Journal Description
FinTech
FinTech
is an international, peer-reviewed, open access journal on a variety of themes connected with financial technology, such as cryptocurrencies, risk management, robo-advising, crowdfunding, blockchain, new payment solutions, machine learning and AI for financial services, digital currencies, etc., published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, RePEc, and other databases.
- Journal Rank: CiteScore - Q1 (Economics, Econometrics and Finance (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.4 days after submission; acceptance to publication is undertaken in 3.7 days (median values for papers published in this journal in the second half of 2024).
- Recognition of Reviewers: APC discount vouchers, optional signed peer review, and reviewer names published annually in the journal.
Latest Articles
Do Fintech Lenders Align Pricing with Risk? Evidence from a Model-Based Assessment of Conforming Mortgages
FinTech 2025, 4(2), 23; https://doi.org/10.3390/fintech4020023 - 9 Jun 2025
Abstract
This paper assesses whether fintech mortgage lenders align pricing with borrower risk using conforming 30-year mortgages (2012–2020). We estimate default probabilities using machine learning (logit, random forest, gradient boosting, LightGBM, XGBoost), finding that non-fintech lenders achieve the highest predictive accuracy (AUC = 0.860),
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This paper assesses whether fintech mortgage lenders align pricing with borrower risk using conforming 30-year mortgages (2012–2020). We estimate default probabilities using machine learning (logit, random forest, gradient boosting, LightGBM, XGBoost), finding that non-fintech lenders achieve the highest predictive accuracy (AUC = 0.860), followed closely by banks (0.857), with fintech lenders trailing (0.852). In pricing analysis, banks adjust the origination rates most sharply with borrower risk (7.20 basis points per percentage-point increase in default probability) compared to fintech (4.18 bp) and non-fintech lenders (5.43 bp). Fintechs underprice 32% of high-risk loans, highlighting limited incentive alignment under GSE securitization structures. Expanding the allowable alternative data and modest risk-retention policies could enhance fintechs’ analytical effectiveness in mortgage markets.
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(This article belongs to the Special Issue Trends and New Developments in FinTech)
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Hybrid GARCH-LSTM Forecasting for Foreign Exchange Risk
by
Elysee Nsengiyumva, Joseph K. Mung’atu and Charles Ruranga
FinTech 2025, 4(2), 22; https://doi.org/10.3390/fintech4020022 - 3 Jun 2025
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This study proposes a hybrid forecasting model that integrates the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a Long Short-Term Memory (LSTM) neural network to estimate Value at Risk (VaR) in the Rwandan foreign exchange market. The model is designed to capture both
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This study proposes a hybrid forecasting model that integrates the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a Long Short-Term Memory (LSTM) neural network to estimate Value at Risk (VaR) in the Rwandan foreign exchange market. The model is designed to capture both volatility clustering and temporal dependencies in daily exchange rate returns. Using daily data on USD, EUR, and GBP from 2012 to 2024, we evaluate the model’s performance relative to standalone GARCH(1,1) and LSTM models. Empirical results show that the hybrid model improves VaR estimation accuracy by up to 10%, especially during periods of elevated market volatility. These improvements are validated through MSE, MAE, and backtesting statistics. The enhanced accuracy is particularly relevant in emerging markets, where exchange rate dynamics are highly nonlinear and sensitive to external shocks. The proposed approach offers practical insights for financial institutions and regulators seeking to improve market risk assessment in emerging economies.
