What do we mean by credit data? This post is a discussion around mathematical terminology and concepts that are useful in the context of working with credit data, taking us from network graph representations of credit systems to commonly used reference data sets
Definition of Credit Data What do we mean by credit data? For our purposes Credit Data is any well-defined dataset that has direct applications in the assessment of the Credit Risk of an individual or an organization, or, more generally, a dataset that allows the application of data driven Credit Portfolio Management policies. The appearance of credit data is quite familiar to practitioners: A spreadsheet, or a table in a database, with a number of columns and rows full of all sorts of information about borrowers and loans.
Solstice is a flexible open source economic network simulator. Its primary outcomes are quantitative analyses of the behavior of economic systems under uncertainty. In this post we provide a first overall description of Solstice to accompany the first public release.
Modeling economic networks and their dynamics. Economic networks are the primary abstractions though which we can conceptualize the state (condition) and evolution of economic interactions. This simply reflects the fact that human economies are quite fundamentally systems of interacting actors (or nodes in a network) with transient or more permanent relations between them.
In practice the network character of an economy is frequently suppressed or under-emphasized and does not play a particularly important role.
We develop a conceptual framework for integrated accounting that imposes on certain non-financial disclosures the same double-entry balance constraints that apply to conventional financial statements. We identify the key ingredients required for a rigorous multidimensional accounting framework in terms of concepts, postulates and design choices, and we illustrate these ideas with a worked-out example of linking financial and energy accounts.
Integrated Energy Accounting is keeping track and reporting on an entity’s detailed energy footprint (primary inputs, transformations and waste generation) not as an addendum to financial accounting and reporting but as a deeply-linked extension that is subject to the same level of rigor.
The central design is the use of multidimensional double-entry bookkeeping which tracks additional quantitative information characterizing economic objects beyond their monetary values. This choice ensures the enforcement of both classic balance sheet constraints and the applicable energy conservation laws.
Recap of Previous Posts Part 1 - Overview of the Public Procurement TED dataset Part 2 - Identification of Entities involved in procurement Part 3 - Attribution of GHG Emissions using the CPV classification In the earlier parts of this series we motivated and defined the scope of our exploration of Public Procurement data, we dug deeper into constructing economic representations of the public procurement process. We also linked procurement entities to private sector sellers.
Recap of Previous Posts Part 1 - Overview of the Public Procurement TED dataset Part 2 - Identification of Entities involved in procurement In the first part of this series we motivated and defined the scope of a study explores Public Procurement data. In the second instalment we dug deeper into an important facet of the data, with the aim of constructing a meaningful economic representation of the public procurement process.
Recap of Previous Post Part 1 - Overview In the first part of this series we motivated and defined the scope of a study that explores Public Procurement data. We discussed the meaning of the main relevant terms (Open Data, Open Source, Green Public Procurement) and briefly reviewed the current state and challenges of the latter in EU context. Further, we took a first look into the EU’s TED Database (which is the main source of data) and highlighted some key statistics which bring to light information such as: size of the dataset, overall structure and some data quality aspects.
Introduction In a series of posts we will explore the role of Open Data and Open Source in enabling and accelerating the broad based effort towards Green Public Procurement (GPP). There are several important (and possibly obscure or “buzzwordy”) terms in the above sentence, so the first order of business will be to unpack them.
Let us start with the term Public Procurement which will be the main domain of interest in this study.
What is the EU Datathon? The EU Datathon is an annual Open Data competition organised by the Publications Office of the European Union since 2017. The competitions are organised to create new value for citizens through innovation and promoting the use of open data, in particular the datasets available on the official portal for European data.
Every year, EU Datathon calls for innovators from around the world to come up with new ways of using open data to address important societal and environmental challenges, with the condition that they use at least one of the thousands of data sets published on data.
Equinox is an open source platform that supports holistic risk management and reporting in the context of Sustainable Portfolio Management. The platform integrates geospatial information with applicable regulatory and industry standards, for example the GHG Protocol (accounting for Project based, Corporate and City-Wide greenhouse gas emissions), the IPCC Emissions Factor database and further reference data, the PCAF attribution methodologies (and more) to provide a holistic view of the footprint of both individual projects and portfolios.
The Role of Open Risk Manual Taxonomies A taxonomy is the categorization of concepts. It can be a very useful tool in supporting effective knowledge management. Fundamentally a taxonomy is a scheme of classification, typically a hierarchical classification, in which things or concepts are organized into groups or types of increasing specificity.
Mathematically, a hierarchical taxonomy is a tree structure of classifications for a given set of objects. It is sometimes also named a containment hierarchy.
Motivation Fig 1. An economic network as a graph. The economy is a complex tangle of various agents that interact via transactions (sales and purchases) and contracts (lending, investing). In recent times more and more techniques from graph theory and network science are brought to bear on economic analysis. On the other hand, ever since the seminal contributions of Leontief, Input-Output Models (IO) have been widely used to describe economic relationships between economic actors (e.
What are 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.
We look into ten years of FOSDEM conference data to start getting to grips with the open source phenomenon and also explore techniques for data review and exploratory data analysis using (of course) open source python tools. In the process we identify the imprint of the pandemic on attendance, the longest ever title, the distribution of mindshare of time and some notable newcomers.
FOSDEM is a non-commercial, volunteer-organized, two-day conference celebrating free and open-source software development. The conference has a geographic focus on European open source ecosystems and projects. FOSDEM is primarily aimed at developers, across the entire range of software and aims to enable them to meet and discuss the status of projects.
We look into ten years of FOSDEM conference data to start getting to grips with the open source phenomenon and also explore techniques for data review and exploratory data analysis using (of course) open source python tools.
Representing a matrix as a JSON object is a task that appears in many modern data science contexts, in particular when one wants to exchange matrix data online. While there is no universally agreed way to achieve this task in all circumstances, in this series of posts we discuss a number of options and the associated tradeoffs.
Motivation and Objective Representing a matrix as a JSON object is a task that appears in many modern data science contexts, in particular when one wants to exchange matrix data online. There is no universally agreed way to achieve this task and various options are available depending on the matrix type and the programming tools and environment one has available. Matrices are in general not “native” structures in computing environments but are handled with speficic packages (modules, extensions or libraries).
Equinox is an open source platform that supports the holistic risk management and reporting of major sustainable finance projects (the financing of projects with material physical footprint) such as project finance.
Equinox aims to integrate in the database a number reference databases that facilitate tasks of sustainable portfolio management. In the current focus such reference material concerns the emissions factors for various processes and activities. In the latest (Solstice Day!) update of the Equinox Project we discuss the integration of reference data an in particular greenhouse gas emissions factors as catalogued in the IPCC Emissions Factors database (EFDB).
We develop an analytic framework that synthesizes current approaches to sustainable portfolio management in the context of addressing climate change. We discuss the different required information layers, approaches to emissions accounting, attribution and forward-looking limit frameworks implementing carbon budget constraints.
The frontpage graphic is adapted from Steffen et al. “Planetary Boundaries: Guiding human development on a changing planet". Science (2015). The Planetary Boundaries concept was proposed in 2009 by this group of Earth system and environmental scientists. The group suggested that finding a “safe operating space for humanity” is a precondition for sustainable development. The framework is based on scientific evidence that human actions since the Industrial Revolution have become the main driver of global environmental change.
Interest in Sustainable Finance is growing What is “Sustainable Finance”? A working definition is: A financial system that takes into account environmental, social and governance considerations to ensure long term sustainability of the human economy.
You can imagine that with a scope and ambition that sweeping, the devil hidden in the details will be of gargantuan size. The definitions of so-called ESG factors, the incorporation of sustainability into business strategies, the governance, policies and risk management applicable to ESG Risks, the ESG and climate-related disclosures and the development of “green” financial products are all topics that combine urgency, complexity and potentially dramatic impact.
Sustainability is depicted as a curve to bend, a temperature threshold to secure. A useful visual model is to see sustainability as a surface of possibilities. Achieving environmental objectives still allows widely differing choices that may not all be equally desirable.
Bending the Curve - Sustainability as a One Dimensional Exercise The opening of the Global Scenario Group report “Bending the Curve: Toward Global Sustainability” by Paul Raskin, Gilberto Gallopin, Pablo Gutman, Al Hammond and Rob Swart, published in 1998 goes as follows:
Over the last few centuries, a mere heartbeat of historic time, humanity has moved to the brink of a new evolutionary milestone - the planetary phase of civilization. The world economy is expanding and becoming more integrated, profoundly reshaping the cultural and political landscape everywhere.
The GSOC 2021 collaboration between Open Risk and the Hydra Ecosystem - Project Wrap-Up Google Summer of Code 2021 came and went amid the still ongoing worldwide pandemic experience. Open Risk was happy to join forces with the Hydra Ecosystem in exploring a proof-of-concept for next generation API’s using Hydra.
The project aimed to guide students (here and here) to build a hypermedia enabled REST service that can serve standardized credit portfolio data.
Offline versus Online In computer technology and telecommunications, online indicates a state of connectivity over digital networks, and offline indicates a disconnected state. Both states have many sub-divisions. For example the type online access varies enormously according to the bandwidth and latency of connections. Similarly, people may be “offline” as not having network access or completely unplugged, as in not having access or using any electronic device.
While the number of people, the fraction of time and the type of activities they engage on has rapidly expanded as digital technology increasingly diffuses, the online state is certainly not the default state and in many regions or population segment might be completely out of reach.