Digitale Identitätssysteme bilden eine zentrale Grundlage moderner Verwaltungs- und E-Government-Prozesse. Sie ermöglichen die sichere Interaktion zwischen Bürger:innen, staatlichen Stellen und privaten Diensten. Ein besonders kritischer Schritt ist dabei die Identitätsprüfung im Rahmen des Onboardings, da hier die Verbindung zwischen einer realen Person und einer digitalen Identität hergestellt wird. Bestehende Onboarding-Verfahren, etwa persönliche Identifikation, VideoIdent, biometrische Verfahren oder dokumentenbasierte Prüfungen, stellen dafür etablierte Mechanismen bereit, erfordern jedoch häufig die Verarbeitung sensibler personenbezogener Daten und stützen sich stark auf organisatorische Vertrauensstrukturen.Die vorliegende Arbeit untersucht, ob ein deterministischer, registerbasierter und kryptographisch unterstützter Matching-Ansatz auf den Onboarding-Prozess von ID Austria angewendet werden kann. Der Fokus liegt dabei nicht auf der Entwicklung eines neuen kryptographischen Bausteins oder eines vollständig neuen Identitätssystems, sondern auf der konzeptionellen Anwendung und prototypischen Umsetzung von Deterministic Privacy-Preserving Identity Matching als Onboarding-Modell. Dieser Ansatz wird im Rahmen der Arbeit als DPPIM-OM bezeichnet.Die Arbeit folgt einem konstruktiv-analytischen Vorgehen. Zunächst werden die technischen und konzeptionellen Grundlagen digitaler Identität, Identitätsprüfung, privacy-preserving Matching, OPRF/VOPRF-Mechanismen und Zero-Knowledge-Nachweisen analysiert. Darauf aufbauend wird ein Onboarding-Modell beschrieben, das deterministischen Full-Match, kanonisierte Attributrepräsentation, servergebundene kryptographische Auswertung, registerbasierten Vergleich und registergebundene Nachweisführung kombiniert. Anschließend wird ein Prototyp umgesetzt, um die technische Realisierbarkeit des Ansatzes unter kontrollierten Bedingungen zu demonstrieren.Das vorgeschlagene Onboarding-Modell wird dem aktuellen ID-Austria-Onboarding sowie VideoIdent-, biometrischen und dokumentenbasierten Verfahren gegenübergestellt. Die Evaluierung erfolgt entlang zentraler Dimensionen wie Datenexposition, Informationsleckage, Sicherheit, Missbrauchsresistenz, Vertrauensmodell, Verifizierbarkeit, Determinismus, Fehleranfälligkeit, Anforderungen an Datenqualität, Prozesskomplexität, Performance sowie Kompatibilität mit dem europäischen regulatorischen Rahmen.Die Ergebnisse zeigen, dass DPPIM-OM insbesondere in den Bereichen Datenminimierung, Informationskontrolle und Verifizierbarkeit deutliche strukturelle Vorteile aufweist. Gleichzeitig bringt der Ansatz spezifische Anforderungen und Einschränkungen mit sich, insbesondere hinsichtlich Datenkonsistenz, technischer Umsetzungskomplexität und fehlender direkter Personenbindung. Die Arbeit kommt zu dem Ergebnis, dass der Ansatz eine vielversprechende Möglichkeit zur Weiterentwicklung digitaler Onboarding-Prozesse darstellt, insbesondere in hybriden Modellen, die klassische Mechanismen zur Personenbindung mit einem deterministischen und kryptographisch überprüfbaren Attributabgleich kombinieren.
Amar Razaq, Muhammad Asad ur Rehman Naseer, Muhammad Naseer, Saher Jabeen
Decentralization has become one of the main governance reforms through which developing economies try to make food security policy more responsive to local conditions. The reform promise is straightforward: subnational governments and community institutions may know local agroecological conditions, household vulnerability, market constraints, and social exclusion better than central ministries. Yet decentralization can also reproduce weak service delivery when authority is transferred without finance, staff, data systems, accountability, or coordination. This chapter argues that local food governance should be assessed as a design problem rather than as a general reform ideal. Effective devolution links clear functional assignments, predictable finance, capable local administration, public participation, and national standards. The chapter develops a multilevel framework for food governance, compares fiscal and institutional patterns in selected developing economies, and uses case boxes from Pakistan, India, Brazil, Kenya, Indonesia, and Ethiopia. It concludes that decentralized governance can strengthen inclusion and responsiveness, but only when local discretion is embedded in transparent institutions and coherent intergovernmental systems.
