Academy News

New Course: FOSS (Open Source) Business Model Risk Canvas

Wed, 14 Jan 2026 19:01:33 GMT

by Ad Min.

In this course we want to study an identification framework for Open Source Business Model Risks.

The scope of the analysis covers both for-profit and non-profit projects.

The structure of the course is as follows:

First we cover general aspects, with a focus on definitions and context.
Next, the identification methodology sections document detailed approaches to potential weaknesses of a business model and their likely impact on the sustainability of a project.

The result is a FOSS Risk Canvas, a concise tool that helps with a comprehensive self-assessment of business model risks that can hinder FOSS projects reach financial sustainability.

Analysing the volatility of financed emissions using waterfall diagrams (blog post)

Thu, 08 Jan 2026 23:21:56 GMT

by Ad Min.

In a blog post we discuss variability drivers of reported financed emissions of portfolios. Using a conceptual deed-dive into calculation procedures we isolate the fundamental factors and how they can be explained using waterfall diagrams.

The Open Risk Manual is now open to Academy users

Tue, 06 Jan 2026 15:43:20 GMT

by Ad Min.

The Open Risk Manual was developed for a long time, with out-most conviction, as an open and free resource. An open online repository of information about Risk Management in all its forms, that was the core idea, part of our vision for widely available open source tools for risk management and sustainable finance.

Alas, as of late the open part of the mission has become very problematic. A large number of AI bots are now roaming the internet and hitting servers (like the one on which the Manual runs) indiscriminately, without regard to breaking it. It has become very difficult to defend against such (effectively) DDoS attacks. Filtering the thousands of hostile bot requests using random address from human users is not what we want to spend our resources on. After trying all possible measures, it became clear that nothing will do. We need to ask users of the Manual to login before browsing and/or searching.

The login mechanism is the same as the Academy. Users of the Academy can already use the Manual using their existing credentials. Other users will need to setup and have an account approved at the Academy.

Mathematical Formulation of Financial Statements

Tue, 16 Dec 2025 20:45:11 GMT

by Ad Min.

Our objective in this post is to express standard financial statements concisely using symbolic mathematical notation that substantially captures their numerical information content and the constraints being satisfied.

We use the incidence matrix of an accounting graph to describe an abstract underlying accounting system that follows double-entry bookkeeping principles and we derive from it the classification, aggregation and stock-flow machinery that reproduces the well-known balance sheet, income and cash flow statements.

Open Risk White Paper 19: Connecting the Dots: Accounting Graphs for Double and Quadruple-Entry Bookkeeping

Wed, 12 Nov 2025 15:31:29 GMT

by Ad Min.

In a new paper we develop the concept of an accounting graph as an intuitive and flexible tool that can faithfully represent widely used accounting concepts.

More specifically, a weighted directed multigraph representation is applied to model standard double-entry bookkeeping (DEB) of individual accounting entities but extended to also provide a consistent accounting graph for larger economic networks that feature multiple transacting entities (so-called quadruple-entry accounting). We illustrate the concepts with stylized accounting examples. Such accounting graphs are promising both as educational tools and towards the application of computational tools on accounting data.

White Paper 18: Sustainable Public Procurement, Part II, Making Use Of Environmentally Extended Input-Output Data

Fri, 10 Oct 2025 09:10:39 GMT

by Ad Min.

Adopting Open Data and Open Source tools can be a catalyst in the sustainability transition and Green Public Procurement (GPP) is a particularly opportune domain to explore this potential. In the first paper in this series we outlined key information flows and tasks that are relevant in this context. Here we dive deeper into how one can leverage a particularly promising source of economic and environmental impact information: Environmentally Extended Input-Output (EEIO) databases. We will discuss some of the challenges that must be addressed to effectively use EEIO tools in GPP, especially in European context. The use cases in focus are: how to produce an overall inventory of direct and indirect emissions for different procurement categories, and how to differentiate between green and non-green products. Some practical problems that must be tackled are: the consistent linkage of procurement data sets to EEIO databases, and the disaggregation of EEIO sectors to more granular of green / non-green products. We discuss potential approaches and their pros and cons. We analyze the specific challenge of creating a CPV-NACE mapping that would link demand driven procurement product taxonomies with supply driven economic activity classifications. We outline a methodology for disaggregating EEIO business sectors to constituent product categories with differentiated environmental impact while preserving the accounting constraints satisfied by the aggregate databases.

Portable Standardized Graph Formats for Input-Output Databases

Wed, 08 Oct 2025 13:43:31 GMT

by Ad Min.

There are currently several important global initiatives that compile and make available statistical economic input-output data (IO). This is done typically on a multi-regional basis (covering many countries and regions, hence MRIO) reflecting the fact that international trade is (still) very much a reality. Environmentally extended input-output (EEIO) databases that are in turn based on economic activity IO data, are increasingly used to examine environmental footprints of economic activities and play an important role in the attribution and screening of regional and sectoral contributions to environmental stresses.

Yet there is a lot of diversity and complexity in the organization of these typically large datasets. This complicates the adoption and use of EEIO, as it requires the dedication of time and effort to acquire and process data, both initially and potentially with any updates. Motivated by this context, we discuss a simple, generic and portable format for disseminating Input-Output data. The format is inspired from the Graph representation of Input-Output matrices. It allows a unified and very extensible description which can be serialized into standard csv files but also inside a minimal portable sqlite database file.

What can Inka Quipus teach us about data management?

Tue, 16 Sep 2025 11:30:42 GMT

by Ad Min.

A blog post about the ingenious methods used by the ancient Inca culture to encode information and what insights we might draw from them today for data science.

The value of metadata, human readibility, schema flexibility and append-only databases? Its all there!

The Green Public Procurement Challenge (Online Game)

Fri, 29 Aug 2025 12:30:42 GMT

by Ad Min.

In a new and free online game we introduce some aspects of Green Public Procurement in a simplified, fun setting that helps highlight some of the considerations involved.

In the game the player assumes the role of a public procurement manager working for a large city. The gameplay imagines our intrepid public servant (namely, you!) inheriting a challenging procurement portfolio that has a substantial environmental footprint (in terms of excess Greenhouse gas emissions). The general objective is to use the next procurement season to reduce the city’s environmental impact by making optimal choices when various procurement tenders materialize.

More background about the game (more extended instructions and glossaries) are provided in a new Open Risk Academy course.

Enjoy!

Using the Kraljic Matrix in Green Public Procurement

Fri, 08 Aug 2025 15:34:23 GMT

by Ad Min.

Sustainable Public Procurement involves significant complexity and implementation barriers as it involves diverse categories of products and services, each with their own specific sustainability and knowledge requirements. It also requires augmented organizational capacities to handle expanded information flows that provide more holistic views on market capabilities and supply chain inter-dependencies.

In this post we want to review and discuss potential applications of Kraljic methodologies specifically in the context of Green Public Procurement, and even more specifically addressing the GHG emissions footprint of public procurement activities.

NACE 2.1 Classification (2025 Revision)

Sat, 10 May 2025 13:01:34 GMT

by Ad Min.

Europe's updated economic activity classification scheme (NACE Rev 2.1 - 2025) is now documented at the Open Risk Manual, with the myriad inclusions / exclusions accessible via hyperlinks.

The old classification continues to be accessible as it will be relevant for some time during the transition period. The entries of the new classification include references to the old one (which sometimes is not 1:1).

New Open Risk White Paper: Sustainable Public Procurement. Part I: Emissions Attribution

Fri, 04 Apr 2025 14:04:07 GMT

by Ad Min.

Summary

Public Procurement represents a major opportunity to catalyze the transition of economies towards more sustainable patterns but faces important challenges.

In this new White Paper we review mechanisms that can help address key pain points through the use of open standards, open data and open source tools. In the first part we frame the overall task of Sustainable Public Procurement as an instance of portfolio management.

We outline three distinct information processing pillars that are relevant in this context. We focus here on the task of measuring and attributing greenhouse gas emissions to an existing procurement portfolio.

Structure of the paper:

In the first section we review relevant background material. In particular we go into the measurement of Greenhouse Gas (GHG) emissions as the essential new information in GPP context.
In the second section we discuss Sustainable Portfolio Management as an integrated practice, outline the main activities involved and their information technical requirements.
In the third section we discuss the basics of GHG accounting as they apply in a local government procurement context. This involves the attribution of emissions to procurement contracts on an individual and then portfolio basis. Our focus is highlighting what are informative portfolio views. We discuss the attribution of direct emissions and the challenge of attributing indirect emissions. We discuss standard GHG accounting (inventory) approaches of measuring direct emissions as exemplified e.g., by the IPCC methodologies.
In the fourth and final section we highlight interesting and relevant open data standards and open source projects in the evolving landscape of tools that can facilitate the implementation of sustainable procurement.

Why are there so many concentration indices?

Tue, 25 Feb 2025 19:02:11 GMT

by Ad Min.

In this new blog post we discuss the proliferation of indices and metrics for computing concentration risk (and related diversification and inequality indices).

We go over the underlying reasons for such proliferation.

Reason 1: Invented separately in many distinct domains
Reason 2: Multiple names for essentially the same Index
Reason 3: Generalized Families of Indexes
Reason 4: The nature of the underlying data
Reason 5: Distinct meaning and usability

What Can We Learn From Random Walks on Input-Output Tables?

Tue, 28 Jan 2025 17:38:46 GMT

by Ad Min.

In this post we elaborate on the insights we can derive when using well established Environmentally-Extended Input-Output frameworks in a slightly different manner: as the canvas for monetary random walks following the money.

Follow the Money: Random Walks on Supply and Use Graphs

Mon, 16 Dec 2024 16:49:32 GMT

by Ad Min.

In the latest Open Risk White Paper we explore how to organize Environmentally-Extended Input-Output frameworks (EEIO), and in particular their Supply and Use Table (SUT) formulation, as graphs.

Working directly with SUT systems instead of converting to symmetric IO matrices involves fewer assumptions and (in principle) higher resolution in expressing environmental impacts. We elaborate first on the representation of SUT tables as directed, weighted bipartite graphs. We discuss both closed (circular) and open system configurations, featuring source and sink nodes. These are modeled as regular and absorbing Markov Chains respectively. We outline a probabilistic random walk framework that realizes mathematically the colloquial Follow the Money concept. This enables computing a range of various existing and new metrics using the EEIO data. As an illustration, besides the standard environmental footprint metric, we introduce the concept of footprint variance or the intrinsic variability of estimates. We illustrate the overall setup using a classic numerical example from the EEIO literature.

Category split of Data Science for better usability.

Mon, 14 Oct 2024 15:38:04 GMT

by Ad Min.

The Data Science category of courses at the Academy has been growing, covering a wide range of current topics relevant for modern quantitative risk management and sustainable finance. In order to organize the content into more homogeneous sets we have now split this category into two sub-categories: Data Engineering and Data Science "proper".

While the precise boundary between these two categories may be a matter of semantics, there is clearly a more technology oriented side of Data Science that focuses on the underlying data flow and processing mechanisms, the API's, programming languages, diverse data formats and related issues, versus the information extraction part that assumes and builds on top of the engineering part.

The existing group of courses has thus been shifted into the corresponding sub-categories and future courses will appear under their respective buckets. The new categorization is of course available at the front page of the Academy. Alternatively you can also peruse the descriptions at our website.

Enjoy!

Testing the Open Risk Manual Android app

Fri, 06 Sep 2024 13:15:29 GMT

by Ad Min.

Dear Academy users,

as part of our plan to make the Open Risk Manual as widely accessible and usable as possible, we are deploying and Android app version. If you are interestested in this functionality you can try out the app during the open testing period.

You can join the testing via a web link

or directly from the Google Play App Store

Please try it out and let us know how it went!

New Course: Visualization of Time Series Data

Tue, 11 Jun 2024 20:37:17 GMT

by Ad Min.

A new course in the data science category offers a deep-dive into the structure of visualizations, in particular visualizations of timeseries data.

The course is now live here at the Academy

Pre-requisites and target audience

Knowledge of basic visualization techniques and mathematical notation of functions and maps. Familiarity with data series and their usage in data science. Should be useful for people who need to work with visualizations e.g., in the context of exploratory data analysis and who want to deepen their intuition about how visualizations are put together.

All visualizations are produced using open source Python or Javascript libraries but this is not a course about programming visualizations!

Summary of the Course

What we aim to achieve in this course is to deconstruct how both typical and less common visualizations of timeseries work.

In the first instance we decompose the visualization process into:

A mathematical transformation, which (optionally) may operate on the raw data and produce new representations thereof
A visual transformation, which converts quantitative data into a visual space

We apply this "recipe" to a large number of visualizations (21 in total), using always the same simple data series. The result is an exploration of the many diverse ways visualization can help extract meaning from data. The steps of course:

21 ways to visualize a simple timeseries

A Numerical Table is also a Visualization
Visualizing Observation Times
Visualizing Observation Values
Color Plots of Measurement Values
Bubble Plots of Measurement Values
Scatter Plots and their Limitations
Linear Line Plot and Continuity
The Step Plot and Discreteness
The Smooth Plot: Pleasant but with a stinging tail
The Area Chart: Filling up space to our advantage
New Visualization Horizons with the Horizon Chart
Abusing the Bar Chart Concept
A Sorted Bar Chart and the power of mathematical transformations
14. The Histogram Transformation
The (Probability) Density Plot and Mathematical Models
The Lag Plot and Persistence
Autocorrelation and further Arcana
The Phase Diagram and Dynamical Systems
Displaying data in the Frequency domain
A Calendar is also a Visualization
The Plot Thickens: The Weekly Calendar Version

Enjoy!

New courses in Data Science, Sustainable Finance and Credit Portfolio Management categories

Mon, 27 May 2024 19:09:55 GMT

by Ad Min.

The following three courses have been activated in the Open Risk Academy and are open to all registered users:

1. Input-Output Models as Graph Networks

Course Link

Economic Input-Output models find various applications in Sustainable Finance. They are typically expressed in term of matrices and vectors but a certain type of qualitative analysis shows strong affinity with graph theory. In this course we go over the relevant concepts and linkage between these two domains.

Summary of the Course

Step 1. In this step we discuss in more detail the motivation for the course and provide a very brief introduction to the graph theory to establish the notation.
Step 2. In this step we explore the duality between graphs and matrix representations.
Step 3. This step introduces the concept of Qualitative Input-Output Analysis
Step 4. In the fourth step off the course we discuss special kinds of nodes: Sources, Sinks and Conservation Laws
Step 5.In the final step of the course we discuss and interpret in graph terms the typical question one wants to answer with an IO model: what happens if there is new set of final demands?

