FinTech, Volume 4, Issue 2 (June 2025) – 6 articles

This paper explores the current use of crypto-assets for payments, focusing mostly on unbacked crypto-assets, while selectively referring to stablecoins. Although some specific characteristics of crypto-assets, such as their price volatility and unclear legal settlement, render them unsuitable for payments, the rapid technological and regulatory developments in the area of crypto-assets-based payments justify monitoring developments in this area. We therefore try to answer the research questions of which/why/how/where/by whom crypto-assets are used for (retail) payments. We analyse and describe a variety of ways in which crypto-assets are used for making payments, focusing on the period from 2019 to 2023 in Europe and worldwide, based on the publicly available statistical data and literature. We identify and exemplify the main use cases, payment methods, DeFi protocols, and payment gateways, and analyse payments with crypto-assets based on location and market participants. In addition, we describe and analyse the integration of crypto-assets into existing commercial payment services. Our work contributes to understanding the shifting domain of crypto-assets-based payments and provides insights into the monitoring of relevant developments via various dimensions that need to keep being explored, with the objective of contributing to the maintenance of the integrity and stability of the financial ecosystem. Full article

Initially designed as an automated ledger tool, Excel swiftly evolved into a data analytics platform for financial analysts to execute intricate financial analyses. Excel is so commonplace in the financial industry that many do not even consider it a fintech tool. The transformation of Excel from a simple ledger tool to a low-code machine learning (mL) platform is not a traditional focus for fintech. The transformation of Excel into an mL platform will let financial analysts and quantitative analyses quickly evolve financial models in Excel to use advanced mL techniques. The low-code interface lets analysts quickly build predictive models. This paper explores how Excel has evolved into a low-code machine platform for financial applications along with the risks associated with Excel’s new functionality. Full article

In the context of rapid advancements in financial technologies and the evolving demand of the digital economy, this study explores the transformative impact of FinTech and artificial intelligence (AI) on the banking sector, with a particular focus on payment systems. By examining innovative financial instruments and AI-driven solutions, this research investigates how these technologies enhance efficiency, security, and customer experience in banking operations. This study evaluates the integration of AI in payment systems, including its role in predictive analytics, fraud detection, and personalization, while aligning with global trends in digital transformation and sustainability. Adopting an interdisciplinary approach, this analysis highlights scalable and resilient strategies that address emerging challenges in the financial ecosystem. The findings provide a comprehensive framework for leveraging AI and FinTech to drive the evolution of banking services, supporting the transition toward a more innovative, digitalized, and sustainable financial future. Full article

This study examines the effect of FinTech on entrepreneurial performance and the essentiality of tax compliance and entrepreneurial orientation. Drawing on information from small and medium enterprises (SMEs) in Greece and utilizing Structural Equation Modeling techniques, our study shows that FinTech plays a key role in improving tax adherence and entrepreneurial mindsets, which subsequently enhances entrepreneurial success. FinTech promotes greater transparency, easier reporting, and less compliance burdens. Companies that make use of FinTech tools see enhancements in meeting tax regulation requirements efficiently and effectively without being weighed down by compliance issues that take up resources meant for innovation and strategic development instead. Moreover, this research highlights the impact of incorporating financial technology solutions for improved management and cultivating an innovative and forward-thinking environment. It highlights the importance of implementing strategies to boost FinTech adoption and foster entrepreneurial achievements, effectively sliding tax compliance into focus. Our research identifies the revolutionary impact of FinTech tools and sheds light on how technological progress can fuel entrepreneurship and improve business outcomes overall. Full article

The Markets in Crypto-Assets Regulation (MiCA) is a comprehensive European Union regulatory framework aimed at harmonizing the crypto-asset market. The existing literature has mainly examined MiCA from a legal perspective, while empirical assessments of industry perspectives remain scarce. In this study, we examine MiCA’s impact on the crypto market and its implications for both theory and practice by analyzing and integrating insights from 12 expert interviews. The findings reveal perceived benefits arising from the unified market, enhanced investor protection, and compliance clarity, alongside challenges related to the high regulatory burden, legal ambiguities, and limited innovation support. On this basis, we provide recommendations for improving the regulatory framework and its implementation. Furthermore, we integrate our findings within the technology–organization–environment (TOE) framework to provide a theory-based starting point for rigorous academic research. These findings contribute to regulatory discourse and offer practical guidance for the relevant stakeholders, including businesses, regulators, policymakers, and academics. Full article

The need for a sustainable economy has grown as technological advancements increasingly influence economic and social structures. This study investigates the role of FinTech and artificial intelligence (AI) in fostering sustainable development by facilitating green initiatives and promoting social responsibility. The research hypothesis posits that FinTech enables better access to financing for economic and social development projects, while AI enhances decision-making processes critical to the implementation of these initiatives. Through a qualitative approach, this study analyzes the interactions between FinTech, AI, and the Sustainable Development Goals (SDGs), exploring whether their relationship is bilateral or unidirectional. Using a quantitative approach, this study employs Principal Component Analysis (PCA) and Analysis of Variance (ANOVA) to examine the key factors influencing bank account ownership across different demographic groups and time periods. PCA is utilized to reduce data dimensionality while preserving the most significant variance, enabling the identification of underlying patterns in financial inclusion determinants. Meanwhile, ANOVA is applied to assess statistical differences in bank account ownership across demographic categories and the pre-pandemic, during-pandemic, and post-pandemic periods, highlighting the impact of digital financial services on financial inclusion trends in Europe. The findings suggest that both technologies play a significant role in supporting sustainability, with FinTech providing the necessary financial tools and AI optimizing decision-making. Furthermore, this study identifies barriers, such as regulatory challenges and technological gaps, that hinder the full integration of these technologies into sustainable development practices. It also highlights facilitators, such as policy support and technological innovation, that accelerate their adoption. The conclusions emphasize the transformative potential of FinTech and AI in achieving robust economic growth, reducing inequalities, and fostering a new cultural approach to resource management and societal responsibility. Full article