C J Noorjahan, Ms. Saranya Durga K, Mrs. Ruth Rebecca R
This paper discusses the Union-to-State tax devolution in India during the years 2015 to 2024, which is constructed based on the proposals of the 14th Finance Commission and the 15th Finance Commission. It provides the vertical fiscal imbalance that persists in India, with the Union dominating the significant sources of revenue and the horizontal imbalance between the States with varying capabilities and needs. Based on secondary data in budget documents, Finance Commission reports, and Reserve Bank publications, the study runs both descriptive analysis and chi-square tests in determining the stability and equity of tax transfers. The research results indicate that tax devolution has been inequitable and fluctuating. Big States like Uttar Pradesh, Bihar and Madhya Pradesh got the maximum shares, with little going to the smaller States like Goa, Sikkim, and Mizoram. Arunachal Pradesh was a small state because of its strategic and geographical location. This was proven right by statistical tests, which means that State size had a significant effect on levels of allocation. The general trend also showed instability, whereby devolution reached its highest point in 2015-16 and was very low in other years, and this makes it hard for the States to plan their finances. Though the share of taxes to the States was raised by the 14th Finance Commission, subsequent changes in the 15th Finance Commission led to average transfers to many States, strengthening inequalities. The research concludes that the existing devolution system still favours the bigger States and proposes a more transparent, equitable and need-based system to reinforce fiscal decentralisation and create a balanced regional development.
José Antonio Siqueira Pontes, Clara Coelho Mangolin
Abstract: Access to financial resources by individuals, corporations, and governments must undergo impact assessments concerning human rights. Public and private governance bodies exert influence over the global financial landscape, ensuring compliance with frameworks such as the UN’s 2030 SDGs through the "Equator Principles" and the "Principles for Responsible Investment." The article aims to analyze the effects of digital tools on responsible financing, such as through the decentralization of financial systems for credit access. It explores the use of artificial intelligence (AI) integrated into "smart contracts," the consumer credit market, especially on peer-to-peer lending platforms, and other fintech solutions for achieving ESG goals like poverty reduction. However, the use of AI and "smart contracts" may also pose risks to human rights. The primary approach involves reviewing international literature to identify emerging risks. The expected outcome is a comprehensive analysis of recent trends and challenges related to corporate social responsibility in the financial sector, particularly regarding human rights in the digital era.
Open access
FinTech, Crowdfunding, Digital Finance
Legal, Health, Environmental and COVID-19 Challenges
Federated Learning enables collaborative model training across distributed clients without requiring direct access to their private data. However, effective deployment faces critical challenges, including heterogeneous data quality, unbalanced participation, and the lack of incentives. In this paper, we propose a federated learning network structured as a decentralized marketplace, where clients are financially rewarded based on the quality and utility of their contributions. Our framework enhances client selection through utility-driven mechanisms and offers strong incentives that promote sustained, high-quality participation. It also ensures security and transparency for the Task Owner while maintaining data privacy. The architecture can support a wide range of collaborative scenarios; spanning from healthcare and finance to consumer applications; where data privacy, fairness, and scalability are paramount. We demonstrate the practicality and effectiveness of our approach through experiments, showcasing improved global model accuracy, and equitable participation.
Smart contracts represent a specific synthesis of technology and law. They are agreements that are automatically executed and, owing to blockchain technology, relatively immutable. Due to their automation and immutability, smart contracts constitute a useful instrument of contemporary digital transactions. At the level of the European Union, smart contracts are comprehensively regulated by Regulation (EU) 2023/2854 on fair access to and use of data. In the first part of the paper, the author analyzes the concept of smart contracts, along with a brief explanation of blockchain technology as their underlying basis. In the second part, the author examines the legislation of the Member States of the European Union concerning smart contracts prior to the adoption of the aforementioned Regulation. The central part of the paper is devoted to an analysis of the provisions of Regulation (EU) 2023/2854 relating to smart contracts, with particular emphasis on the essential requirements for smart contracts used in the performance of data sharing agreements, as well as on the procedure for assessing the compliance of smart contracts with those essential requirements. In the conclusion, the author elaborates the thesis that the new European Union legislation, including that relating to smart contracts, represents a qualitative leap compared to previous solutions, as it provides a detailed regulation of some of the most significant issues concerning the functioning of smart contracts and offers appropriate legal and technical guarantees for their successful application.