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Open AccessArticle
Machine Learning for Predicting Bank Stability: The Role of Income Diversification in European Banking
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Karim Farag, Loubna Ali, Noah Cheruiyot Mutai, Rabia Luqman, Ahmed Mahmoud and Nol Krasniqi
FinTech 2025, 4(2), 21; https://doi.org/10.3390/fintech4020021 - 31 May 2025
Abstract
There is an ongoing debate about the role of income diversification in enhancing bank stability within the financial services industry in Europe. Some advocate for diversification, while others argue that its importance should not be overstated. Some financial institutions are encouraged to focus
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There is an ongoing debate about the role of income diversification in enhancing bank stability within the financial services industry in Europe. Some advocate for diversification, while others argue that its importance should not be overstated. Some financial institutions are encouraged to focus on their traditional investments instead of income diversification, while others suggest that income diversification can stabilize or destabilize, depending on the regulatory environment. These conflicting results indicate a lack of clear evidence regarding the effectiveness of income diversification. Therefore, this paper aims to study the impact of income diversification on bank stability and enhance the predictive performance of bank stability by analyzing the period from 2000 to 2021 using a sample from 26 European countries, based on aggregate bank data. It employs a hybrid method that combines econometric techniques, specifically the generalized method of moments and a fixed-effects model, with machine-learning algorithms such as Random Forest and Support Vector Machine. These methods are applied to enhance the reliability and predictive power of the analysis by addressing the problem of endogeneity (via generalized method of moments) and capturing non-linearities, interactions, and high-dimensional patterns (via machine learning). The econometric findings reveal that income diversification can reduce non-performing loans, improve bank solvency, and enhance the Z-score, indicating the significant role of income diversification in improving bank stability. Conversely, the results also show that the machine-learning algorithms used play a crucial role in enhancing the predictive performance of bank stability.
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(This article belongs to the Special Issue Financial Technology and Strategic AI Integration in FinTech: Transforming Banking, Payments, and Building a Sustainable Economy—Challenges and Opportunities)
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The Investment Styles and Performance of AI-Related ETFs: Analyzing the Impact of Active Management
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Nikoletta Poutachidou and Alexandros Koulis
FinTech 2025, 4(2), 20; https://doi.org/10.3390/fintech4020020 - 29 May 2025
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This paper studies the performance of ETFs that invest in companies involved in artificial intelligence (AI) technologies, such as firms focused on AI research, development, and applications. Using daily data from 15 American ETFs focused on AI-related companies over the period from 1
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This paper studies the performance of ETFs that invest in companies involved in artificial intelligence (AI) technologies, such as firms focused on AI research, development, and applications. Using daily data from 15 American ETFs focused on AI-related companies over the period from 1 February 2019 to 29 December 2023, this paper investigates their investment style characteristics through a returns-based style analysis (RBSA). This study offers detailed insights into the degree of active versus passive management and highlights strategic patterns that may guide investment decisions in AI-themed financial products. We highlight that asset selection drives fund performances more than active management strategies, offering practical insights for investors and policymakers.
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(This article belongs to the Special Issue Fintech Innovations: Transforming the Financial Landscape)
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An Assessment of Lithuania’s Financial Technology Development
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Laima Okunevičiūtė Neverauskienė, Irena Danilevičienė and Gileta Labašauskienė
FinTech 2025, 4(2), 19; https://doi.org/10.3390/fintech4020019 - 7 May 2025
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The Lithuanian financial technology (referred to as FinTech) sector is one of the fastest-growing financial technology centers in Europe; however, this sector faces economic, regulatory, and technological challenges that hinder its development. This article aims to assess the state of development of Lithuania’s
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The Lithuanian financial technology (referred to as FinTech) sector is one of the fastest-growing financial technology centers in Europe; however, this sector faces economic, regulatory, and technological challenges that hinder its development. This article aims to assess the state of development of Lithuania’s FinTech sector, identify the main challenges, and provide recommendations to promote the development of the sector. This study uses quantitative indicators, inter-criteria correlation, multi-criteria evaluation methods, and SWOT analysis. This article’s results will help identify the key factors that influence the growth of the FinTech sector in Lithuania and will be useful in shaping the sector’s further development strategy. The results of this study revealed that factors such as favorable regulation influence the FinTech sector in Lithuania the most, strengthening the innovation ecosystem and attracting international investments. However, the sector still faces challenges such as a lack of skilled labor, ensuring cybersecurity, and constant regulatory adaptation to new technologies. Based on the results of this study, it is recommended to pay more attention to educational programs aimed at training technology specialists, to promote cooperation between the public and private sectors, and to further improve the regulatory environment to ensure the sustainable and safe development of FinTech.