2. Mathematical Representations of Credit Portfolio Data

Course Link

For our purposes in this course Credit Data is any well-defined dataset that has direct applications in the assessment of the Credit Risk of an individual or an organization. More generally, it is any dataset that allows the application of data-driven Credit Portfolio Management policies. Digging into the meaning of these data collections, the logic that binds them together, is essential for understanding what they can be used for and what limitations and issues they may be affected by. This course explores new angles to look at old practices.

Summary of the Course

Step 1. Definition of Credit Data
Step 2. Credit Data Classifications
Step 3. From Graphs to Reference Data
Step 4. Static Credit Data Snapshots
Step 5. Dynamic (Performance) Credit Data
Step 6. Scheduled versus Actual Cash Flows

3. An overview of graph methods in data science

Course Link

Graphs (and the related concept of Networks) have emerged from a relative mathematical and physics niche to an ubiquitous model for describing and interpreting various phenomena in very diverse domains. In fact the term graph appears now is so many different context it is hard to keep track of the meaning and relations between all these applications. In this course we aim to explore relations between different graph concepts as they are currently used in data science and related fields.

Summary of the Course

Step 1. Introduction
Step 2. The Graph of a Function
Step 3. The Mathematical Graph
Step 4. The Abstract Data Type (ADT) Graph
Step 5. Computation Graphs
Step 6. Data Graphs
Step 7. Property Graphs
Step 8. Knowledge Graphs
Step 9. Graph Databases
Step 10. Probabilistic Graph Models
Step 11. Graph Neural Networks (GNN)

Enjoy!

New Course: Working with Large Matrices using Command Line Tools

Thu, 09 May 2024 12:28:22 GMT

by Ad Min.

Dear Academy users,

we are happy to release a fresh new course: Working with Large Matrices using Command Line Tools.

What is this course about

In this course we explore a number of Linux command line tools (CLI):

Bash scripting
Several basic CLI commands (ls, cd, etc.)
File manipulation oriented CLI commands such as head, cut, wc
The awk programming language and scripting

We apply these in a very concrete context: working with large matrix files that form part of various economic input-output models. Such files are cumbersome to work with in spreadsheets, but on the other hand the overhead of using a full-blown statistical / data science environment might be also high. Command line tools offer a handy intermediate approach that may be useful in various context.

Prerequisites

Basic knowledge of and a working setup of a Linux or Linux-like development environment (including working with a shell and a text editor) is essential. Any standard Linux distribution should work (Using WSL on Windows machines) and MacOS as well (possibly with the installation of GNU tools).

Some exposure to scripting and any general purpose programming language (E.g., Python, Javascript, C++, Java) is required for understanding the scripts and work through the awk exercises.

The course derives motivation from the large matrix data processing task. Hence, some idea of what a matrix is and why it is relevant to know how to work with them is assumed, but it is not required for completing the course as we do now go into any mathematical aspects of matrices.

Motivation for Command Line tools
Overview and Setup of CLI Tools
A hello world in Awk
Downloading Data: Using command line tools to get published matrix data stored in local disk
Extracting Data: verify we have downloaded correct datasets and (if necessary) bring to a shape that makes it usable (e.g. uncompressing it)
Scanning Data Files: get a first high level view of what sort of files we have downloaded
Figuring out Structure and Dimensions: understand structure of the file (separators, total number of rows and columns involved and their nature).
Scrubbing / Cutting / Reshaping: create clean files where matrix data with a known number of rows and columns are stored in tab separated ascii format.
Transformations: Perform simple mathematical transformations and statistical operations. Investigate the degree to which matrix values are non-trivial (non-zero)

Resources

We will work with Input-Output matrices downloaded from well known public distributions (EXIOBASE, FIGARO, OECD-ICIO). Scripts providing guidance and solutions to the suggested exercises are available the Open Risk Academy Gitub Repositories.

Enjoy!

New Course: An Introduction to the Copernicus Satellite Data Ecosystem

Mon, 22 Apr 2024 22:15:12 GMT

by Ad Min.

Earth Day is an annual event on April 22 to demonstrate support for environmental protection. First held on April 22, 1970, Earth Day celebrations now include a wide range of events coordinated globally by earthday.org (formerly Earth Day Network) including 1 billion people in more than 193 countries.

We honor this occasion releasing a new Academy data science course that provides an introduction to the Copernicus Satellite Data Ecosystem. Copernicus is the name of an Earth observation system of the European Union's Space programme. Its objective is to look at our planet and its environment, in particular serving the needs of European citizens. Copernicus offers integrated information services (data) that draw both from Satellite based Earth Observations and In-Situ (non-space) data collection.

This course should be a useful first reading for anybody who wants to get involved in using Copernicus data but has no prior experience.

In the first step we go over a high-level overview of the Copernicus program. This should serve as a first orientation for anybody interested to work with Copernicus data but is not yet sure what is available.

In the second step we build a high level catalog of the available data resources. Copernicus is a large program, involving many institutions, diverse satellites and instruments, providing original and processed data, including additional sources of ancillary data and an ever evolving set of tools providing data access. This section aims to organize all these to some degree.

In the third step and final step of this introduction into the Copernicus programme we discuss some tools that relevant for working with Copernicus data resources. Detailed work with Copernicus data requires using diverse specialized tools but there are ongoing efforts to systematize and standardize them with various toolboxes, platforms and API's. Here we only scratch the surface of the relevant technologies to get you started!

Enjoy, and as always keep us posted with any feedback, ideas or suggestions about how to improve the Open Risk Academy.

Towards a Faceted Taxonomy of Financial Services

Wed, 06 Mar 2024 13:18:01 GMT

by Ad Min.

In a new blog post we discuss the structure and role of taxonomies in financial services. Our age is increasingly dominated by the dual challenges and opportunities of the sustainability transition on the one hand, and digital transformation on the other. We witness emerging new financial domains with novel names such as Fintech , or TechFin, or various combinations and hues of Green and Sustainable in Sustainable Finance and we see forces that are reshaping the direction of travel for the financial industry.

Understanding where and how the broader Financial System will be affected by these developments is of no small interest. Stakeholders are effectively all users of Financial Products , which means practically every economically active actor! A good example of renewed focus on “taxonomic” thinking is the EU Sustainable Finance Taxonomy an EU-wide classification system that aims to determine whether an economic activity is environmentally sustainable. Current Financial Service providers, are also keenly interested, since such systemic developments can drastically reshape business models. Last but not least, financial regulators and policymakers have the heavy burden of ensuring that these emerging financial system adaptations are fit-for-purpose. In a fully digitized economic system old fences and firewalls may no longer be relevant.

The motivation for thinking about classifications and taxonomies comes from the fact that analysing changing systems requires, at the outset, insightful, objective descriptions of their past and present states. A financial system oriented taxonomy would be a categorization or classification of concepts associated with the broader economic phenomenon we call Financial Services. A taxonomy or classification is typically a hierarchical structure in which concepts (classes, or categories) are organized into groups or types of increasing specificity.

In the post we discuss a large number of related taxonomy examples and distill some of the essential features required. This reading should be interesting to anybody interested in more holistic view of the financial system and its risks, or for those aim to understand the new forms of "unbundling" financial service provision.

Open Source and Open Education (OEWeek online chat event)

Mon, 04 Mar 2024 11:09:32 GMT

by Ad Min.

Open source software is very effective in democratizing digital capabilities across a vast range of domains. As prime example, Moodle is an open source eLearning platform that powers hundreds of thousands of learning environments globally (it provides also the basic infrastructure for the Open Risk Academy). Yet contributing to open source faces the formidable barrier of scarce technical (digital) literacy. How can we best use open source to teach about open source? Can we set in motion a virtuous cycle that will produce a reinforcing mechanism where people use open source tools to build more open source education tools? This is the topic of a free format online chat event.

The event should be interesting for anybody thinking or working at the intersection of open source and open education irrespective of which domain they specialize in. We'll try to make a number of different channels available:

as an Open Risk Academy forum and chat. This is the main venue.
a matrix channel
a mastodon discussion
our commons forum
and github discussions

The scheduled time is 5:00pm-6:00pm (Europe/Amsterdam time) on the 7th of March 2024. Come and join the discussion!

Awesome Sustainable Finance List

Tue, 20 Feb 2024 10:05:10 GMT

by Ad Min.

We are building an awesome sustainable finance list that aims to identify and highlight all open source and open data projects that make an impact on sustainable finance, understood in the broadest way. Are you aware of any project that targets this space, you are very welcome to contibute.

Particularly welcome any pointers to projects that focus on the "S" of ESG: the social dimension of finance. If you have a github account you can directly contribute here.

List of current topics (topic suggestions also welcome!)

Thank you!

A new short course providing interactive analysis of input-output models

Sun, 18 Feb 2024 14:58:50 GMT

by Ad Min.

A new short introductory course on Input-Output analysis focuses on stylized interactive calculations that can be performed directly within the online reading sections.

The level of the course is introductory. There are no mathematical nor computer science prerequisites. It should be useful for anybody wishing to obtain insights into the flow of the basic calculations behind modern large scale Environmentally Extended Input-Output Models.

The objective of the course is to provide intuition and familiarity with the basic calculation workflow, indicatively:

From the Initial IO System

Calculate the Technical Requirements Matrix:

Calculate the Leontief Inverse Matrix:

Enter a new Demand vector:

To obtain the new IO system:

Enjoy!

Connecting the Dots, Tensor Representations of Activitypub Networks

Mon, 05 Feb 2024 12:29:17 GMT

by Ad Min.

ActivityPub is a technical specification towards decentralized (more precisely, federated) social networking (termed the Fediverse) based upon the exchange of ActivityStreams messages that follow the Activity Vocabulary. The ActivityPub proposal has been standardized and published by the W3C and has motivated the design of several federated social networking systems. NB: As Open Risk we are already present on the Fediverse via a Mastodon account.

Analysing and understanding the dynamics of economic networks is of vital importance for informed decision-making. In a number of previous White Papers we reviewed and illustrated how mathematical concepts from Network and Graph theory (OpenRiskWP08,OpenRiskWP10) can be used to that effect.

Our focus in the latest White Paper (OpenRiskWP15) in the Connect the Dots series is on mathematical (in particular Tensor) representations of federated online networks that help encode succinctly certain important elements of their structure. We focus on federated networks adhering to the ActivityPub protocol, which we discuss in the relevant detail.

The classic, simple (with no self-loops), directed graph is sufficient to describe the Following/Followed connectivity of Actors within a single Server. The core idea is to map Actors to graph nodes, and express relations using graph edges.

The challenge is that actual ActivityPub networks will be quite a bit more demanding in the variety of Actor and Activities that they engage in, which limits the utility of simple graphs.

Loosely speaking, Tensors can be seen as generalizations of vectors and matrices. Vectors could be called rank-1 tensors, they have one index. Matrices are rank-2 tensors, they have two indexes or dimensions. The more indices, the higher the rank of a tensor. Adjacency Matrices are rank-2 tensors, so they are inherently limited in the complexity of the relationships they can capture. Adjacency Tensors are higher-order objects that can potentially capture more complex network relations. The multilayer adjacency tensor is a very general object that can be used to represent a wealth of complicated relationships among nodes.

The mapping of networks to tensor algebra is typically the first step in the process towards concrete applications. Depending on the task one might need to flatten the relevant tensors into the so-called supra-adjacency matrix which can then be analysed with more conventional matrix algebra.

Best wishes to all for a regenerative holiday break

Sat, 23 Dec 2023 13:50:18 GMT

by Ad Min.

Dear Open Risk Academy users, another end-of-year in upon us, with the world oscillating as ever between hope and despair, the global challenges mounting, even as our potential for problem solving grows exponentially. What to wish for this holiday season? Maybe a few moments of calm gratitude and restoring emotional balance. Maybe the warm, regenerative embrace of friends and family. Maybe reconnecting with nature and its wonders. Or maybe all of the above and more! Hope to see you all around in the new year, with renewed energy, exploring ever deeper ways in which open source transparency and collaboration can bring about meaningful change in how we aproach risk management and sustainable finance. kind regards Philippos, Open Risk

New Academy Course, an Introduction to Tensor Operations with Eigen

Fri, 10 Nov 2023 14:13:37 GMT

by Ad Min.

An Introduction to Tensor Operations with Eigen is a new course at the Open Risk Academy. It is a DeepDive into using the Eigen C++ Library to perform Tensor calculations.

What is Eigen::Tensor?

Eigen is a C++ template library for linear algebra covering matrices, vectors, numerical solvers, and related algorithms. We focus in this course on a significant extension of Eigen (the Tensor module) that extends Eigen's functionality in handling higher-dimensional numerical objects (tensors of three and higher dimensions).

Motivation for the Course

Eigen (and in particular its Tensor module) is a building block used by major open source computational libraries and frameworks such a Tensorflow and Stan. Such libraries frequently require tensor type containers (higher-dimensional than vectors and matrices). Familiarity with the Eigen::Tensor API enables developers with similar requirements to write concise, high-level C++ code that is performant on a variety of devices.

Course Objectives

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.

We learn the concept and techniques of the Eigen Tensor class
How to declare, initialize Tensors of various ranks and types and how to access Tensor elements
Elementary unary and binary operations involving Tensors
More complex operations (reductions, contractions)
Modifying the shape of Tensors

The course is now live at the Academy, the github repository hosts C++ scripts used in the course.

Pre-requisites

Basic knowledge and a working setup for C++ development (e.g., being able to add Eigen as a header only library) is required.

Mathematical notation is used liberally throughout the course to clarify (for those familiar with it) the tensor manipulation concepts but is not strictly required for benefiting from the course.

Summary of Contents

The course comprises 14 Steps covering the following topics

Step 1. Getting started with Eigen
Step 2. Tensor Class Declarations
Step 3. Tensor Class Initializations
Step 4. Working with Tensor Elements, I
Step 5. Working with Tensor Elements, II
Step 6. Random Number Initialization
Step 7. Unary Element-Wise Operations
Step 8. Binary Element-Wise Operations
Step 9. In-Memory Representations of Tensors
Step 10. Tensor Contraction Operations
Step 11. Tensor Reduction Operations
Step 12. Tensor Shape Modifying Operations
Step 13. Tensor Scanning Operations
Step 14. Review and Outlook

Course Exercises

The exercises concern writing C++ small snippets of code that accomplish a certain task. The form of each exercise is as a Catch2 test. Indicative solutions are provided in this repository.

