Financial data unbound: The value of open data for individuals and institutions

Curated on Posted on by Stefaan Verhulst

Paper by McKinsey Global Institute: “As countries around the world look to ensure rapid recovery once the COVID-19 crisis abates, improved financial services are emerging as a key element to boost growth, raise economic efficiency, and lift productivity. Robust digital financial infrastructure proved its worth during the crisis, helping governments cushion people and businesses from the economic shock of the pandemic. The next frontier is to create an open-data ecosystem for finance.

Already, technological, regulatory, and competitive forces are moving markets toward easier and safer financial data sharing. Open-data initiatives are springing up globally, including the United Kingdom’s Open Banking Implementation Entity, the European Union’s second payment services directive, Australia’s new consumer protection laws, Brazil’s drafting of open data guidelines, and Nigeria’s new Open Technology Foundation (Open Banking Nigeria). In the United States, the Consumer Financial Protection Bureau aims to facilitate a consumer-authorized data-sharing market, while the Financial Data Exchange consortium attempts to promote common, interoperable standards for secure access to financial data. Yet, even as many countries put in place stronger digital financial infrastructure and data-sharing mechanisms, COVID-19 has exposed limitations and gaps in their reach, a theme we explored in earlier research.

This discussion paper from the McKinsey Global Institute (download full text in 36-page PDF) looks at the potential value that could be created—and the key issues that will need to be addressed—by the adoption of open data for finance. We focus on four regions: the European Union, India, the United Kingdom, and the United States.

By open data, we mean the ability to share financial data through a digital ecosystem in a manner that requires limited effort or manipulation. Advantages include more accurate credit risk evaluation and risk-based pricing, improved workforce allocation, better product delivery and customer service, and stronger fraud protection.

Our analysis suggests that the boost to the economy from broad adoption of open-data ecosystems could range from about 1 to 1.5 percent of GDP in 2030 in the European Union, the United Kingdom, and the United States, to as much as 4 to 5 percent in India. All market participants benefit, be they institutions or consumers—either individuals or micro-, small-, and medium-sized enterprises (MSMEs)—albeit to varying degrees….(More)”.

The State of Global Emotions

Curated on Posted on by Stefaan Verhulst

Gallup: “Nobody was alone in feeling more sad, angry, worried or stressed last year. Gallup’s latest Negative Experience Index, which annually tracks these experiences worldwide in more than 100 countries and areas, shows that collectively, the world was feeling the worst it had in 15 years. The index score reached a new high of 32 in 2020.

Line graph. The Negative Experience Index, an annual composite index of stress, anger, worry, sadness and physical pain, continued to rise in 2020, hitting a new record of 32.

Gallup asked adults in 115 countries and areas if they had five specific negative experiences on the day preceding the survey. Four in 10 adults said they had experienced worry (40%) or stress (40%), and just under three in 10 had experienced physical pain (29%) during a lot of the previous day. About one in four or more experienced sadness (27%) or anger (24%).

Already at or near record highs in 2019, experiences of worry, stress, sadness and anger continued to gain steam and set new records in 2020. Worry and sadness each rose one percentage point, anger rose two, and stress rocketed up five. The percentage of adults worldwide who experienced pain was the only index item that declined — dropping two points after holding steady for several years at 31%.

But 2020 officially became the most stressful year in recent history. The five-point jump from 35% in 2019 to 40% in 2020 represents nearly 190 million more people globally who experienced stress during a lot of the previous day.

Line graph. Reported stress worldwide soared to a record 40% in 2020 amid the COVID-19 pandemic.

Worldwide, not everyone was feeling this stress to the same degree. Reported stress ranged from a high of 66% in Peru — which represents a new high for the country — to a low of 13% in Kyrgyzstan, where stress levels have historically been low and stayed low in 2020….(More)”

Turning data into public value: European lessons on unleashing the transformative power of city data

Curated on Posted on by Stefaan Verhulst

Paper by Anushri Gupta and Luca Mora: “The age of big data and smart city technologies provides city governments with unprecedented potential for data-driven decision making. Committed to constantly developing new urban policy and supporting urban operations, city governments have been using data describing the functioning of urban infrastructure assets and public services for a very long time. However, the widespread diffusion of digital systems has now created a remarkable new window of opportunity.


With many digital solutions being introduced into the built environment to improve the sustainability of urban sociotechnical systems, enormous amounts of data are constantly generated at the city level, and at unprecedented speed. City surveillance cameras, government applications for public services, building automation systems, intelligent transport systems, and smart grids are some examples of digital technologies which are contributing to producing an exhaustive stream of data “that can be harnessed to provide urban intelligence and reshape the practices and processes of public administrations”, creating a fertile environment for innovation and entrepreneurial activity. When attempting to tap into these large streams of city data, however, the opportunity to deliver sustainable value is met with significant sociotechnical challenges, which undermine the capability of urban development actors….(More)”.

Charting the ‘Data for Good’ Landscape

Curated on Posted on by Stefaan Verhulst

Report by Jake Porway at Data.org: “There is huge potential for data science and AI to play a productive role in advancing social impact. However, the field of “data for good” is not only overshadowed by the public conversations about the risks rampant data misuse can pose to civil society, it is also a fractured and disconnected space. There are a myriad of different interpretations of what it means to “use data for good” or “use AI for good”, which creates duplicate efforts, nonstrategic initiatives, and confusion about what a successfully data-driven social sector could look like. To add to that, funding is scarce for a field that requires expensive tools and skills to do well. These enduring challenges result in work being done at an activity and project level, but do not create a coherent set of building blocks to constitute a strong and healthy field that is capable of solving a new class of systems-level problems.

We are taking one tiny step forward in trying to make a more coherent Data for Good space with a landscape that makes clear what various Data for Good initiatives (and AI for Good initiatives) are trying to achieve, how they do it, and what makes them similar or different from one another. One of the major confusion points in talking about “Data for Good” is that it treats all efforts as similar by the mere fact that they use “data” and seek to do something “good”. This term is so broad as to be practically meaningless; as unhelpful as saying “Wood for Good”. We would laugh at a term as vague as “Wood for Good”, which would lump together activities as different as building houses to burning wood in cook stoves to making paper, combining architecture with carpentry, forestry with fuel. However, we are content to say “Data for Good”, and its related phrases “we need to use our data better” or “we need to be data-driven”, when data is arguably even more general than something like wood.

We are trying to bring clarity to the conversation by going beyond mapping organizations into arbitrary groups, to define the dimensions of what it means to do data for good. By creating an ontology for what Data for Good initiatives seek to achieve, in which sector, and by what means, we can gain a better understanding of the underlying fundamentals of using data for good, as well as creating a landscape of what initiatives are doing.

We hope that this landscape of initiatives will help to bring some more nuance and clarity to the field, as well as identify which initiatives are out there and what purpose they serve. Specifically, we hope this landscape will help:

  • Data for Good field practitioners align on a shared language for the outcomes, activities, and aims of the field.
  • Purpose-driven organizations who are interested in applying data and computing to their missions better understand what they might need and who they might go to to get it.
  • Funders make more strategic decisions about funding in the data/AI space based on activities that align with their interests and the amount of funding already devoted to that area.
  • Organizations with Data for Good initiatives can find one another and collaborate based on similarity of mission and activities.

Below you will find a very preliminary landscape map, along with a description of the different kinds of groups in the Data for Good ecosystem and why you might need to engage with them….(More)”.

Repository of Behavioral Interventions in Latin America and the Caribbean

Curated on Posted on by Stefaan Verhulst

Inter-American Development Bank (IDB): “How do you keep people from gathering with friends and family during a pandemic? How do you improve school attendance among preschoolers? How do you make sure taxpayers pay their fair share? These are some of the questions researchers seek to solve so countries can continue to grow and prosper. Many issues come down to human behavior and how the right policy tools can nudge people into doing things that will benefit themselves and society. A new repository collects these tools and the lessons learned from behavioral interventions in Latin America and the Caribbean, making them available for policymakers across the region and beyond.

For nearly a decade, the Inter-American Development Bank (IDB) has been working with local and national governments in the region to advance knowledge and expertise on individual and collective decision-making. The goal is to address biases that guide people’s behavior in detrimental ways. By designing strategies to correct them, we can help people make wiser choices in areas that range from education and savings to health, tax compliance, and labor markets….

To collect our findings and make the lessons we learned over the years available to policymakers and researchers, we recently created the largest online repository of quantitative behavioral economics field experiments conducted in Latin America and the Caribbean. The repository is aimed specifically at policymakers and is available in Spanish and English….(More)”.

Could Trade Agreements Help Address the Wicked Problem of Cross-Border Disinformation?

Curated on Posted on by Stefaan Verhulst

Essay by Susan Ariel Aaronson: “Whether produced domestically or internationally, disinformation is a “wicked” problem that has global impacts. Although trade agreements contain measures that address cross-border disinformation, domestically created disinformation remains out of their reach. This paper looks at how policy makers can use trade agreements to mitigate disinformation and spam while implementing financial and trade sanctions against entities and countries that engage in disseminating cross-border disinformation. Developed and developing countries will need to work together to solve this global problem….(More)”.

A New Tool Shows How Google Results Vary Around the World

Curated on Posted on by Stefaan Verhulst

Article by Tom Simonite: “Google’s claim to “organize the world’s information and make it universally accessible and useful” has earned it an aura of objectivity. Its dominance in search, and the disappearance of most competitors, make its lists of links appear still more canonical. An experimental new interface for  Google Search aims to remove that mantle of neutrality.

Search Atlas makes it easy to see how Google offers different responses to the same query on versions of its search engine offered in different parts of the world. The research project reveals how Google’s service can reflect or amplify cultural differences or government preferences—such as whether Beijing’s Tiananmen Square should be seen first as a sunny tourist attraction or the site of a lethal military crackdown on protesters.

Divergent results like that show how the idea of search engines as neutral is a myth, says Rodrigo Ochigame, a PhD student in science, technology, and society at MIT and cocreator of Search Atlas. “Any attempt to quantify relevance necessarily encodes moral and political priorities,” Ochigame says.

Ochigame built Search Atlas with Katherine Ye, a computer science PhD student at Carnegie Mellon University and a research fellow at the nonprofit Center for Arts, Design, and Social Research.

Just like Google’s homepage, the main feature of Search Atlas is a blank box. But instead of returning a single column of results, the site displays three lists of links, from different geographic versions of Google Search selected from the more than 100 the company offers. Search Atlas automatically translates a query to the default languages of each localized edition using Google Translate.

Ochigame and Ye say the design reveals “information borders” created by the way Google’s search technology ranks web pages, presenting different slices of reality to people in different locations or using different languages.

When they used their tool to do an image search on “Tiananmen Square,” the UK and Singaporean versions of Google returned images of tanks and soldiers quashing the 1989 student protests. When the same query was sent to a version of Google tuned for searches from China, which can be accessed by circumventing the country’s Great Firewall, the results showed recent, sunny images of the square, smattered with tourists.

Google’s search engine has been blocked in China since 2010, when the company said it would stop censoring topics the government deemed sensitive, such as the Tiananmen massacre. Search Atlas suggests that the China edition of the company’s search engine can reflect the Chinese government’s preferences all the same. That pattern could result in part from how the corpus of web pages from any language or region would reflect cultural priorities and pressures….(More)”

Search Atlas graph showing different search results
An experimental interface for Google Search found that it offered very different views of Beijing’s Tiananmen Square to searchers from the UK (left), Singapore (center), and China. COURTESY OF SEARCH ATLAS

Policy Impacts

Curated on Posted on by Stefaan Verhulst

About: “Over the past 50 years, researchers have made great strides in analyzing public policy. With better data and improved research methods, we know more than ever about the impacts of government spending.

But despite these advances, it remains surprisingly challenging to answer basic questions about which policies have been most effective.

The difficulty arises because methods for evaluating policy effectiveness are not standardized. This makes it challenging, if not impossible, to compare and contrast across different policies.

Policy Impacts seeks to promote a unified approach for policy evaluation. We seek to promote the Marginal Value of Public Funds, a standardized metric for policy evaluation. We have created the Policy Impacts library, a collaborative effort to track the returns to a wide range of government policies…(More).

Guide on Geospatial Data Integration in Official Statistics

Curated on Posted on by Stefaan Verhulst

Report by PARIS21: “National geospatial integration agencies can provide detailed, timely and relevant data about people, businesses, buildings, infrastructures, agriculture, natural resources and anthropogenic impacts on the biosphere. There is a clear benefit to integrating geospatial data into traditional national statistical systems. Together they provide a very clear picture of the social, economic and environmental issues that underpin sustainable development and allow for more informed policy making. But the question is where to start?

geospatial data integration

This new PARIS21 publication provides a practical guide, based on five principles for national statistics offices to form stronger partnerships with national geospatial integration agencies….(More)”.

Why don’t they ask us? The role of communities in levelling up

Curated on Posted on by Stefaan Verhulst

Report by the Institute of Community Studies: “We are delighted to unveil a landmark research report, Why don’t they ask us? The role of communities in levelling up. The new report reveals that current approaches to regeneration and economic transformation are not working for the majority of local communities and their economies.

Its key findings are that:

  • Interventions have consistently failed to address the most deprived communities, contributing to a 0% average change in the relative spatial deprivation of the most deprived local authorities areas;
  • The majority of ‘macro funds’ and economic interventions over the last two decades have not involved communities in a meaningful nor sustainable way;
  • The focus of interventions to build local economic resilience typically concentrate on a relatively small number of approaches, which risks missing crucial dimensions of local need, opportunity and agency, and reinforcing gaps between the national and the hyper-local;
  • Interventions have tended to concentrate on ‘between-place’ spatial disparities in economic growth at the expense of ‘within-place’ inequalities that exist inside local authority boundaries, which is where the economic strength or weakness of a place is most keenly felt by communities.
  • Where funds and interventions have had higher levels of community involvement, these have typically been disconnected from the structures where decisions are taken, undermining their aim of building community power into local economic solutions…(More)”.