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(This article belongs to the Special Issue Trends and New Developments in FinTech)
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Beyond Traditions: Swiss Banking’s Journey into Digital Assets and Blockchain
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Patrick Schueffel and Daniel Stuessi
FinTech 2025, 4(2), 18; https://doi.org/10.3390/fintech4020018 - 6 May 2025
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Swiss banks are at a pivotal moment as digital assets gain traction, presenting both challenges and opportunities. This study examines how Swiss banks can leverage their internal resources and capabilities to establish a competitive advantage in the digital asset ecosystem. Using the Resource-Based
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Swiss banks are at a pivotal moment as digital assets gain traction, presenting both challenges and opportunities. This study examines how Swiss banks can leverage their internal resources and capabilities to establish a competitive advantage in the digital asset ecosystem. Using the Resource-Based View and the VRIO (Value, Rarity, Imitability, and Organization) framework, this study investigates the strategic importance of key services such as custody, staking, and tokenization. Drawing on expert interviews with Swiss banking leaders, this research identifies these services as vital for maintaining Switzerland’s financial leadership. Findings suggest that Swiss banks’ established reputation for trust, combined with regulatory clarity under the Distributed Ledger Technology Act, creates a strong foundation for digital asset adoption. While digital asset custody services address the growing demand for security, tokenization presents significant growth potential, particularly in real-world asset markets. This study concludes that Swiss banks can sustain their competitive edge by investing in blockchain expertise, fostering fintech partnerships, and enhancing educational initiatives. By combining traditional banking strengths with innovative digital asset services, Swiss banks are well positioned to capitalize on this evolving financial landscape.
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Open AccessArticle
Key Factors Influencing Fintech Development in ASEAN-4 Countries: A Mediation Analysis
by
Ari Warokka, Aris Setiawan and Aina Zatil Aqmar
FinTech 2025, 4(2), 17; https://doi.org/10.3390/fintech4020017 - 25 Apr 2025
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Financial technology (FinTech) rapidly transforms financial landscapes across ASEAN-4 countries by enhancing financial inclusion and digital service accessibility. However, the key factors driving FinTech development in these economies remain ambiguous. While existing studies highlight the economic and technological aspects of FinTech adoption, limited
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Financial technology (FinTech) rapidly transforms financial landscapes across ASEAN-4 countries by enhancing financial inclusion and digital service accessibility. However, the key factors driving FinTech development in these economies remain ambiguous. While existing studies highlight the economic and technological aspects of FinTech adoption, limited research distinguishes the unique conditions shaping FinTech’s evolution in developing ASEAN markets. This study bridges this gap by identifying economic and non-economic determinants and exploring their mediating effects. This research aims to investigate the primary drivers of FinTech development in ASEAN-4, emphasizing the roles of financial access and technological readiness as mediators in fostering a sustainable FinTech ecosystem. Utilizing structural equation modeling (SEM) with SmartPLS3, this study analyzes secondary data from 2008 to 2018, evaluating macroeconomic indicators, banking conditions, internet penetration, innovation levels, population dynamics, and human development factors. General banking conditions, access to finance, and technological readiness significantly impact FinTech development. Additionally, financial accessibility and technological infrastructure mediate the influence of economic stability, innovation, and digital penetration on FinTech growth. This study underscores policymakers’ and stakeholders’ need to enhance digital infrastructure and financial accessibility to accelerate FinTech growth. Strengthening financial ecosystems will drive digital transformation and economic resilience in emerging ASEAN economies.
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FinTech, Fractional Trading, and Order Book Dynamics: A Study of US Equities Markets
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Janhavi Shankar Tripathi and Erick W. Rengifo
FinTech 2025, 4(2), 16; https://doi.org/10.3390/fintech4020016 - 25 Apr 2025
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This study investigates how the rise of commission-free FinTech platforms and the introduction of fractional trading (FT) have altered trading behavior and order book dynamics in the NASDAQ equity market. Leveraging high-frequency ITCH data from highly capitalized stocks—AAPL, AMZN, GOOG, and TSLA—we analyze
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This study investigates how the rise of commission-free FinTech platforms and the introduction of fractional trading (FT) have altered trading behavior and order book dynamics in the NASDAQ equity market. Leveraging high-frequency ITCH data from highly capitalized stocks—AAPL, AMZN, GOOG, and TSLA—we analyze market microstructure changes surrounding the implementation of FT. Our empirical findings show a statistically significant increase in price levels, average tick sizes, and price volatility in the post-FinTech-FT period, alongside elevated price impact factors (PIFs), indicating steeper and less liquid limit order books. These shifts reflect greater participation by non-professional investors with limited order placement precision, contributing to noisier price discovery and heightened intraday risk. The altered liquidity landscape and increased volatility raise important questions about the resilience and informational efficiency of modern equity markets under democratized access. Our findings contribute to the growing literature on retail trading and provide actionable insights for market regulators and exchanges evaluating the design and oversight of evolving trading mechanisms.