Enjoy!

Brief Cloud Hosting Outage

Mon, 06 Nov 2023 18:56:58 GMT

by Ad Min.

Dear Academy users, due to technical issues at our hosting provider both the Open Risk Academy and the Open Risk Manual were inaccessible for a few hours today. The servers are now again online. Apologies for any inconvenience. Open Risk

Find us on the open source Fediverse!

Wed, 04 Oct 2023 09:48:39 GMT

by Ad Min.

The fediverse is a neologism for a new generation of open source social networks that finds increasing adoption by users worldwide.

Its defining feature is that it does not rely on a single centralized service but rather orchestrates (federates) communication across a (potentially) large number of servers that exchange data using a specific protocol (activityPub).

At Open Risk we are exploring the possibility of setting up such a federating server with focus on the subject matters of interest, though work currently underway may enable our Open Risk Commons to federate directly.

In the meantime we have a fediverse account where we post occasional updates and promote our vision for open source and open data approaches to (sustainable) finance and risk management.

Are you already on the fediverse or interested to explore this new universe of possibilities? You can readily open an account on an instance of your choice and connect with us there!

Academy Python based tutorials have been bumped to Python 3.10

Fri, 29 Sep 2023 11:12:26 GMT

by Ad Min.

Some Academy courses include Python based tutorials (with source files available on github). These have been now tested using the 3.10 version of the Python interpreter. The 3.10 version will be supported by PSF until 2026.

There are some minor bugs in some scripts and examples that will be fixed in the sequel but it is recommended that students of Python related courses already consider upgrading their setup to 3.10.

Crash course introduction to Input-Output model mathematics

Tue, 19 Sep 2023 15:09:08 GMT

by Ad Min.

A new crash course is available now in the Academy.

The course should be useful for people who want to refresh their linear algebra and matrix theory knowledge or want identify specific areas which they wish to study deeper. It offers a brief introduction to Input-Output Model mathematics, the basic elements of linear algebra and matrix theory that are necessary to understand the standard Input-Output models, including their environmental impact extensions. Matrix theory is the main subject covered here, as it is the dominant mathematical tool used in IO analysis. The focus is on notation and defining the mathematical objects and operations commonly used, not the economic interpretation or any mathematical proofs.

This resource can be seen as a slightly more mathematical version compared to Appendix A: Matrix Algebra for Input-Output Models as presented in the definitive textbook on IO models, namely Input-Output Analysis Foundations and Extensions by Miller and Blair. We follow roughly the naming, notation and conventions of the Encyclopedic Dictionary of Mathematics.

A summary of the main topics covered:

Basics, Matrix Definition, Matrix Families
Various Matrix Operations
Matrix-Matrix Products (Cayley, Hadamard, Kronecker etc.)
Matrix Inversion and Matrix Series
Select IO Specific Topics

You can enroll directly here. Enjoy and keep us posted with any observations, ideas or feedback on how to improve this resource.

New Course: The Climate Dictionary Quiz

Tue, 12 Sep 2023 12:20:00 GMT

by Ad Min.

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 the general public. It selects several dozen important climate concepts that are currently actively discussed worldwide with the aim to make them more accessible and relatable to individuals from various backgrounds and levels of expertise. The content is crafted to cater to diverse audiences, catering to both the scientifically inclined and those with limited prior knowledge of the subject.

A selection of Climate Risk related terms that are documented in the Open Risk Manual are already integrating the Climate Dictionary content with a focus on Risk Management and Sustainable Finance implications. As an additional resource, the Climate Dictionary Quiz accessible here at the Open Risk Academy is based on the Climate Dictionary and provides an educational tool to enable deeper understanding of the essential terminology.

The quiz consists of circa 65 questions of multiple choice type. The objective is to enable anybody interested in climate change to benchmark their knowledge of these key terms.

(*) Currently in English

Image: Temperature anomaly (deviation from long-term average) as reported by NASA for July 2023

Migration of course code repositories from main Open Risk account

Tue, 22 Aug 2023 11:56:25 GMT

by Ad Min.

Dear Academy users, the github repositories for courses that have associated code and/or data has been re-organized to improve usability. A new github organization (Open Risk Academy) now holds all such course directories (instead of the main Open Risk account).

Any old links to specific repos should be still functional (redirecting to their new location) but the best way to access the collection is through the new organization landing page linked above.

There is also a new associated github discussion page that can help with specific issues around course material available in these repos. As always the Open Risk Commons forum is available for more general discussions of tools, risk models, best practices or any other relevant issue.

Happy "back to school" to everyone!

2001 Users joined the Open Risk Academy's Space Odyssey

Wed, 28 Jun 2023 09:48:23 GMT

by Ad Min.

Dear Academy users,

we have happily reached 2001 registered users. For fans of Stanley Kubrick's extraordinary 1968 movie this is a number full of connotations.

Well, actually its way past 2001. It is anno 2023 already. While the future is not quite what is was predicted to be, it is wonderful and scary in its own way.

Digital technology is everywhere, ubiquitous computing devices in the hands of (almost) everybody, information networks spanning (almost) the entire planet, algorithms gobbling ever more data and getting ever more complex and inscrutable.

What does the dawn of the digital age mean for both old and new and emerging risks. What does it mean for our ability to learn to manage these risks?

What role can the Academy play to enable an open, widely available risk management skill-set based on open source tools and knowledge bases?

Where lies the biggest potential for impact? Is it Sustainable Finance? Or maybe Python Data Science? Or Cybersecurity or AI Risk? Maybe something else altogether that you see brewing or even "all of the above"?

I would like to invite you to chip in your opinion, suggestions and experiences to help us chart a course for the next phase of the journey. What courses or tools do you see as most relevant for our own, down to Earth, Space Odyssey?

Looking forward to hear from you. Please send a free-form email with any thoughts or remarks to academy@openriskmanagement.com

Electrifying the Doughnut: Simplified Visions of Sustainable Finance

Wed, 21 Jun 2023 13:05:37 GMT

by Ad Min.

Dear Academy users,

today is June 21, happy Solstice Day! It is also the sixth annual #ShowYourStripes Day - a time when meteorologists and other climate communicators around the world raise awareness of our warming planet by displaying colorful visuals of climate change.

An opportune moment, thus, to put together a few words and visuals inspired by the remarkable sustainability transition journey we have embarked on as societies, the changes this may bring to the shape of economic activities to come, the structure of future financial systems and the new challenges for risk management.

The blog post Electrifying the Doughnut: Simplified Visions of Sustainable Finance is a journey into well known visualizations such as Planetary Boundaries and the Doughnut Economy that have eloquently and succintly raised public perceptions about complex issues around economic sustainability.

It raises the question: Can we create more quantitative and practical versions that can be used in the context of developing sustainable finance tools and risk management? What simplifications and tradeoffs are needed? How can we reconcile and present diverse information such as spatial distribution of production and consumption, complex supply chains, energy mix and, ultimately, responsibility for transitioning towards a sustainable economy.

Enjoy!

Equinox 0.7 release focuses on scope 2 (electricity) emissions

Fri, 09 Jun 2023 22:47:37 GMT

by Ad Min.

New data models introduced in this release of Equinox cater to the requirement of integrating energy attribute certificate information into the portfolio database.

