Blog

Federated Credit Systems, Part I: Unbundling the Credit Provision Business Model

As an architectural design and information technology approach, federation has received increased attention in domains such as the medical sector (under the name federated analysis), in official statistics (under the name trusted data) and in mass computing devices (smartphones), under the name federated learning.

Using Sankey Diagrams

Sankey Diagrams are a type of flow diagram composed of interconnected arrows. The width of the arrows is proportional to the flow rate. Sankey diagrams are often used in physical sciences (physics, chemistry, biology) and engineering but also in economics. They can be used to represent the relative role and significance of various inputs and outputs in a given process.

openNPL 0.2 release

The open source openNPL platform supports the management of standardized credit portfolio data for non-performing loans. In this respect it implements the detailed European Banking Authority NPL loan templates. openNPL aims to be at the same time easy to integrate in human workflows (using a familiar web interface) and integrate into automated (computer driven) workflows.

Risk Management will not be the same going forward: too much is at stake

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.

openNPL now Available in Dockerized Form

Following up on the first release of openNPL the platform is now available to install using Docker. Running openNPL via docker is the installation option that simplifies the manual process (but a working docker installation is required!).

Docker Hub

You can pull the latest openNPL image from Docker Hub ( This method is recommended if you do not want to mess with the source distribution).

Course Objective

This course is a deep-dive into the structure of visualizations, in particular visualizations of timeseries data. The course is now live at the Academy.

Non-Performing Loans

The covid-19 crisis will certainly impact the concentration of Non-Performing Loans but given the special nature of this economic crisis compared (in particular) with the 2008 financial crisis it is unclear how precisely things will evolve.

In a previous post and white paper (OpenRiskWP07_022616) we discussed the importance of advancing open and transparent methodologies for managing the risks associated with such credit portfolios. Effective management of NPL is also a top regulatory priority. Following calls from the EU Commission and the EU Council to develop data templates to reduce information asymmetries between potential buyers and sellers of NPL, the European Banking Authority (EBA) has developed such standardised data templates.

What is Risk Compensation?

Risk Compensation is a behavioral model of human attitudes towards risk which suggests that people might adjust their behavior in response to the perceived level of risk. It follows that, depending on the strength of the effect, that it might counteract and even annul the impact of risk mitigation, if the updated attitude and behavior modifies the actual underlying risk

The community mobility reports and OpenCPM

In a previous post we introduced new OpenCPM functionality that integrates COVID-19 community mobility data (currently from Google). The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

The community mobility reports and OpenCPM

As the COVID-19 pandemic unfolded technology providers (most notably Google and Apple) made available to the public aggregated and anonymized data about human mobility in the crisis period (on the basis of smartphone location data). These Community Mobility Reports provide insights into how mobility patterns changed in response both to pandemic news and policies aimed at combating COVID-19.

Course Content

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

Agent-Based Models

The origins and early years

According to Wikipedia an agent-based model (ABM) is

ABM: class of computational models for simulating the actions and interactions of autonomous agents (both individual or collective entities such as organizations or groups) with a view to assessing their effects on the system as a whole.

Course Content

This course is an introduction to the concept of credit contagion. It covers the following topics:

• Contagion Risk Overview and Definition
• Various Contagion Types and Modelling Challenges
• The Simple Contagion Model by Davis and Lo
• Supply Chains Contagion
• Sovereign Contagion

Connecting the Dots: Economic Networks as Property Graphs

We develop a quantitative framework that approaches economic networks from the point of view of contractual relationships between agents (and the interdependencies those generate). The representation of agent properties, transactions and contracts is done in the context of a property graph.

A typical use case for the proposed framework is the study of credit networks.

A survey of existing definitions of risk

When looking up the meaning of Risk we are confronted with a surprising situation. There is no satisfying and authoritative general purpose one-line definition that we can adopt without second thoughts. Let us start with the standard dictionary definitions:

What do people talk about at FOSDEM 2020

Introduction

FOSDEM is a non-commercial, volunteer-organized European event centered on free and open-source software development. It is aimed at developers and anyone interested in the free and open-source software movement. It aims to enable developers to meet and to promote the awareness and use of free and open-source software. FOSDEM is held annually since 2001, usually during the first weekend of February, at the Université Libre de Bruxelles Solbosch campus in the southeast of Brussels, Belgium. The history of FOSDEM is neatly available at Wikipedia, while the current conference (2020) website is available here.

Making Open Risk Data easier

In an earlier blog post we discussed the promise of Open Risk Data and how the widespread availability of good information that is relevant for risk management can substantially help mitigate diverse risks.

The list of Open Risk Data providers, particularly from public sector, keeps increasing and we are aiming to document all available datasets in the dedicated page of the Open Risk Manual.

The integration of climate risk and broader sustainability constraints into risk management is a monumental task and many tools are still lacking. Yet there is strong support and bold initiatives from policy bodies and an increasing focus from the private sector side.

Semantic Web Technologies

The Risk Model Ontology is a framework that aims to represent and categorize knowledge about risk models using semantic web information technologies.

In principle any semantic technology can be the starting point for a risk model ontology. The Open Risk Manual adopts the W3C’s Web Ontology Language (OWL). OWL is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things. OWL is a computational logic-based language such that knowledge expressed in OWL can be exploited by computer programs, e.g., to verify the consistency of that knowledge or to make implicit knowledge explicit. OWL documents, known as ontologies, can be published in the World Wide Web and may refer to or be referred from other OWL ontologies. OWL is part of the W3C’s Semantic Web technology stack, which includes RDF, RDFS, SPARQL, etc

The motivation for federated credit risk models

Federated learning is a machine learning technique that is receiving increased attention in diverse data driven application domains that have data privacy concerns. The essence of the concept is to train algorithms across decentralized servers, each holding their own local data samples, hence without the need to exchange potentially sensitive information. The construction of a common model is achieved through the exchange of derived data (gradients, parameters, weights etc). This design stands in contrast to traditional model estimation where all data reside (or are brought into one computational environment).