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Exploring the Use of Crypto-Assets for Payments
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Eleni Koutrouli and Polychronis Manousopoulos
FinTech 2025, 4(2), 15; https://doi.org/10.3390/fintech4020015 - 3 Apr 2025
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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
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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.
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(This article belongs to the Special Issue Trends and New Developments in FinTech)
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Automated Ledger or Fintech Analytics Platform?
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Andrew Kumiega
FinTech 2025, 4(2), 14; https://doi.org/10.3390/fintech4020014 - 2 Apr 2025
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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
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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.
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Banking Transformation Through FinTech and the Integration of Artificial Intelligence in Payments
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Otilia Manta, Valentina Vasile and Elena Rusu
FinTech 2025, 4(2), 13; https://doi.org/10.3390/fintech4020013 - 1 Apr 2025
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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
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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.
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(This article belongs to the Special Issue Fintech Innovations: Transforming the Financial Landscape)
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Unlocking Entrepreneurship in the FinTech Era: The Role of Tax Compliance in Business Performance
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Konstantinos S. Skandalis and Dimitra Skandali
FinTech 2025, 4(2), 12; https://doi.org/10.3390/fintech4020012 - 31 Mar 2025
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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
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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.
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Business Implications and Theoretical Integration of the Markets in Crypto-Assets (MiCA) Regulation
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Gayane Mkrtchyan and Horst Treiblmaier
FinTech 2025, 4(2), 11; https://doi.org/10.3390/fintech4020011 - 25 Mar 2025
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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
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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.
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Open AccessCommunication
FinTech and AI as Opportunities for a Sustainable Economy
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Valentina Vasile and Otilia Manta
FinTech 2025, 4(2), 10; https://doi.org/10.3390/fintech4020010 - 25 Mar 2025
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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
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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.
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(This article belongs to the Special Issue Financial Technology and Strategic AI Integration in FinTech: Transforming Banking, Payments, and Building a Sustainable Economy—Challenges and Opportunities)
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Open AccessArticle
Financial Overconfidence and High-Cost Borrowing: The Moderating Effect of Mobile Payments
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Isha Chawla and Manouchehr Mokhtari
FinTech 2025, 4(1), 9; https://doi.org/10.3390/fintech4010009 - 12 Feb 2025
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Inadequate financial literacy and overconfidence in financial knowledge, coupled with the use of mobile payments (MPs), may contribute to harmful financial behaviors. While the relationship between financial knowledge confidence and financial behaviors is well documented, there is limited understanding of how financial confidence
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Inadequate financial literacy and overconfidence in financial knowledge, coupled with the use of mobile payments (MPs), may contribute to harmful financial behaviors. While the relationship between financial knowledge confidence and financial behaviors is well documented, there is limited understanding of how financial confidence affects the use of alternative financial services (AFSs), such as payday loans, and how MPs moderate this relationship. This study examines the moderating effect of MPs on the association between financial knowledge confidence and the demand for AFS, utilizing data from U.S. adults surveyed in the 2018 National Financial Capability Study. The results show that individuals who use MPs are significantly more likely to engage with AFSs compared to non-users, with MPs increasing the likelihood of AFS usage by 92% (odds ratio: 1.92). Furthermore, overconfident individuals who use MPs are 94% more likely to rely on AFSs (odds ratio: 1.94). These findings highlight the need for targeted financial education and policymaking to mitigate the risks associated with financial overconfidence and MP usage.
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Open AccessArticle
Racial Disparities in Conforming Mortgage Lending: A Comparative Study of Fintech and Traditional Lenders Under Regulatory Oversight
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Zilong Liu and Hongyan Liang
FinTech 2025, 4(1), 8; https://doi.org/10.3390/fintech4010008 - 8 Feb 2025
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This study examines racial and ethnic disparities in mortgage-lending outcomes across different lender types—large banks, fintech lenders, non-bank lenders, small banks, and credit unions—using Home Mortgage Disclosure Act (HMDA) data from 2018 to 2023. By analyzing approval rates, rate spreads, and origination charges,
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This study examines racial and ethnic disparities in mortgage-lending outcomes across different lender types—large banks, fintech lenders, non-bank lenders, small banks, and credit unions—using Home Mortgage Disclosure Act (HMDA) data from 2018 to 2023. By analyzing approval rates, rate spreads, and origination charges, we evaluate how borrower outcomes vary by race and ethnicity, controlling for loan characteristics, borrower attributes, and regional factors. Our findings reveal that Black and Hispanic borrowers consistently face less favorable terms than White borrowers, with disparities differing by lender type. Large banks, operating under stringent regulatory oversight, demonstrate relatively equitable pricing but impose higher loan denial rates on minorities. Credit unions, despite offering the lowest rate spreads overall, penalize minority borrowers more severely in pricing than other lender types. Fintech lenders, while charging higher-rate spreads and fees, show smaller credit access disparities for minority borrowers. Non-bank and small banks display mixed results, with inconsistencies in their treatment of minorities across pricing and credit access. These results highlight that neither technological innovations nor alternative lending models alone suffice to eliminate systemic inequities. Achieving equitable mortgage lending requires enhanced regulatory oversight, greater transparency in algorithmic decision-making, and stricter enforcement of fair lending practices.
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(This article belongs to the Special Issue Trends and New Developments in FinTech)
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Blockchain for Quality: Advancing Security, Efficiency, and Transparency in Financial Systems
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Tomaž Kukman and Sergej Gričar
FinTech 2025, 4(1), 7; https://doi.org/10.3390/fintech4010007 - 5 Feb 2025
Cited by 1
Abstract
This article delves into the transformative impact of blockchain technology on enhancing transaction quality and efficiency. Since the emergence of blockchain alongside Bitcoin in 2008, its decentralised and transparent nature has significantly improved transaction speed, security, and cost efficiency. These advancements have solidified
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This article delves into the transformative impact of blockchain technology on enhancing transaction quality and efficiency. Since the emergence of blockchain alongside Bitcoin in 2008, its decentralised and transparent nature has significantly improved transaction speed, security, and cost efficiency. These advancements have solidified blockchain as a foundational innovation in financial services. The paper examines critical milestones in blockchain, including Bitcoin, Ethereum, and Binance Coin (BNB), and their role in reshaping global finance by automating processes and reducing reliance on intermediaries. Additionally, the study evaluates blockchain’s impact on quality management, particularly emphasising how its immutable ledger system enhances the reliability and transparency of financial transactions. Despite challenges such as scalability, energy consumption, and regulatory hurdles, the potential for blockchain to redefine transaction quality in financial services is evident. This research contributes to the growing body of literature by integrating blockchain technology and traditional quality management systems, providing a comprehensive perspective on how the two domains influence one another. The findings underscore blockchain’s ability to drive innovation in financial services while addressing security, efficiency, and operational quality concerns.
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(This article belongs to the Special Issue Financial Technology and Strategic AI Integration in FinTech: Transforming Banking, Payments, and Building a Sustainable Economy—Challenges and Opportunities)
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Crowdfunding and Energy Efficiency Contracting: Exploring New Pathways for Private Investment in Building Renovations
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Renan Magalhães, Federico Narracci and Jens Lowitzsch
FinTech 2025, 4(1), 6; https://doi.org/10.3390/fintech4010006 - 4 Feb 2025
Cited by 1
Abstract
Energy Efficiency Contracting (EEC) enables structural improvements in buildings by financing upgrades through the savings generated, eliminating the need for upfront investment by property owners. Although the model supports the energy transition and the reduction in GHG emissions, its adoption in the private
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Energy Efficiency Contracting (EEC) enables structural improvements in buildings by financing upgrades through the savings generated, eliminating the need for upfront investment by property owners. Although the model supports the energy transition and the reduction in GHG emissions, its adoption in the private sector faces relevant barriers such as the lack of information from the Energy Service Companies (ESCOs), distrust from clients in benefits with no upfront costs, and legal and behavioral barriers. To overcome these challenges, the FinSESCo platform, funded by Era-Net 2020 joint call, aims to channel private investments into building renovations and renewable energy installations via a crowdfunding portal. The platform allows individuals and organizations to finance small-scale renewable energy installations and energy efficiency measures for homeowners, tenants, and apartment owners. The new platform is likely to change the way EE investments are made and reach out to new audiences. A survey of 2585 German households sought to understand the drivers of EE investments, factors affecting the decisions, and their relationships with several demographic variables. Using a stepwise backward regression model, the study found significant differences between traditional investors in EE and those who would use the FinSESCo platform. Low- and medium-income households were more likely to take up the platform, and previous renewable energy ownership, experience with EEC models, and knowledge of crowdfunding further raised willingness to participate. The results point to the potential of the FinSESCo platform to expand EEC to new audiences, underlining its role of democratization and diversification of investments in building energy efficiency.
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(This article belongs to the Special Issue Financial Technology and Strategic AI Integration in FinTech: Transforming Banking, Payments, and Building a Sustainable Economy—Challenges and Opportunities)
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Examining the Drivers and Economic and Social Impacts of Cryptocurrency Adoption
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Yongsheng Guo, Ezaddin Yousef and Mirza Muhammad Naseer
FinTech 2025, 4(1), 5; https://doi.org/10.3390/fintech4010005 - 25 Jan 2025
Cited by 2
Abstract
This study investigates the key drivers and the economic and social impacts of cryptocurrency adoption. Based on panel data across 37 countries from 2020 to 2023, this research examines the interplay between cryptocurrency adoption and technology development, monetary policies, and economic and social
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This study investigates the key drivers and the economic and social impacts of cryptocurrency adoption. Based on panel data across 37 countries from 2020 to 2023, this research examines the interplay between cryptocurrency adoption and technology development, monetary policies, and economic and social development. Employing a mixed-methods approach, the research incorporates panel data analysis across multiple countries to explore correlations and causal relationships between these variables. The study found that technology development, measured by the Network Readiness Index (NRI) enables cryptocurrency adoption. Economic conditions measured by higher national inflation rates and monetary policy indicators, including lower interest and exchange rates are the key drivers for cryptocurrency adoption. The empirical findings reveal that cryptocurrency adoption has negative relationships with economic development measured by the GDP growth rate, unemployment rate, and social development represented by the governance quality corruption index. It implies that cryptocurrency is used as a virtual anchor (digital gold) for national inflation. Findings reveal how network readiness, economic conditions, and monetary policies contribute to fostering cryptocurrency adoption, while resulting in impacts on economic growth, labour markets, and governance. The research contributes to the literature by integrating technological, economic, and governance perspectives to elucidate the role of cryptocurrency in reshaping the global economic and social systems.
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(This article belongs to the Special Issue Trends and New Developments in FinTech)
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Open AccessReview
Exploring Financial Literacy in Higher Education with the Help of FinTech: A Bibliometric Analysis of Linkages to Access, Behavior, and Well-Being Through Digital Innovation
by
Ionut Marius Croitoru, Paula-Paraschiva Dragan (SPIRIDON), Nicoleta Daniela Ignat and Romanita Jumanca
FinTech 2025, 4(1), 4; https://doi.org/10.3390/fintech4010004 - 18 Jan 2025
Abstract
This study explores the dynamic interaction between financial literacy and higher education, focusing on the critical role of financial education in improving individual financial well-being. Using bibliometric analysis and the VOSviewer software, this research examines thematic clusters in financial literacy, categorized into access,
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This study explores the dynamic interaction between financial literacy and higher education, focusing on the critical role of financial education in improving individual financial well-being. Using bibliometric analysis and the VOSviewer software, this research examines thematic clusters in financial literacy, categorized into access, behavior, health, and education. By analyzing 469 articles from the Web of Science database (2020–2024), this study identifies trends and key linkages between financial literacy and societal well-being, highlighting the role of digital innovation. While FinTech is discussed as a facilitator of financial inclusion and education, the primary focus lies in understanding how financial literacy drives behavioral change, capacity building, and economic resilience. This paper provides information for policymakers and educators to design inclusive, behaviorally focused educational programs that address specific demographic needs, ultimately contributing to societal and economic resilience.
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(This article belongs to the Special Issue Trends and New Developments in FinTech)
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