The overall procedure for accounting for Scope 2 emissions does not deviate from the established patterns of the GHG Protocol:

Description of the GHG Inventory Boundary and in particular electricity consumption within that boundary
Information on Emissions (Energy and Emission Sources, Activity data and Emission Factors associated with each activity)
Information on Methodologies of measurement and Data Quality
Information on Emission Changes (For Period-on-Period explanations)

This standard GHG quantification and reporting procedure is already mapped in the Equinox architecture, e.g. in the design of its portfolio and reference data models and reporting flows.

The peculiar case of Grid energy attributes

The peculiarity of electricity and Scope 2 emissions is that (in general) energy injected into distribution grids does not retain any of its production attributes and in particular the amount of GHG emissions that were generated during its production. This follows simply from the physics of electricity generation and transmission.

Various jurisdictions have developed certification schemes that create informational artifacts that attribute energy produced during a certain period on the basis of the generating device. Market-Based Scope 2 Accounting is an alternative Scope 2 GHG Protocol method based on GHG emissions emitted by the generators from which the reporting entity contractually purchases electricity alongside energy attribute certificates.

In order to facilitate the reporting of Scope 2 emissions under the market-based approach, the 0.7 release of Equinox introduces data models and tools for managing energy attribute certificates, in particular those following the European Energy Certificate System (EECS) standards.

Resources

Are you interested in Sustainable Portfolio Management and open source tools or eLearning material to support the energy transition? Please reach out!

Open Risk White Paper 14: Integrated energy accounting using relational databases

Sat, 20 May 2023 16:38:45 GMT

by Ad Min.

In this new Open Risk White Paper we demonstrate a concrete implementation of an integrated energy accounting framework using relational database technologies.

The framework enables accounting of non-financial disclosures (such as the physical and embodied energy footprints of economic transactions) while enforcing the familiar double-entry balance constraints used to produce conventional (monetary) accounts and financial statements.

In addition, it allows enforcing constraints associated with the flow and transformations of energy that can happen inside the organizational perimeter.

An overview of the different elements of an integrated accounting system

A schematic overview of the different elements that an integrated energy accounting system must (in-principle) consider:

The organizational boundary of a reporting entity is maybe the key element to consider first. It is something defined legally in terms of ownership and, by-and-large, it is the same as the financial reporting boundary.

At the most basic level energy accounting would focus on the asset side of the financial balance sheet and examine its physical energy profile (for example the rate of acquisition or generation of energy for business purposes). Reporting these energy mix metrics, along with the corresponding energy intensity ratios using monetary flows from the financial reporting side comprises the essence of current reporting requirements as expressed e.g., by the European Sustainability Reporting Standards.

Linking the energy consumption activity of an entity with its upstream and downstream value chains leads to hybrid environmentally extended input-output models which are currently available only at the macro-economic level, e.g. the EU Physical energy flow accounts (PEFA) system.

Connecting the energy profile of the entity with financial counterparties that provide different forms of capital leads to current environmental footprint attributions models pursued by the financial industry such as PCAF.

While material use of physical energy must in any case be accounted for, the embodied energy in various goods or services offers the most coherent representation as it ties business processes that may be disconnected in time and space yet serve the same economic purpose: providing a final product.

Last but not least, an entity may have non-trivial interactions that are not captured under financial exchanges with economic agents. This segment includes the environmental “account” that may serve both as a source of high-quality energy and as a sink of waste energy. It also includes broader contracts with society, for example the indirect impacts of energy infrastructure on communities.

White Paper Sections

Motivation and Overview: This is broadly non-technical overview that is building on the more mathematical and conceptual framework developed in WP12
European Sustainability Reporting Requirements: A review the energy-related reporting requirements of the newly introduced (but not yet final) European Sustainability Reporting Standards (ESRS)
EcoWidgetCo worked out example: We will track the activities of a fictitious company, an ambitious new green venture that builds micro-mobility widgets using recycled materials and (mostly) renewable energy. We sketch how several periods of EWC’s existence and operations could be represented in an integrated energy accounting context.
Postgres SQL Implementation: We describe how the framework of integrated energy accounting can be implemented using the concepts and tools of relational databases, with a focus on the schema structure and the triggers that are required to enforce generalized balance sheet equations and physical energy laws. The implementation is open source and available to explore in the Open Risk repository.

Getting involved with the European Sustainability Reporting Standards

Thu, 11 May 2023 15:20:26 GMT

by Ad Min.

Dear all,

the European Sustainability Reporting Standards (ESRS) are promising to completely reshape the business reporting landscape in Europe over the coming years. A massive amount of new, non-financial information will have to be collected and disclosed, alongside the traditional financial (monetary) considerations. In turn this will have revolutionary impact on risk management, in particular ESG risks.

If you are involved in any aspect of sustainability, especially if based in Europe, feel free to explore and get involved with any of the resources we are putting together around the ESRS.

At the Open Risk Manual expanding the knowledge base around sustainable finance with more detailed glossaries and entries focused on the ESRS standards.
Here at the Academy with courses like the introduction to Input-Output models that are one the key tools in examining value chain impacts.
At the Open Risk Commons forum where a new dedicated category serves as discussion forum for anybody interested in the details of ESRS.
In term of software for sustainable portfolio management, equinox is the only open source solution entirely dedicated to this task. Join the discussion in the forum or on github.

The XBRL Glossary collection at the Open Risk Manual

Fri, 28 Apr 2023 16:01:35 GMT

by Ad Min.

The XBRL Glossary categoy of the Open Risk Manual collects definitions of various XBRL terms.

The focus of the glossary is to try to clarify the technical nomenclature as it appears in the XBRL specification, which is somewhat arcane and confusing. General business reporting terms are in separate categories under the XBRL / Accounting terms categories.

In due course the aim is to further populate the examples of the various glossary entries and potentially also include relevant snippets illustrating the XBRL format.

Feedback, ideas or recommendations can be provided anonymously by clicking on the "Help improve this page" link that is at the bottom of every entry of the Manual.

Getting started with Open Source: The Amazing Jupyter Universe

Fri, 31 Mar 2023 17:05:42 GMT

by Ad Min.

Dear Academy users,

In a previous module of the Getting Started with Open Source course we discussed the Linux operating system which is the bedrock and maybe most significant example of open source success.

For our purposes the OS is but the enabling platform. We are primarily interested in running or developing applications (for example risk models and risk management tools) on top of the operating system. 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 found massive adoption in diverse applications. This open source data science spring happens across diverse language and system communities, including old workhorses such as C++, Java but also newcomers such as Rust.

Yet a triad of ecosystems within that broader universe (namely Python, R and Julia) are distinguished by having a very important or even exclusive data science profile and impact. These three revolutionized the way we do data science today as compared to even just a decade ago.

One nickname that has been given to this set of data science oriented language is Jupyter. Its a loose word game with the initials of "Julia, Python and R" and the planet Jupiter. The name and logo are an homage to Galileo's discovery of the moons of Jupiter, as documented in notebooks attributed to Galileo.

In this module we undertake a side by side comparison of a wide range of aspects of the Python, Julia and R language ecosystems. The table of contents is listed below. This comparison is neither exhaustive nor conclusive. It is merely a map all of the important tools that are out there!

