Open Data

The Open Risk Manual is now available also as an Android App

The Open Risk Manual is an open online repository of information (wiki) about risk management in all its forms. The Manual is developed and maintained by Open Risk. Our objective is to create a comprehensive, detailed, authoritative collection of risk management resources that are easily accessible by anybody, anywhere - well, network access is currently required!

An Awesome List for Sustainable Finance.

A curated list of sustainable finance resources. The focus of the list is on code (tools, libraries, frameworks etc.) that fairly directly support any type of sustainable finance effort and open data that are useful in a sustainable finance context.

Introduction

In this fourth and final installment we will discuss how the data framework we have developed thus far can be mapped into classic portfolio management concepts and categories, and thus, how one can articulate the concept of sustainable procurement management on a portfolio basis. The concepts and analytic methodologies of financial portfolio management¹ can significantly enhance the toolkit available to practitioners and, in sense, connects the domain of Green Public Procurement to other ongoing initiatives in broader Sustainable Finance.

Introduction

This is the third in a series of posts where we explore the role of Open Data and Open Source in enabling and accelerating the broad based effort towards Green Public Procurement (GPP). In this third installment we will link procurement entities to private sector sellers and, through the sectoral profile of the procurement contract, (CPV category) we will infer the amount of CO2 emissions that can be attributed to these activities.

Introduction

This is the second in a series of posts where we explore the role of Open Data and Open Source in enabling and accelerating the broad based effort towards Green Public Procurement (GPP).

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) terms in this sentence, so our first order of business will be to unpack them.

Course Objective

The objective of the course is to discuss the relation of economic input-output models with graph theory and networks.

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.

Visualizing a year in lockdowns and restricted mobility

As we move into February 2021 the world will be experiencing almost a year under pandemic conditions. This has markedly changed behavioral patterns of human mobility across the board. One major difference with previous pandemics is that through the use of a variety of digital technologies and new data collection channels we know have an unprecedented view of those changing mobility patterns.

Constructing a Global Mobility Index (GMI)

In previous posts (here, and here) we introduced new Open Risk Dashboard functionalities that integrate COVID-19 community mobility data (currently focusing on the datasets provided by Google).

As a reminder, these reports chart over time human mobility trends collected from mobile geolocation data. The granularity is by geography and across different categories of places / activities such as retail and recreation areas, groceries and pharmacies, parks, transit stations, workplaces, and residential areas. Through these data sets we have available (for the first time in history) an overall quantitative view of global mobility (and Mobility Risk )!

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.

Pre-requisites

Knowledge of basic visualization techniques and mathematical notation of functions and maps. Familiarity with data series and their usage in data science.

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.

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 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).

Visualization of large scale economic data sets

Economic data are increasingly being aggregated and disseminated by Statistics Agencies and Central Banks using modern API’s (application programming interfaces) which enable unprecedented accessibility to wider audiences. In turn the availability of relevant information enables more informed decision-making by a variety of actors in both public and private sectors. An excellent example of such a modern facility is the European Central Bank’s Statistical Data Warehouse (SDW), an online economic data repository that provides features to access, find, compare, download and share the ECB’s published statistical information.

Motivation for Building an open source database based on EBA’s Standardized NPL Templates

In an insightful recent piece, “Overcoming non-performing loan market failures with transaction platforms”, Fell et al. dug deeply into the market failures that help perpetuate the Non-performing loan (NPL) problem. They highlight, in particular, information asymmetries and the attendant costs of valuing NPL portfolios as key obstacles. In the same wavelength, the European Banking Authority published standardized NPL data templates as a step towards reducing the obstacles that prevent the reduction of NPL’s.

The Promise of Open Risk Data

There is a legend that every time a data set is released into the open, somewhere dies a black swan

Well, it is not a true legend. Legends take centuries of oral storytelling to form. In our frantic age, dominated by the daily news cycle and viral twitter storms, legends have been replaced by the rather more short-lived memes and #hashtags.

Risk Management Internship

In finance, it’s the best of times, it’s the worst of times

It is a special moment to start a career in financial services. We are walking amid the ruins of the previous financial order. Fallen banks, broken markets, negative interest rates, shell-shocked economies and discredited theoretical assumptions. We see the enormous cost and impact to the welfare of society of a less than perfect financial system which has not kept pace with the advancement of our general knowledge and technical capabilities in most other domains.

May the network be with you in 2016

From Open Risk, to all our friends, colleagues, collaborators, users, partners and the public: