probability work that some may consider being estimates or guesses to the uninitiated. However, these estimations are not baseless.
The framework appreciates the value of probabilities to paint a picture of cybersecurity incidents. It is not precise, per se, because there are no definite values when an incident happens or how much damage it will cost. But it offers a range of motion by which an incident can likely occur.
In this regard, these findings qualify as intelligent guesses that are based on numbers and analytics. The framework crunches the numbers to determine the likelihood that an information risk will go out of hand. Controlling these risks is critical, rendering these probability estimates as useful references.
Intricate Information Networks
The FAIR framework makes sense of all the technical details of information risk with a hierarchy of facts — a flowchart, if you will. This so-called digital taxonomy is a gateway to complex concepts. Without prior exposure to the framework, it may be challenging to navigate the analysis required to make functional and useful analysis inputs.
There are criticisms that all the jargon further confuses decision-makers who have no thorough understanding of technology.
RiskLens has been specifically created and designed to make life easier for the implementation of the FAIR framework. Without RiskLens, it can get very complicated for regular users. Below are some of the advanced information that RiskLens helps to process:
- Details of loss frequency and loss magnitude specific to industries
- Analytics that employ advanced Value at Risk (VaR)
- Template-based workflows for practice
- Models of Maturity
- Business security data
Guidance and Teamwork with Professionals
Factor Analysis of Information Risk (FAIR) can manage the vulnerabilities and threats of an organization with a risk-based approach. Its quantitative approach has shown success with precise and accurate results. It has also been declared as a leading model for risk management and quantification by the global consortium called the Open Group.
The FAIR Framework is an effective defense line against the evolving cybersecurity threats that the world faces every day. More than ever, it is essential to keep up with patches, updates, and threat databases.
Studying the FAIR framework’s strengths and weaknesses enable the organization to be efficient in devoting digital safety resources. To fully maximize its advantages, it is best to partner with information risk professionals such as RSI Security.
Our team of experts can thoroughly study and apply the risks your organization faces and manage them accordingly with the FAIR framework’s help.
We understand that time and money are of the essence for companies. We will maximize your cybersecurity’s cost efficiency with our expert understanding of Factor Analysis of Information Risk. You’re in good hands with RSI Security.