Risk, Randomness, Uncertainty and other Ambiguous Terms Uncertainty versus Risk is a popular discussion topic among risk managers, especially after major risk management disasters. The debate can get really hairy and drift into deep philosophical areas about the nature of knowledge etc. Yet the significance of having an as clear as possible language toolkit around these terms should not be underestimated. Practical risk management typically shuns too deep excursions into the meaning of things, yet that is not quite compatible with the use of sophisticated methods and tools (such as a Risk Model ) that assumes an understanding of the scope and limitations of “knowledge”.
The Risk Function Ontology The Risk Function Ontology is a framework that aims to represent and categorize knowledge about risk management functions using semantic web information technologies. Codenamed RFO codifies the relationship between the various components of a risk management organization. Individuals, teams or even whole departments tasked with risk management exist in some shape or form in most organizations. The ontology allows the definition of risk management roles in more precise terms, which in turn can be used in a variety of contexts: towards better structured actual job descriptions, more accurate description of internal processes and easier inspection of alignement and consistency with risk taxonomies (See also live version and white paper (OpenRiskWP04_061415)
What is Risk Compensation? Risk Compensation is a behavioral model of human attitudes towards risk which suggests that people might adjust their behavior in response to the perceived level of risk. It follows that, depending on the strength of the effect, that it might counteract and even annul the impact of risk mitigation, if the updated attitude and behavior modifies the actual underlying risk Examples of potential risk compensation effects abound A prominent example of potential risk compensation in recent times that established the concept in more formal terms in public policy debates concerned the beneficial role of safety belts in automobiles.
NACE Classification and the EU Sustainable Finance Taxonomy: The integration of climate risk and broader sustainability constraints into risk management is a monumental task and many tools are still lacking. Yet there is strong support and bold initiatives from policy bodies and an increasing focus from the private sector side. The EU (Sustainable Finance) Taxonomy is one such initiative of fundamental significance as it attempts to map at a granular level economic activities with respect to their climate risk mitigation or adaptation potential and create tangible metrics and thresholds to measure progress (the ultimate anti-greenwashing treatment)
What is a Risk Taxonomy? There are formal definitions of risk taxonomies (and we will go over those below), but it might be useful to first look at a very intuitive example of a risk taxonomy: the classification of fire hazards (also known as fire classes) Everybody knows (or should know!) that the different types of fire (the underlying Risk in this context) cannot be treated the same way because they respond in different ways to the substances used to suppress the fire.
Unbundling the Banks: A How To Guide: Talk of unbundling the banks is all the rage these days (if we believe the fintech startups). Yet upon closer inspection one gets the feeling that these optimistic people might not necessarily know exactly what they are trying to unbundle, the true complexity of a medium to large bank, which in turn reflects, at least in part, the complexity of our modern financial system.
The periodic table of risk elements: You know the periodic table of elements, even if you flunked your science courses! It is the large colorful and blocky table that hanged on every school’s classrooms before becoming yet another mobile app. The periodic table is one of the early and iconic achievements of science. It lists all the pure chemical elements found in nature, the building blocks of all possible material substances.