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.
A survey of existing definitions When looking up the meaning of risk we are immediately confronted with a surprising situation. There is no satisfying and authoritative general purpose one-liner that we can adopt without second thoughts. Let us start with the standard dictionary definitions: The online Merriam Webster Dictionary defines risk as the possibility of loss or injury The online Cambridge Dictionary opines that risk means the possibility of something bad happening The Oxford English (Concise, Hardcover!
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)
Semantic Web Technologies The Risk Model Ontology is a framework that aims to represent and categorize knowledge about risk models using semantic web information technologies. In principle any semantic technology can be the starting point for a risk model ontology. The Open Risk Manual adopts the W3C’s Web Ontology Language (OWL). OWL is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things.
We have updated the logo for the Open Risk Manual. The new logo aims to make more explicit both the inspiration that the Open Risk Manual project draws from the trail-blazing Wikipedia initiative (and increasing collection of associated Wikimedia projects) and the reliance on the open source ecosystem of software and tools, including the mediawiki software and the important semantic mediawiki extension. The principal stylistic element is the “double brackets” [[ ]], which is the standard way one adds connectivity between different parts of the wiki in wikitext (the mediawiki markup language).
In the European Union there are several ongoing large scale legislative and regulatory projects that transform the context within which individual, firms and the public sector interact economically. While financial and regulatory reform is an ongoing process in all jurisdictions globally, the size and supra-national nature of the European Union makes those projects particularly interesting. A new entry at the Open Risk Manual aims to provide a brief overview of ongoing projects / initiatives.
Overview of the Julia-Python-R Universe A new Open Risk Manual entry offers a side-by-side review of the main open source ecosystems supporting the Data Science domain: Julia, Python, R, sometimes abbreviated as Jupyter. Motivation A large component of Quantitative Risk Management relies on data processing and quantitative tools (aka Data Science). In recent years open source software targeting Data Science finds increased adoption in diverse applications. The Overview of the Julia-Python-R Universe article is a side by side comparison of a wide range of aspects of Python, Julia and R language ecosystems.
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.
Limit frameworks are fundamental tools for risk management A Limit Framework is a set of policies used by financial institutions (or other firms that actively assume quantifiable risks) to govern in a quantitative manner the maximum risk exposure permitted for an individual, trading desk, business line etc. Why do we need limit frameworks? A limit framework is expressing in concrete terms the Risk Appetite of an institution to assume certain risks.
Motivation for the comparison A large component of risk management relies on data processing and quantitative tools. In turn, such information processing pipelines and numerical algorithms must be implemented in computer systems. Computing systems come in an extraordinary large variety but in recent years open source software finds increased adoption for diverse applications (machine learning, data science, artificial intelligence). In particular cloud computing environments are primarily based on open source projects at the systems level.
The ESMA Securitisation Templates are now fully documented at the Open Risk Manual. Users can browse, search and cross-reference with the rest of the knowledge base. Category Browsing The ESMA Templates Categories are part of both the Securitisation category and the Information Technology Category. Each one of the templates and each one of the sections within a template forms its own category. In turn all the fields in that section of the template are part of that category
Representing economic activity using pictograms Visualization can produce significant new insights when applied to quantitative data. It is currently undergoing a renaissance that mirrors other developments in computing and data science. Sophisticated open source libraries such as d3.js or matplotlib, to name but a couple, are enabling an ever wider range of users to distill valuable information from the avalanche of data being produced. Yet when it comes to visualizing data that relate to abstract concepts it can be quite difficult to find an appropriate grammar to express the quantitative context.
Transparency, collaboration key to regaining trust in financial services In banking, confidence is the first order of business Maintaining the confidence of market participants, clients, shareholders, regulators and governments is uniquely important for the financial sector. Trust is, quite literally, the real currency. Yet it is a truism that confidence is hard to build up and rather easy to destroy. Why is this so? The short answer: The difficulty in rebuilding trust is linked to the lack of transparency.
Business Model Risk: The Forgotten Risk Type Sustainable business models that demonstrate adequate profitability over long horizons are key to a healthy market economy. This applies to firms and organizations of any size and in any sector. But how do we determine what is sustainable and how can we tell a risky business structure from a stable one? On the small-scale end of the size spectrum we have the domain of startups and SME’s.
Open Risk developed an online accessible version of the AQR manual that offers additional means to access and browse the Phase 2 ECB AQR Manual.
The Risk Manual is one of the core tools of the Open Risk Commons. We have released a first set of article entries covering a broad area of risk management topics.