Motivation and Objectives

History and Community

Devices and Operating Systems

Package Management

Package Documentation

Language Characteristics

Development Environment

Files, Databases and Data Manipulation

Data Quality, Validation and Workflow Management

Stochastic Processes and Econometrics

Machine Learning Libraries

GeoSpatial Libraries

Visualization

Web, Desktop and Mobile Deployment

Semantic Web / Semantic Data

Privacy-Preserving Computation / Federated Learning

Bindings to Other Languages

High Performance Computing

Using R, Python and Julia together

Getting started with Open Source: Linux module

Thu, 30 Mar 2023 14:41:28 GMT

by Ad Min.

Dear Academy users, after some time we have started revamping the Getting started with Open Source course. The first new part to be released focuses on the Linux operating system. The module highlights the importance that Linux plays in the broader Open Source movement and provides a first overview of some important elements.

This course might be for you if you are reasonably technical and comfortable with computers and have not really been into Linux much but might be tempted. You hear alot of good things about open source ecosystems based on Linux and how they can empower your work but your are not quite sure where and how to start. Maybe you are more into research and academic work and want to get closer to the "bare metal" on which to develop and productionize your models and algorithms. Maybe you are already comfortable with Windows systems but you would like to explore containers and cloud computing.

The course table of contents is listed below. There is also an (experimental) chat facility to try out if you want to discuss things about Linux.

Motivation and Objective

The Linux Kernel

Linux Distributions

Linux Software Managers

Linux Windows and Desktop Environments

A brief history of Linux

Learning more about Linux

Getting started with Linux - Chat

Open Risk White Paper 13: Federated Credit Systems, Part II: Techniques for Federated Data Analysis

Wed, 22 Mar 2023 20:42:41 GMT

by Ad Min.

In this Open Risk White Paper, the second of series focusing on Federated Credit Systems, we explore techniques for federated credit data analysis. Building on the first paper where we outlined the overall architecture, essential actors and information flows underlying various business models of credit provision, in this step we focus on the enabling arrangements and techniques for building Federated Credit Data Systems and enabling Federated Analysis.

We start with a brief and non-technical description on privacy-preserving technologies, focusing on the special role of federated analysis within the spectrum of cryptographic approaches to multi-party computation.

We then discuss generative processes of credit data that both motivate federated analysis uses cases and shape its specific characteristics in the context of the financial sector.

We proceed to define the concept of a federated credit data system, with the federated master data table as an iconic outcome. Building on that layout we sketch how generic algorithms might be structured in a federated analysis context, giving examples from concentration risk analysis.

We conclude with thoughts on the potential challenges to realize and benefit from federated systems in finance. You can find this White Paper in the usual place. Comments, remarks, feedback etc. always welcome on our reddit sub or the Open Risk Commons

Mathematical Representations of Credit Portfolio Data (New Blog Post)

Thu, 09 Mar 2023 15:42:51 GMT

by Ad Min.

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. Digging into the meaning of these data collections, the logic that binds them together, is essential for understanding what they can be used for and what limitations and issues they may be affected by.

This new blog post explores a new angle to look at an old practice. Enjoy!

The second part of the Mortgage Data Processing series is now online

Fri, 03 Mar 2023 16:55:40 GMT

by Ad Min.

Course (PYT37066) is now available on the Academy for all users

Course Content:

This crash course illustrates how to process loan-level US Agency mortgage data using awk, pandas and django. The second part of the course focuses on the performing book. This part covers the following topics:

Concepts of the Credit Life Cycle and how changing states are captured in Loan Data as Dynamic (Variable) Fields with a focus on performing loans (excluding delinquent loans)
Selecting performing loan data using awk and pandas, manipulating and exporting derived data models using pandas
Data Quality Concepts for Performing Loans and Concepts from Bitemporal Databases
Importing performing book credit data models into a django based web platform (openNPL) that enables further interactive work with such data

Nota Bene: The course requires actual historical loan performance data for its proper completion. Those data are not provided within the course. Students must source such data themselves from the Data Dynamics website and agree to be in compliance with the applicable terms and conditions.

Who Is This Course For:

The course is useful to:

Data Engineers / Data Scientists across the financial industry and beyond that need to work with mortgage data
Credit Risk Management professionals and students
Credit Portfolio Management professionals

How Does The Course Help:

Mastering the course content provides background knowledge towards the following activities:

Improved ability to process large loan-level historical performance data
Pre-process, categorize, segment and improve on such data sets in preparation for further analysis

What Will You Get From The Course:

You will be able to confidently work with Loan-level historical performance data
You will be able to contribute to the specific use cases mentioned above

Course Level and Difficulty Level:

This course is part of the Risk Modeling using Python family.

This is a Core Level course in Risk Modelling. A good grounding at Introductory level to various Data Engineering and Data Science topics is a prerequisite for making the most out of this course.
This is a Technical course which means certain technology elements (Python, CLI) are needed for mastering the material.

If you have not taken an Open Risk Academy course before the "CrashCourse Academy Demo" provides a quick overview of the Academy.

The following table places the course in the Open Risk Academy skills diagram:

Course Level & Type
	Introductory Level	Core Level	Advanced Level
Non-technical
Technical		CrashProgram PYT37066

Course Material:

The course material comprises the following:

Five Readings (Steps)
Associated Scripts (available in the repository)

Time Requirements and Important Dates

The course is self-paced and can be undertaken at any point. It requires a commitment of about five hours total, depending on student familiarity and existing development environment.
It is advisable to pursue this course after completing the first part of the series

Where To Get Help:

If you get stuck on any issue with the course or the Academy:

If the issue is related to the course topics / material, check in the first instance the Course Forum
If the issue is related the operation of the Open Risk Academy check first the Academy FAQ. If the issue persists contact us at info@openrisk.eu

New Course: Processing (US) Agency Mortgage Data Using Awk, Pandas (Part 1)

Wed, 08 Feb 2023 12:29:57 GMT

by Ad Min.

A new crash course (PYT26065) is now available on the Academy for all users

Course Content:

This crash course illustrates how to process loan-level US Agency mortgage data using awk, pandas and django. The first part of the course focuses on static (acquisition) type attributes. This part covers the following topics:

Downloading and preprocessing historical loan-performance datasets using awk
Processing loan-performance datasets using pandas
Working and fixing any missing data type issues
Classifying data attributes according to a Credit Data Taxonomy
Manipulating and exporting derived data models using pandas
The Split-Apply-Combine process
Importing data models into a django based web platform (openNPL) that enables interactive work with the data

Nota Bene: The course requires actual historical loan performance data for its proper completion but those data are not provided. Students must source such data themselves from the Data Dynamics website and agree to be in compliance with the applicable terms and conditions.

Who Is This Course For:

The course is useful to:

Data Engineers / Data Scientists across the financial industry and beyond that need to work with mortgage data
Credit Risk Management professionals and students
Credit Portfolio Management professionals

How Does The Course Help:

Mastering the course content provides background knowledge towards the following activities:

Improved ability to process large loan-level historical performance data
Pre-process, categorize, segment and improve on such data sets in preparation for further analysis

What Will You Get From The Course:

You will be able to confidently work with Loan-level historical performance data
You will be able to contribute to the specific use cases mentioned above

Course Level and Difficulty Level:

This course is part of the Risk Modeling using Python family.

This is a Core Level course in Risk Modelling. A good grounding at Introductory level to various Data Engineering and Datea Science topics is a prerequisite for making the most out of this course.
This is a Technical course which means certain technology elements (Python, CLI) are needed for mastering the material.

If you have not taken an Open Risk Academy course before the "CrashCourse Academy Demo" provides a quick overview of the Academy.

The following table places the course in the Open Risk Academy skills diagram:

Course Level & Type
	Introductory Level	Core Level	Advanced Level
Non-technical
Technical		CrashProgram PYT26065

Course Material:

The course material comprises the following:

Five Readings (Steps)
Associated Scripts (available in the repository)

Time Requirements and Important Dates

The course is self-paced and can be undertaken at any point. It requires a commitment of about five hours total, depending on student familiarity and existing development environment.

Where To Get Help:

If you get stuck on any issue with the course or the Academy:

If the issue is related to the course topics / material, check in the first instance the Course Forum
If the issue is related the operation of the Open Risk Academy check first the Academy FAQ. If the issue persists contact us at info@openrisk.eu

Latest version of openNPL starts support for Fannie Mae Loan Performance Data

Wed, 18 Jan 2023 22:38:37 GMT

by Ad Min.

The openNPL credit portfolio management platform implements and builds on the detailed European Banking Authority loan templates for NPL data. It thereby enables the collection and easy management of non-performing loan data according to best-practices.

In the the latest update (0.5.3) the platform is expanded to enable working also with US Agency (Fannie Mae) Mortgage Loan Performance data. This functionality is still under development and will mature with the upcoming 0.6 release of openNPL (along with other related resources) so stay tuned! The updated code documentation is available here. The corresponding data dictionaries and concepts are documented with a new category at the Open Risk Manual.

Academy Course DAT31063 (Class Inheritance in Data Science) has been updated

Thu, 29 Dec 2022 16:51:17 GMT

by Ad Min.

The course content and supporting code have been updated:

Another year in permacrisis, yet the future is in our hands

Fri, 23 Dec 2022 16:52:13 GMT

by Ad Min.

Dear users and friends of the Open Risk Academy, it is this time of the year again... Where the, all too-visible, signs of fragility and failure in how we collectively organize our affairs and communities across the globe must be internalized and transformed into positive learnings towards a more resilient future.

Not an easy task: our infatuations, lazy habits, poor information access and poor decisions that make no rational or emotional sense time and again take the upper hand and create exhaustion and a sense of impossibility. Yet there is no option but persist with an agenda that empowers invididuals and organizations to enhance welfare at all levels. After all, everything positive that has been achieved was due to somebody acting.

At Open Risk we will continue to try contibute our small effort towards the open future of risk management. We wish you too, a regenerative break this holiday season and a healthy and productive 2023.

Solstice - a new framework for simulating economic networks

Thu, 24 Nov 2022 18:49:23 GMT

by Ad Min.

Dear all,

we've started releasing bits and pieces of a new open source tool we are building (the Solstice simulation framework) on our github repo and more is comming over the next weeks. You can check out the first installment of the Solstice manual which describes the analytic framework behind Solstice.

The analytic framework has the following core components:

A representation of economic entities as property graphs (nodes and edges with associated attributes) as discussed in our earlier white papers (number 8 and 10 in particular)
A representation of network-wide factors and dynamics drivers as macro variables
Sources of uncertainty (both macro (system-wide) and idiosyncratic (entity-specific)
A discrete temporal grid where future states of the economic network and (any) macro variables are modeled
Network evolution along the temporal grid due to both deterministic and stochastic elements that follows by a variety of risk distributions / models using potentially a combination of model components (satellite models)
Bottom up composition of network state changes using elementary "system updates"
Ability to condition on specific realizations of (in particular) macro factors, which emulates scenario analysis / stress testing
Introducing special entities that interact with the network in systemic ways (e.g. financial intermediaries, sovereigns or regulatory entities) with specialized internal states
Collection of sampling statistics of network evolution and distillation of useful risk metrics and reports

If you are interested to use and/or contribute to our open source projects please follow and star them on github and (if appropriate) raise issues with ideas or functionality that you would like to see.

Academy News

New Course: FOSS (Open Source) Business Model Risk Canvas

Analysing the volatility of financed emissions using waterfall diagrams (blog post)

The Open Risk Manual is now open to Academy users

Mathematical Formulation of Financial Statements

Open Risk White Paper 19: Connecting the Dots: Accounting Graphs for Double and Quadruple-Entry Bookkeeping

White Paper 18: Sustainable Public Procurement, Part II, Making Use Of Environmentally Extended Input-Output Data

Portable Standardized Graph Formats for Input-Output Databases

What can Inka Quipus teach us about data management?

The Green Public Procurement Challenge (Online Game)

Using the Kraljic Matrix in Green Public Procurement

NACE 2.1 Classification (2025 Revision)

New Open Risk White Paper: Sustainable Public Procurement. Part I: Emissions Attribution

Summary

Structure of the paper:

Why are there so many concentration indices?

What Can We Learn From Random Walks on Input-Output Tables?

Follow the Money: Random Walks on Supply and Use Graphs

Category split of Data Science for better usability.

Testing the Open Risk Manual Android app

New Course: Visualization of Time Series Data

Pre-requisites and target audience

Summary of the Course

21 ways to visualize a simple timeseries

New courses in Data Science, Sustainable Finance and Credit Portfolio Management categories

1. Input-Output Models as Graph Networks

Summary of the Course

2. Mathematical Representations of Credit Portfolio Data

Summary of the Course

3. An overview of graph methods in data science

Summary of the Course

New Course: Working with Large Matrices using Command Line Tools

What is this course about

Prerequisites

Table of Contents

Resources

New Course: An Introduction to the Copernicus Satellite Data Ecosystem

Towards a Faceted Taxonomy of Financial Services

Open Source and Open Education (OEWeek online chat event)

Awesome Sustainable Finance List

A new short course providing interactive analysis of input-output models

Connecting the Dots, Tensor Representations of Activitypub Networks

Best wishes to all for a regenerative holiday break

New Academy Course, an Introduction to Tensor Operations with Eigen

What is Eigen::Tensor?

Motivation for the Course

Course Objectives

Pre-requisites

Summary of Contents

Course Exercises

Brief Cloud Hosting Outage

Find us on the open source Fediverse!

Academy Python based tutorials have been bumped to Python 3.10

Crash course introduction to Input-Output model mathematics

New Course: The Climate Dictionary Quiz

Migration of course code repositories from main Open Risk account

2001 Users joined the Open Risk Academy's Space Odyssey

Electrifying the Doughnut: Simplified Visions of Sustainable Finance

Equinox 0.7 release focuses on scope 2 (electricity) emissions

The peculiar case of Grid energy attributes

Resources

Open Risk White Paper 14: Integrated energy accounting using relational databases

An overview of the different elements of an integrated accounting system

White Paper Sections

Getting involved with the European Sustainability Reporting Standards

The XBRL Glossary collection at the Open Risk Manual

Getting started with Open Source: The Amazing Jupyter Universe

Getting started with Open Source: Linux module

Open Risk White Paper 13: Federated Credit Systems, Part II: Techniques for Federated Data Analysis

Mathematical Representations of Credit Portfolio Data (New Blog Post)

The second part of the Mortgage Data Processing series is now online

Course (PYT37066) is now available on the Academy for all users

Course Content:

Who Is This Course For:

How Does The Course Help:

What Will You Get From The Course:

Course Level and Difficulty Level:

Course Material:

Time Requirements and Important Dates

Where To Get Help: