522 is the number of public development banks identified to date (Xu et al, 2021) that make up the Finance in Common global coalition. Responsible for around 10% of the world’s annual investment, these institutions play an essential role in the international financial architecture. With a mandate and public responsibility, they provide financial support in sectors where social and/or environmental profitability is greater than private profitability, such as health, education and the fight against climate change. Thus, they are called to play a decisive role in achieving the 2030 Agenda.

Some public development banks (PDBs) analyse their alignment with the SDGs, but the use of disparate methods does not yield reliable and comparable results. At the same time, the majority of PDBs publish an annual activity and sustainable development report. These documents, available online, are a wealth of information today little exploited and on which we rely in our project.

Read also: FICS 2021: A new database of the world's Public Development Banks and financing institutions unveiled

This research project led by AFD aims to test the potential of artificial intelligence (AI) technologies for the benefit of sustainable development. It resulted in the creation of the SDG Prospector, a tool that offers a unified and relevant method to map the extra-financial commitments of public development banks. It quantifies the degree of importance given to each of the 17 Sustainable Development Goals in official PDBs documentation.

The analysis was conducted over a five-year period (2016-2020) for 237 institutions. Thus, it is possible to draw up an overview of the SDG alignment by bank, geographies, size of balance sheets, mandates, levels of development, etc.

Read also: Using Artificial Intelligence to assess progress towards the Sustainable Development Goals

In order to extract the information contained in the annual reports of public development banks, the SDG Prospector applies an artificial intelligence method specialized in language analysis (Natural Language Processing). This innovative technique is more accurate than a keyword analysis, as it allows the tool to recognize the context of sentences.

To do this, the SDG Prospector relies on a learning base, which allows it to identify when a text mentions the SDGs and to determine which SDG it is. The learning base consists of more than 8,500 texts related to the 2030 Agenda, mainly from United Nations documents, government reports and NGOs. Specializing in the recognition of SDGs, the Prospector divides each annual report into paragraphs of about ten lines and determines whether there is mention of one, several or no SDGs.

The results allow to draw an extensive mapping of PDBs’ positioning towards the 2030 Agenda: 

• PDBs strategic and operational narrative is mainly structured around the SDGs, such as SDG 8 “Decent Work and Economic Growth” and SDG 9 “Innovation and Infrastructure”;
• SDG 13 “Climate Action” is increasingly taken into account by the entire sample, and we note a positive correlation between the size of PDBs’ balance sheet and their consideration for SDGs that are associated with environmental protection;
• Biodiversity constitutes a negligible part of PDBs’ narrative;
• Social SDGs account for 21% of PDBs’ annual reports. However, cross-cutting SDGs such as gender equality, reduced inequalities and the eradication of poverty represent a minor share of PDBs’ narrative;
• PDBs that have similar characteristics in terms of size, mandate and geography tend to share the same SDG narrative.

Analyze your document with the SDG Prospector: sdgprospector.org

The artificial intelligence techniques used allow new data to emerge, both for research and for the operational implementation of the SDGs. Other innovative projects followed by AFD contribute to this dynamic, in line with the IA-Biodiv Challenge.

Read our Research Paper: "The Proof is in the Pudding: Revealing the SDGs with Artificial Intelligence"

• Régis Marodon, Special Advisor on sustainable finance at AFD
• Jean-Baptiste Jacouton, Research Officer at AFD

In Argentina, the participation to the platform economy is a recent but rapidly expanding phenomenon. The severe recent economic crisis and its reinforcement with the Covid-19 crisis have been destabilizing to standard work relations, in an environment where informality is widespread and where gender inequalities are experienced across occupations. The high rate of internet connectivity (with coverage among the highest in Latin America) as well as the hardship of the economic conditions experienced in the labour market provide a particularly favorable environment for the expansion of the platform modality.

The research partnership between AFD and the Economics Department at the Instituto de Ciencias of the Universidad Nacional de General Sarmiento (UNGS) seeks to create some primary qualitative and quantitative data on platforms in Buenos Aires Metropolitan Area.

It explores app-based platforms for the personal service sector, such as the ones for domestic work, office repair services, food delivery and ride-hailing services. The project develops articles inspecting various aspects of the platform economy, characterizing the workers that engage in it, their labour conditions, as well as their perceptions about this type of insertion. It enquires about the levels of flexibility and/or control posed by platforms on the work process, inspecting the relationship with existing labour regulations and its implications for workers’ labour conditions. Moreover, the research identifies the opportunities/obstacles for entry and permanence in the analyzed occupations and the way in which gender restrictions operate.

The project is based on a mixed methods’ approach, developing its primary qualitative and quantitative data.

In the first phase of the project, a series of in-depth interviews and focus groups is conducted with workers of each occupational group in order to delve deeper into the different dimensions of platform work. 

In the second phase of the project, building on the information from the qualitative data collection, an ad-hoc quantitative survey is designed to collect data about workers on the platform to strengthen knowledge on their experience. The survey is based on a non-probabilistic sample with gender quotas per platform, seeking to ensure comparability among occupations and demographic groups. Moreover, thanks to a collaboration with the ILO Country Office for Argentina, the data is inspected jointly with an existing dataset produced by ILO. 

Several articles and presentations stem from this fruitful collaboration, with five initial research papers available for download in the AFD repository.

• The first article investigates whether working through a digital platform increases labour registration in high-informality occupations. It analyses how labour entry occurs in three selected platform-based occupations in Argentina. Considering the peculiarities of each occupation, it identifies which elements may contribute to a “formalization effect” and how this is experienced by workers. The main results of this working paper show that “formalization” is dependent on several factors: a platform’s business model, or the company’s interest and need to promote or encourage such process; the pre-existing occupational dynamics in terms of formalization; and general labour market conditions. In the context of an Argentine labour market harmed by a prolongued recession, most transitions to formality via the platform occur to previously unemployed workers who join them. However, given that in many cases unemployment is preceded by stable waged jobs, formalisation promoted by platforms (usually through the figure of the registered independent workers) is often perceived as a setback.
• The second article explores the challenges posed by regulation of platform labour, based on the case of Argentinean riders. The article analyses the treatment of three dimensions that tend to be at the centre of riders’ own concerns when it comes to the regulation of their occupation. First, the preservation of flexible schedules is found as a strong driver for riders participation into the platform. Second, the continuity of income self-regulation is a very relevant aspect for workers, even though this often implies overworking. Third aspect is an effective access to social protection, found as a major threat for riders’ job safety and well-being, and the absence of an occupational hazards insurance for riders stands out as a real barrier for workers.
• The third article explores how the digitalization of the work relation affects domestic workers in Argentina at the onset of the Covid-19 crisis. It analyses the use workers do of Zolvers, the only digital platform for domestic service in the country, and it compares what are the differences between jobs that have been taken on the platform and those outside. The working paper argues that the association between domestic service and the platform economy should be analysed in context: the uberisation of the activity is not a linear and uniform trend, but rather a contextual one. Compared to off-platform jobs in the sector, the article finds significantly higher levels of registration among Zolvers workers. This is particularly relevant since Zolvers’ jobs are characterized by few weekly hours, a kind of insertion that has proved most resistant to formalisation policies in the sector. The article delves into the reasons behind these phenomenon, which are tightly related to the platform business model. However, in the context of the Covid-19 crisis, the working paper also shows that registration, although having a protective effect, does not counteract the vulnerability implied by short-hours job positions, whose termination is substantially cheaper than full-time work.
• The fourth article investigates gender inequalities among platform riders and drivers. It identifies whether there exist gender gaps in terms of hours and income and what is their magnitude. Moreover, it analyses some possible determinants, including features specific to these occupations. The working paper finds that platforms are facilitating an increase in female participation due to three main factors: the impossibility of finding another job, the impersonal recruiting mechanisms and time flexibility offered by platforms. This trend still implies significant gender gaps. The analysis suggests that the differentiated economic performance of male and female riders and drivers is mainly associated to pre-existing gender inequalities that are reinforced by algorithmic bias in the platform. In particular, the scoring system of platforms tends to reward intensive workloads and participation in the more profitable shifts, such as nights and weekends. This implies important obstacles for women in terms of both their care responsibilities and their need to prevent street insecurity events.
• The last article delves deeper into female platform drivers’ labour market trajectories.  It inspects the profile of female drivers joining the platform in exploring which previous job experiences may have helped them to dare into a male-dominated occupation. Additionally, it reviews how, once in the platform, female drivers juggle between this activity and their socially assigned care responsibilities. The working paper shows that female drivers participation defies the idea that occupations involving driving or circulating in public spaces are inappropriate for women. However, this conquest has strong limits. The working paper finds that the daily efforts to reconcile paid work together with domestic care activities imply negative impacts in terms of earnings levels and health. The situation exposes an omnipresent unequal gender order, which still needs to be systematically questioned and confronted.

The Research Conversation webinar "Digital labour platforms: what challenges and opportunities for Argentina?" has been organized to discuss the results of the research project.

Contacts: 

• Dr Francisca Pereyra, Adjunct Professor, Economics Department, Instituto de Ciencias, Universidad Nacional de General Sarmiento (UNGS)
• Dr Cecilia Poggi, AFD Research Officer