Digital Cross-Border Payment Technologies in Fragile, Conflict, and Vulnerable Settings
Notice bibliographique
Résumé
Abstract Financial sector de-risking is a growing problem leading to the financial exclusion of a growing number of countries around the world, especially in fragile, conflict and vulnerable (FCV) contexts deemed to be of high risk from a regulatory compliance perspective. De-risking is marked by the withdrawal of banks and other financial institutions from high-risk jurisdictions and has been termed a “global crisis” by the United Nations (UN) and other international organizations (IOs). Mounting complexity of the global compliance landscape—including the risk of sizeable fines and penalties linked to multilateral and autonomous sanctions, as well as other related regulations—alongside cost and reputational considerations, have led to a rapid decline in global correspondent banking relationships (CBRs) over the past decade (Moret, More civilian pain than political gain (Again?): The demise of targeted sanctions and associated humanitarian impacts. In A. Charron and C. Portela (Eds) Multilateral sanctions revisited: Lessons learned from Margaret Doxey. McGill Queen’s University Press, 2022). A growing number of countries are becoming partially or fully “unbanked”, as a consequence. Ramifications of de-risking include constraints in humanitarian and development assistance; hindered civil society activities; barriers to flows of household remittances; bottlenecks in legitimate trade, investment and wider financial services. Ultimately, these trends diminish resilience and prospects for sustainable peace and tend to hit the underprivileged the hardest—including women, children (Pelter, Teixeira, & Moret, Sanctions and their impact on children. UNICEF, February, 2022), the elderly, those with chronic health conditions and refugees. This chapter provides an overview of the opportunities and challenges associated with digital humanitarian fund transfer technologies and explores whether innovative payment platforms could help stem and mitigate some of the principal constraints associated with the mounting global challenge of financial sector de-risking. It concludes that technology-based solutions for cross-border payments relating to basic human needs are still in their infancy, also representing a major gap in the academic and policy literature. It draws on literature covering several use cases to suggest that payment innovations have potential to play a vital role, particularly in contexts where local entities are able to facilitate liquidity access or establish digital ecosystems for local payments. These innovations can also bring about advantages that include speed, cost-effectiveness, transparency, accountability, choice and heightened compliance, with the right guardrails. It highlights the importance of Human Centred Design (HCD) and finds that, although some IOs and non-governmental organisations (NGOs) have begun adopting innovative payment technologies in certain contexts, widespread adoption remains limited, particularly for cross-border payments. Furthermore, the pace of technological advances is often far ahead of regulatory frameworks, posing potential legal risks to users and hindering effectiveness. It concludes that addressing humanitarian fund transfer challenges associated with de-risking necessitates greater research, use cases and dialogue across stakeholder groups to foster a better understanding the role these technologies could play, alongside capacity building and awareness-raising initiatives, to enable users to take informed choices and contribute to the development of appropriate safety measures, policies and regulations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,007 | 0,012 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,021 | 0,005 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».