Financial Competences Ontology
The Financial Competences Ontology (FCO) is a semantic web framework that aims to represent and categorize financial competences. FCO is described using W3C RDF Schema and the Web Ontology Language OWL. FCO aims to conform as closely as possible to the European Union/OECD (2022) Financial Competence Framework for adults.
Business Model Risk Ontology
The Business Model Risk Ontology is a framework that aims to represent and categorize knowledge about Business Models, in particular their Risk profile.
Credit Ratings Ontology
The Credit Ratings Ontology is a framework that aims to represent and categorize knowledge about Credit Rating Agencies and related data (Credit Ratings) using semantic web information technologies.
Non-Performing Loan Ontology
The Non-Performing Loan Ontology is a framework that aims to represent and categorize knowledge about non-performing loans using semantic web information technologies.
Risk Function Ontology
The Risk Function Ontology is a framework that aims to represent and categorize knowledge about risk management functions. Codenamed RFO, it codifies the relationship (roles and responsibilities) between the various persons involved in a risk management organization.
In this post we endorse the UN Open Source principles and take stock on their implications for the domains of risk management and sustainable finance. We also take a step back and discuss how open source is an essential ingredient for the PODA manifesto, namely putting people above data and algorithms.
The UN Open Source Principles is a set of eight high-level guiding principles that were recently adopted by the UN Chief Executive Board’s Digital Technology Network (DTN). They open a new window and provide guidelines to drive collaboration and Open Source adoption within the UN and globally. They send a strong signal of the importance of open source and how individuals and organisations need to act to benefit but also support a thriving and sustainable open source community.
A DeepDive Course into using Python to work with Input-Output Models
The SFI32064 course is a DeepDive with nine segments, exploring Input-Output models using Python and the Pymrio library. The following is an updated overview of it contents.
A DeepDive using the Eigen C++ Library to perform Tensor calculations
The objective of the course is to provide an introduction to using Eigen::Tensor as a high-level library for using Tensors in C++ projects.
The Climate Dictionary Quiz is now accessible as a course at the Open Risk Academy. The Quiz is based on the UN Climate Dictionary and provides an interactive educational tool to enable deeper understanding of the essential terminology.
The Climate Dictionary is an initiative of the United Nations Development Programme (UNDP) aimed at providing people worldwide with a simplified guide to understand climate change. The Dictionary (first published Aug 2023) seeks to bridge the gap between complex scientific jargon such as present in the IPCC publications and other scientific bodies and the public.
A DeepDive Course into using Python to work with Input-Output Models
Environmentally Extended Multi-Regional Input-Output (EE-MRIO) tables describe economic relationships of economic actors (e.g. industrial sectors) operating within and between regions and their environmental repercussions.
An EE MRIO augments the more basic and historically first proposed Input-Output Models (IO) with additional datasets and/or modeling assumptions in order to provide insights into the environmental foorprint of economic activity. Presently, the emphasis on negative externalities of economic activity (e.g., climate change, biodiversity loss) turns EE MRIO models into a useful conceptual and analytic tool. Yet a good grounding on the underlying IO models is a prerequisite and this is the focus of this new course that is now available at the Open Risk Academy.
We explore a variety of distinct uses of graph structures in data science. We review various important graph types and sketch their linkages and relationships. The review provides an operational guide towards a better overall understanding of those powerful tools
Graphs (and the related concept of Networks) have emerged from a relative mathematical and physics niches to become mainstream models for describing and interpreting various phenomena. The objective of the course is to review various important graph types as they are increasingly explored in data science and sketch their linkages and relationships (a graph of graphs!).
A CrashCourse introduction to semantic data using Python covering a number of frameworks such as rdflib, owlready and pySHACL
This CrashCourse is an introduction to semantic data using Python.
It covers the following topics:
In the Back-to-School for 2020 we have more ways to access the Academy, new functionalities and more courses. In the rest of this post you will find a summary of the changes with pointers to further information where required
The summer is over in the Northern Hemisphere - and what an unusual summer has it been! Worldwide the implications and challenges of adjusting to a Covid-19 pandemic are still a major issue, affecting individuals, companies and governments.
This course is a CrashProgram (short course) introducing the GeoJSON specification for the encoding of geospatial features. The course is at an introductory technical level. It requires some familiarity with data specifications such as JSON and a very basic knowledge of Python
This course is an introduction to the concept of credit contagion. It covers the following topics:
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.
In two new Open Risk Academy courses we figure step by step how to use python to work to review risk data from a data quality perspective and how to perform exploratory data analysis with pandas, seaborn and statsmodels:
Loan Level Templates Using Python
In this Open Risk Academy course we figure step by step how to use python to work with Loan Level Templates, using the ECB SME template as an example.
Get an Open Risk Academy account and get started with the course here
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?
Financial services jobs continue being decimated. A recent (as of the initial post date) FT article was a sobering summary of the continuing transformation of the financial sector: 2015 alone has seen more than 10% reduction of the total workforce across large EU/US banks: