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on Payment Systems and Financial Technology |
| By: | Raphael Auer; Ulf Lewrick; Jan Paulick |
| Abstract: | We investigate trends and drivers of cross-border flows of the two major native cryptoassets (Bitcoin and Ether) and the two major asset-backed stablecoins (Tether and USD Coin) between 184 countries from 2017 to 2024. These flows are substantial, peaking at around USD 2.6 trillion in 2021, with stablecoins accounting for close to half the volume. The unique bilateral data allow us to estimate the drivers of these flows in a gravity framework, and how they differ across different types of crypto assets. Our findings highlight speculative motives and global funding conditions as key drivers of native crypto asset flows. Transactional motives play a significant role in cross-border flows for stablecoins and low-value Bitcoin transactions, where we further find a strong association with higher costs of traditional remittances. Geographic barriers play a diminished role compared to traditional financial flows, and capital flow management measures appear ineffective. |
| Keywords: | cryptocurrency, payments, cross-border flows, blockchain, decentralised finance, capital flow management, Bitcoin, Ether, USD Coin, Tether, stablecoins, remittances |
| JEL: | F24 F32 F38 G15 G23 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:bis:biswps:1265 |
| By: | Dominic Russel; Claire Shi; Rowan Clarke |
| Abstract: | We use transaction-level data from a major payment processor in South Africa to study revenue-based financing for small businesses provided by financial technology (fintech) companies. After eight months, payments through the selected processor are 16% lower for businesses that take financing offers than for observably similar non-takers, due to businesses hiding revenue to avoid repayments (moral hazard) and the tendency for riskier businesses to seek financing more frequently (adverse selection). Two natural experiments suggest that fintech platforms non-lending interactions with small businesses for example, payment processing and inventory management can limit both hiding and selection. By tying repayment to the continued use of non-lending products, fintechs can reduce enforcement and monitoring frictions. Our results help explain the rise of fintech-provided revenue-based financing and provide evidence for policymakers looking to increase financial inclusion and boost the growth of firms, particularly in developing economies. |
| Date: | 2025–05–13 |
| URL: | https://d.repec.org/n?u=RePEc:rbz:wpaper:11078 |
| By: | Wang, Jiancheng; Li, Xiaoye |
| Abstract: | This paper studies China's big digital platforms’ value-added effect as venture capitalists, using a dataset of companies registered in China that eventually reach the initial public offering stage. We find that China's digital platforms’ investments positively affect their portfolio firms’ IPO performance, in terms of higher IPO valuation, lower underpricing, and shorter time to reach the IPO stage, which is inconsistent with the grandstanding hypothesis. The plausible underlying channels are the certification and monitoring roles played by China's digital platform. The results remain robust after addressing several concerns. Our study sheds new light on VCs’ characteristics and digital platforms’ activities. |
| Keywords: | digital platforms; IPO performance; new ventures; value adding; venture capital |
| JEL: | G23 G24 G32 L20 |
| Date: | 2023–06–01 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:118665 |
| By: | Yu Zhang; Zelin Wu; Claudio Tessone |
| Abstract: | Cryptocurrencies are digital tokens built on blockchain technology, with thousands actively traded on centralized exchanges (CEXs). Unlike stocks, which are backed by real businesses, cryptocurrencies are recognized as a distinct class of assets by researchers. How do investors treat this new category of asset in trading? Are they similar to stocks as an investment tool for investors? We answer these questions by investigating cryptocurrencies' and stocks' price time series which can reflect investors' attitudes towards the targeted assets. Concretely, we use different machine learning models to classify cryptocurrencies' and stocks' price time series in the same period and get an extremely high accuracy rate, which reflects that cryptocurrency investors behave differently in trading from stock investors. We then extract features from these price time series to explain the price pattern difference, including mean, variance, maximum, minimum, kurtosis, skewness, and first to third-order autocorrelation, etc., and then use machine learning methods including logistic regression (LR), random forest (RF), support vector machine (SVM), etc. for classification. The classification results show that these extracted features can help to explain the price time series pattern difference between cryptocurrencies and stocks. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.12771 |
| By: | Baston, George |
| Abstract: | Cross-border financial transactions involve complex processes due to the involvement of multiple intermediaries and the challenges of currency conversion. Blockchain technology offers significant improvements in the speed, efficiency, and transparency of these transactions by utilizing decentralized ledgers. The integration of Artificial Intelligence (AI) further enhances transaction security, risk management, and predictive analytics, which are crucial in financial markets. Blockchain enables real-time settlements and reduces the reliance on traditional financial intermediaries, reducing transaction costs and time delays. Additionally, AI systems improve market analysis by providing predictive insights and identifying patterns in large datasets. The combination of blockchain and AI facilitates interoperability between financial systems, enabling more efficient cross-border transactions, reducing operational inefficiencies, and promoting transparency. This paper explores the applications of blockchain and AI in cross-border transactions, market analysis, and their synergistic effects on enhancing financial systems. |
| Date: | 2025–04–14 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:wr6qc_v1 |
| By: | Marzanna Poniatowicz (Faculty of Economics and Finance, University of Bialystok); Agnieszka Piekutowska (Faculty of Economics and Finance, University of Bialystok) |
| Abstract: | Purpose The dynamic development of the alternative finance sector is a characteristic phenomenon of contemporary times. In the literature, the key reasons identified for this phenomenon are: i. Technological advancement: The development of digital technologies, including the Internet, blockchain, and artificial intelligence, has enabled the creation of innovative financial platforms and services that are more accessible and efficient compared to traditional financial institutions (Taherdoost, 2023; Lekhi, 2024). ii. Financial exclusion issues: Many small and medium-sized enterprises, startups, and individuals have limited access to traditional sources of financing, such as bank loans, due to stringent credit requirements. This exclusion manifests as a lack of access to traditional banking services, high costs and demands of traditional financial institutions, lack of flexibility of traditional financial services, limited geographical availability of specific financial services, low financial awareness, and a lack of trust in traditional financial institutions. Alternative finance, through technological innovations and flexible business models, offers solutions that can reduce the problem of financial exclusion and provide access to essential financial services for entities previously excluded from the traditional financial system (Carbó et al., 2005). iii. The search for higher returns: Investors are looking for new investment opportunities that offer higher returns compared to traditional bank deposits or bonds. Alternative forms of investing, such as crowdfunding, attract investors due to potentially higher profits (Freedman and Nutting, 2015). iv. Changes in consumer behavior in the market: The younger generation, known as Millennials and Generation Z, prefers convenient, fast, and online financial services. Young people are more open to using modern financial technologies and are less attached to traditional banks (CAsfera.pl, 2022). v. Changing regulations and government policies aimed at increasing competition in the financial sector: Many governments and regulatory bodies are introducing regulations that support the development of alternative finance. These include not only regulations regarding crowdfunding but also cryptocurrencies and open banking, which promote innovation and competition in the financial sector (World Bank and Cambridge Centre for Alternative Finance, 2019). The aforementioned conditions contribute to the rapid development of the alternative finance sector, which is becoming an increasingly important part of the global financial system. In this context, the dynamic growth of crowdfunding (CF) as a community financing instrument is also observed. CF appears to be a kind of phenomenon. The term was first used in 2006 by the American blogger M. Sullivan, founder of Fundavlog. One of the most comprehensive definitions of CF is proposed by Mollick (2014). According to him, CF “refers to the efforts by entrepreneurial individuals and groups - cultural, social, and for-profit - to fund their ventures by drawing on relatively small contributions from a relatively large number of individuals using the internet, without standard financial intermediaries” (Mollick, 2014). The research objective set by the authors is to determine the specifics of CF as an alternative financing tool in the Polish context. The authors focus on ten key characteristics of the analyzed instrument, including (1) community financing, (2) accessibility for small and medium-sized enterprises and startups, (3) lower entry barriers compared to traditional financial services, (4) direct interaction with investors, (5) diversity of financing models (e.g., donation-based CF, reward-based CF, royalty-based CF, equity CF, debt CF, etc.), (6) market testing, (7) marketing and promotion, (8) investment risk, (9) administrative support and legal regulations, and (10) community and engagement. Design/methodology/approach The study employed the method of analyzing literature related to the issues of alternative finance and CF, as well as the analysis of legal acts regulating CF for instance Regulation (EU) 2020/1503 of the European Parliament and of the Council of 7 October 2020 on European crowdfunding service providers for business) and the national level (the Act of 7 July 2022 on crowdfunding for business ventures and assistance to borrowers). Additionally, an analysis was conducted on the functioning of selected crowdfunding platforms and entities authorized to provide crowdfunding services, as well as an analysis of examples of investments financed using this instrument. The article also utilized statistical data from the European Securities and Markets Authority database. Findings The conducted research confirmed the research hypothesis, which states that the development of CF as a financial instrument in Poland is driven by technological advancements that enable the creation of innovative financial platforms, as well as by the ability of the instrument to offer greater financial flexibility (compared to traditional financing instruments), faster access to capital, and the potential to build communities around financed projects. It was shown that in Poland, compared to other EU member states (such as France, Italy, Spain, the Netherlands, and even Lithuania), CF is at an early stage of development (European Securities and Markets Authority Database, 2024). However, it has significant growth potential due to the aforementioned attributes. These features make it not only an attractive instrument for entities that face difficulties in obtaining traditional financing but also contribute to reducing financial exclusion in Poland. It was demonstrated that CF is gaining importance primarily as an alternative source of financing for small and medium-sized enterprises, startups, and various social and cultural projects. Originality/value The legal regulations regarding CF in Poland are relatively new, and analyses of the functioning of crowdfunding platforms and investments financed through this source of funding are limited. This analysis fills that gap. The unique economic context of Poland, with its specific economic and social conditions differing from those of other EU countries, is significant in this regard. The analysis of CF in Poland takes into account the specific conditions of the country, such as the level of digitization of society, trust in new technologies, the level of financial exclusion, and the specific financial needs of small and medium-sized enterprises. Moreover, Poland is one of the fastest growing fintech markets in Europe. Analyzing CF in this context allows us to understand how innovative financial technologies impact the development of alternative sources of financing in the country. Poland is at the stage of developing various types of crowdfunding platforms, including donation-based, equity-based, and reward-based platforms. Examining the functioning of these platforms provides valuable information about their effectiveness and attractiveness to different user groups. It is also worth noting that Poland has a strong community culture (e.g., "Solidarity" as a social movement in the 1980s, which played a key role in overthrowing communism in Poland and is one of the most well-known examples of a strong community and solidarity culture in Europe), which can promote the development of CF. Importantly, our research also considers the aspect of financial education, which is crucial for understanding and accepting alternative forms of financing by society. |
| Keywords: | Crowdfunding, Alternative financing, Investment |
| JEL: | G11 G23 G28 |
| Date: | 2024–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:aoh:conpro:2024:i:5:p:248-250 |
| By: | Okechukwu Christopher Onuegbu; Bettina Oboakore Agbamu; Belinda Uju Anyakoha; Ogonna Wilson Anunike |
| Abstract: | Digital banking is among the technological innovations currently reverberating the cyber wave. this study seeks to assess communication, awareness and acceptance of it among the residents of south-east and south-south, nigeria. the survey objectives were to ascertain awareness level of the south-east and south-south residents towards digital banking during the cash crunch, determine the acceptance level of digital banking among the south-east and south-south residents, find out the role of communication in awareness and acceptance of digital banking during the cash crunch in south-east and south-south nigeria, and assess the usage of digital banking amidst cash crunch in south-east and south nigeria. the study methodology is a sample survey which allowed researchers to administer questionnaires on 385 respondents out of the 50, 166, 807 study population. the findings showed that awareness level of digital banking was good (36%) in south-east and south-south nigeria during the cash crunch but it level of acceptance and usage improved more (37%) after the cash crunch. the study also ascertained that communication contribute significantly (59%) towards the usage and acceptance of digital banking in the two zones. it further showed that usage of digital banking in south-east and south-south has improved due to significant contributions of communication. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.10546 |
| By: | Joann Jasiak; Peter MacKenzie; Purevdorj Tuvaandorj |
| Abstract: | This paper examines how Canadian firms balance the benefits of technology adoption against the rising risk of cyber security breaches. We merge data from the 2021 Canadian Survey of Digital Technology and Internet Use and the 2021 Canadian Survey of Cyber Security and Cybercrime to investigate the trade-off firms face when adopting digital technologies to enhance productivity and efficiency, balanced against the potential increase in cyber security risk. The analysis explores the extent of digital technology adoption, differences across industries, the subsequent impacts on efficiency, and associated cyber security vulnerabilities. We build aggregate variables, such as the Business Digital Usage Score and a cyber security incidence variable to quantify each firm's digital engagement and cyber security risk. A survey-weight-adjusted Lasso estimator is employed, and a debiasing method for high-dimensional logit models is introduced to identify the drivers of technological efficiency and cyber risk. The analysis reveals a digital divide linked to firm size, industry, and workforce composition. While rapid expansion of tools such as cloud services or artificial intelligence can raise efficiency, it simultaneously heightens exposure to cyber threats, particularly among larger enterprises. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.12413 |
| By: | Han, Li |
| Abstract: | This paper investigates the synergistic integration of blockchain and artificial intelligence (AI) in financial systems, with emphasis on security, transparency, and operational efficiency. The study analyzes blockchain’s decentralized ledger mechanism and AI’s anomaly detection algorithms in enhancing fraud prevention and regulatory compliance. It explores the application of these technologies in cross-border payments and high-frequency trading (HFT), demonstrating their impact on settlement time reduction, transaction cost minimization, and market execution precision. Case studies include the role of Ripple and Stellar in decentralized remittance systems and AI optimization in algorithmic trading strategies. The paper also addresses limitations such as regulatory divergence, technological interoperability, model risk, and cybersecurity vulnerabilities, highlighting implementation challenges in financial infrastructures. |
| Date: | 2025–04–16 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:2mn3f_v1 |
| By: | Harang Ju; Michael Zhao; Sinan Aral |
| Abstract: | Prior spending shutoff experiments in search advertising have found that paid ads cannibalize organic traffic. But it is unclear whether the same is true for other high volume advertising channels like mobile display advertising. We therefore analyzed a large-scale spending shutoff experiment by a US-based mobile game developer, GameSpace. Contrary to previous findings, we found that paid advertising boosts organic installs rather than cannibalizing them. Specifically, every $100 spent on ads is associated with 37 paid and 3 organic installs. The complementarity between paid ads and organic installs is corroborated by evidence of temporal and cross-platform spillover effects: ad spending today is associated with additional paid and organic installs tomorrow and impressions on one platform lead to clicks on other platforms. Our findings demonstrate that mobile app install advertising is about 7.5% more effective than indicated by paid install metrics alone due to spillover effects, suggesting that mobile app developers are under-investing in marketing. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.16151 |
| By: | Mbate, Michael; Fall, El Hadji |
| Abstract: | This paper examines the relationship between financial inclusion and energy access, leveraging micro-level survey data from Kenya (2016–2018) and employing propensity score matching to establish causal linkages. The analysis reveals that financial inclusion significantly enhances energy access, with distinct variations across financial institutions and energy types. Financial inclusion operates through three critical mechanisms: increasing households’ willingness to pay for energy, alleviating upfront connection costs via flexible payment schemes, and enabling seamless energy-related transactions through digital platforms. These findings underscore the importance of inclusive financial policies and the role of formal and informal financial institutions as intermediaries in addressing energy poverty. |
| Keywords: | digital platforms; energy access; energy costs; financial inclusion; propensity score matching; willingness to pay |
| JEL: | Q40 O13 G21 N27 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:127538 |
| By: | Bernd Hayo; Matthias Neuenkirch; Manuel Walz |
| Abstract: | This documentation paper provides background information and basic descriptive statistics for a representative survey of the French, German, and Italian populations, focusing on attitudes towards and the demand for a digital euro conducted on our behalf by Dynata in November and December 2023. The survey is quota-based by gender, age, income, and region. To measure views on a digital euro, the survey controls for various characteristics, including the digitalisation of daily life, financial literacy, payment behaviour, attitudes towards European integration, and several socio-demographic characteristics. Additionally, three treatments are implemented. Treatment 1 highlights the differences between private and public money, Treatment 2 presents various hypothetical designs for a digital euro, and Treatment 3 introduces a digital euro holding limit. |
| Keywords: | Digital Euro, ECB, Monetary Policy, Money Demand, Payment Systems |
| JEL: | E41 E42 E51 E58 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:trr:wpaper:202504 |
| By: | Hassan, Wesam Adel |
| Abstract: | This article examines cryptocurrency trading in Turkey, focusing on the ‘gamblification’ of this emerging market. Based on 18 months of ethnographic research (2021-2022) conducted during an economic crisis exacerbated by the COVID-19 pandemic, the research reveals how Turks engaged with cryptocurrencies are considering the structural parallels between trading and gambling. The article also incorporates the perspective of Turkey's Directorate for Religious Affairs (Diyanet), which has declared cryptocurrency trading impermissible, highlighting the tension between contemporary financial practices and traditional Islamic frameworks. The article links the perception of cryptocurrency trading as a modern game of chance, as articulated by research participants, to Turkey's economic instability and their technological shift from traditional state-regulated games of chance (lotteries, betting on sports, and horse racing) to cryptocurrency trading. My ethnographic method brings new empirical data and qualitative analysis to understand the cultural and religious dynamics shaping this emergent financial phenomenon in the under-studied context of Turkey. I argue that cryptocurrency adoption in Turkey is driven by more than economic necessity; it reflects a cultural transformation valuing modernity and innovation. Many Turks view cryptocurrency as a viable alternative to traditional financial systems and a representation of the future of money. This shift signifies a departure from conventional monetary practices and reflects a collective idealisation of the future of finance. The article thus illuminates how Turkish individuals navigate risk and speculation during economic crises, demonstrating their adaptability in engaging with non-monetary financial markets. |
| Keywords: | cryptocurrency; gambling; Turkey; trading; Islam |
| JEL: | F3 G3 J1 |
| Date: | 2025–03–24 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:127631 |
| By: | Leonardo Madio; Matthew Mitchell; Martin Quinn; Carlo Reggiani |
| Abstract: | We study the competitive impact of content moderation by a dominant online platform. We exploit an exogenous shock that led the largest adult content platform to remove all non-verified content, eliminating 80% of its video library. Using a difference-in-differences approach and leveraging on daily website-country level traffic data, we find that this policy resulted in a 41% drop in traffic within one month, suggesting strong user preferences for the removed content. However, much of the displaced traffic was absorbed by competing platforms, including both mainstream rivals and less regulated fringe websites. Over six months, fringe sites experienced a 55% increase in visits, far outpacing the 10% growth of mainstream competitors. Search engines played a critical role in this reallocation: fringe platforms saw a surge in traffic from search referrals and aggregators, as users actively sought alternative content sources. We document an intensification of competition in search: the leading platform became more aggressive towards copyright-infringing rivals, strategically using DMCA filings to remove competing content from search results. Our findings highlight how asymmetric exposure to content moderation shocks can reshape market competition, drive consumers toward less regulated spaces, and alter substitution patterns across platforms. |
| Keywords: | content moderation, platforms, adult websites, search. |
| JEL: | D83 K42 L82 O39 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11842 |
| By: | GEORGAKAS, IOANNIS |
| Abstract: | Adopting a common European digital currency seems likely to be a powerful monetary tool that will facilitate the implementation of policies such as quantitative easing and interest rate regulation. On the other hand, the risk of destabilisation of the banking system , requires careful planning and public awareness. CBDCs will strengthen the EU geopolitically and seem to have an environmental dimension. The debate within the EU and the ECB is intense both on issues of legitimacy under the European Treaties and on issues of democracy and privacy rights. In practice, this is a technological innovation with serious parallel economic, social and political consequences. |
| Keywords: | CBDCs, Eurozone policy, Monetary Sovereignty, ECB, Personal Data, Privacy |
| JEL: | E42 E52 E58 |
| Date: | 2025–04–18 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:124457 |
| By: | Sara A. Safari; Maximilian Janisch; Thomas Leh\'ericy |
| Abstract: | In the theory of financial markets, a stylized fact is a qualitative summary of a pattern in financial market data that is observed across multiple assets, asset classes and time horizons. In this article, we test a set of eleven stylized facts for financial market data. Our main contribution is to consider a broad range of geographical regions across Asia, continental Europe, and the US over a time period of 150 years, as well as two of the most traded cryptocurrencies, thus providing insights into the robustness and generalizability of commonly known stylized facts. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.08611 |
| By: | Filip Stefaniuk; Robert \'Slepaczuk |
| Abstract: | The article investigates the usage of Informer architecture for building automated trading strategies for high frequency Bitcoin data. Three strategies using Informer model with different loss functions: Root Mean Squared Error (RMSE), Generalized Mean Absolute Directional Loss (GMADL) and Quantile loss, are proposed and evaluated against the Buy and Hold benchmark and two benchmark strategies based on technical indicators. The evaluation is conducted using data of various frequencies: 5 minute, 15 minute, and 30 minute intervals, over the 6 different periods. Although the Informer-based model with Quantile loss did not outperform the benchmark, two other models achieved better results. The performance of the model using RMSE loss worsens when used with higher frequency data while the model that uses novel GMADL loss function is benefiting from higher frequency data and when trained on 5 minute interval it beat all the other strategies on most of the testing periods. The primary contribution of this study is the application and assessment of the RMSE, GMADL, and Quantile loss functions with the Informer model to forecast future returns, subsequently using these forecasts to develop automated trading strategies. The research provides evidence that employing an Informer model trained with the GMADL loss function can result in superior trading outcomes compared to the buy-and-hold approach. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.18096 |
| By: | Bakreski, Filip |
| Abstract: | This research paper examines the phenomenon of population collapse in digital gaming ecosystems from 2010 to 2024. Through analysis of player statistics, developer communications, community sentiment, and economic factors, we identify common patterns and causal mechanisms of rapid player base decline. Using case studies of major titles including World of Warcraft, Fortnite, Anthem, and Fallout 76, alongside theoretical frameworks from network economics and systems dynamics, we explore how and why gaming populations rise, fall, and occasionally recover. The research reveals key collapse triggers—content droughts, poor management, monetization shifts, technical issues, and competitive pressure—while highlighting successful prevention strategies such as consistent content delivery, transparent communication, and technical stability. This paper contributes to understanding digital ecosystem sustainability with implications for game developers, community managers, and digital platform operators. |
| Date: | 2025–04–11 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:56rvh_v1 |
| By: | Ophir Friedler; Hu Fu; Anna Karlin; Ariana Tang |
| Abstract: | Platforms design the form of presentation by which sellers are shown to the buyers. This design not only shapes the buyers' experience but also leads to different market equilibria or dynamics. One component in this design is through the platform's mediation of the search frictions experienced by the buyers for different sellers. We take a model of monopolistic competition and show that, on one hand, when all sellers have the same inspection costs, the market sees no stable price since the sellers always have incentives to undercut each other, and, on the other hand, the platform may stabilize the price by giving prominence to one seller chosen by a carefully designed mechanism. This calls to mind Amazon's Buy Box. We study natural mechanisms for choosing the prominent seller, characterize the range of equilibrium prices implementable by them, and find that in certain scenarios the buyers' surplus improves as the search friction increases. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.14793 |
| By: | Xu, Lei |
| Abstract: | This paper investigates the implementation of artificial intelligence (AI) and blockchain technologies in the smart transportation infrastructure of Shenzhen between 2024 and 2025. It analyzes Shenzhen's electrification of public transport, integration of AI for traffic signal optimization, and deployment of AI-enhanced passenger safety systems. The paper also examines the role of blockchain in ensuring secure, decentralized data exchange, and energy trading protocols for electric vehicles. Additionally, challenges such as data interoperability, security, and ethical governance are discussed. The findings provide insights into how emerging technologies can transform urban mobility and establish a replicable model for global smart city development. |
| Date: | 2025–04–14 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:yn67b_v1 |
| By: | Timoth\'ee Fabre; Damien Challet |
| Abstract: | This paper investigates real-time detection of spoofing activity in limit order books, focusing on cryptocurrency centralized exchanges. We first introduce novel order flow variables based on multi-scale Hawkes processes that account both for the size and placement distance from current best prices of new limit orders. Using a Level-3 data set, we train a neural network model to predict the conditional probability distribution of mid price movements based on these features. Our empirical analysis highlights the critical role of the posting distance of limit orders in the price formation process, showing that spoofing detection models that do not take the posting distance into account are inadequate to describe the data. Next, we propose a spoofing detection framework based on the probabilistic market manipulation gain of a spoofing agent and use the previously trained neural network to compute the expected gain. Running this algorithm on all submitted limit orders in the period 2024-12-04 to 2024-12-07, we find that 31% of large orders could spoof the market. Because of its simple neuronal architecture, our model can be run in real time. This work contributes to enhancing market integrity by providing a robust tool for monitoring and mitigating spoofing in both cryptocurrency exchanges and traditional financial markets. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.15908 |
| By: | Hiroshi Oishi (Bank of Japan); Eisuke Kobayashi (Bank of Japan); Yoshihiko Sugihara (Bank of Japan) |
| Abstract: | Non-Bank Financial Intermediation (NBFI) accounts for about half of global financial assets and plays a pivotal role in financial intermediation activities. Recent observations have indicated a marked shift in the composition of NBFI, with a notable increase in the presence of investment funds, contrasting with the traditional composition of NBFI, which comprises insurance corporations and pension funds. The interconnectedness between banks and NBFI is also viewed to be increasing, mainly through increases in their cross-border transactions. Consequently, there has been a rise in cases where responses of NBFI, particularly investment funds, have been considered as contributing to the amplification of financial stresses, leading to heightened financial market volatility. In view of the potential for such stresses to propagate throughout the global financial system, including the banking sector, a series of policy recommendations have been issued by the Financial Stability Board (FSB) to contain vulnerabilities of NBFI. This article presents an overview of NBFI's financial intermediation, summarizes policy initiatives designed to enhance its resilience, and provides perspectives on issues surrounding NBFI through a review of the FSB's regular issue of the "Global Monitoring Report on Non-Bank Financial Intermediation" and its policy recommendations. |
| Keywords: | non-bank financial institutions; financial intermediation; financial risk and risk management; government policy and regulation |
| JEL: | G23 G15 G32 G28 |
| Date: | 2025–05–15 |
| URL: | https://d.repec.org/n?u=RePEc:boj:bojrev:rev25e06 |
| By: | Duc Tuyen TA; Wajdi Ben Saad; Ji Young Oh |
| Abstract: | With the introduction of the PSD2 regulation in the EU which established the Open Banking framework, a new window of opportunities has opened for banks and fintechs to explore and enrich Bank transaction descriptions with the aim of building a better understanding of customer behavior, while using this understanding to prevent fraud, reduce risks and offer more competitive and tailored services. And although the usage of natural language processing models and techniques has seen an incredible progress in various applications and domains over the past few years, custom applications based on domain-specific text corpus remain unaddressed especially in the banking sector. In this paper, we introduce a language-based Open Banking transaction classification system with a focus on the french market and french language text. The system encompasses data collection, labeling, preprocessing, modeling, and evaluation stages. Unlike previous studies that focus on general classification approaches, this system is specifically tailored to address the challenges posed by training a language model with a specialized text corpus (Banking data in the French context). By incorporating language-specific techniques and domain knowledge, the proposed system demonstrates enhanced performance and efficiency compared to generic approaches. |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.12319 |
| By: | Biljana Angelova (Ss. Cyril and Methodius University in Skopje, Institute of Economics - Skopje); Violeta Cvetkoska (Ss. Cyril and Methodius University in Skopje, Faculty of Economics – Skopje); Milanka Dimovska (Ss. Cyril and Methodius University in Skopje, Faculty of Economics – Skopje) |
| Abstract: | Purpose Financial institutions are rapidly following the applications of artificial intelligence (AI) allowing them to better organize and perform job duties and understand their customers. With the application of AI, employees in financial institutions will not be burdened with the performance of operational activities and will have more time to devote themselves to their professional and personal growth and development. In this way, technology such as AI will not replace people but will be their support. This current topic is the main incentive to delve deeper into the application of AI in financial institutions through bibliometric data visualization and analysis. Many managers have an aversion to using artificial intelligence algorithms in decision-making, despite their superior performance (Mahmud et al., 2023). Banks, as the most important actors for the continuity of the financial system, should conduct evaluation and measurement of branch performance and set goals for them and portfolio managers, which is an important process for decision-making and strategic planning in the banking industry (Met at al., 2023). Poor decision-making in financial institutions is likely to cause financial crises (Weng and Huang, 2021). Аrtificial intelligence and machine learning are helping many managers to focus on key and strategic aspects and spend less time on repetitive tasks, enabling better financial risk management (Mahalakshmi et al., 2022). The artificial intelligence system enables development accompanied by better performance and optimization (Dennis et al., 2023). The gradual application of artificial intelligence in corporate financial risk management results in a decent performance in recalling fraudulent firms (Lin and Gao, 2022). COVID-19 has affected the change of digitalization and technological development of financial institutions (Aziz et al., 2022). Many challenges for financial services have opened up with the transition to digital freedom (Narsimha et al., 2022). Detecting activities related to financial cybercrime is a major problem, as a highly restrictive algorithm can block all suspicious activities that interfere with customers' real business (Nicholls et al., 2021). Customers are increasingly facing many fraudulent attacks and scams in financial banking operations, and cybercriminals have found the opportunity to use financial transactions to carry out their fraudulent activities (Narsimha et al., 2022). A large volume of sensitive customer-related data circulates and accumulates in financial institutions every day (Park et al., 2021). In the financial sector, machine learning algorithms, in addition to being used in fraud detection and providing financial advice to investors, can also examine a large database in a short period (Lei et al., 2022). Design/methodology/approach The data for the bibliometric analysis has been downloaded from the Scopus database. By applying the Prisma protocol, in the first phase-identification, we searched for the terms “financial institutions”, “artificial intelligence” and “AI”. 467 documents were identified during the period 1987-2023. The language of the documents was English. In the second phase-screening, no document was excluded because non-English documents and duplicates were not identified. In the third phase-eligibility, 281 documents were excluded because only the articles were eligible and the total sample in this phase consisted of 186 articles. In the fourth phase-inclusion, we undertook a manual check of the relevance of each article based on an analysis of the abstracts 70 articles were excluded due to their irrelevance and the total sample in this phase consists of 116 articles. Furthermore, the VOSviewer software was employed for authors' co-authorship, organizations' co-authorship, and countries' co-authorship analysis, keyword co-occurrence analysis of the abstracts for the whole period and the last five years and keyword co-occurrence analysis for the last five years for the used methods, models, and software. Findings The number of articles related to AI in financial institutions has been growing in the last three years of the analyzed period. 84% of the articles were published by co-author teams and 16% by a single author. The most cited single author is Mhlanga D. and the journal Expert Systems with Applications takes the first place in terms of the source of published articles and number of citations. From the analysis made with VOSviewer software, it can be concluded that: it does not mean that if some countries are geographically closer, the authors will write papers in co-authorship, USA is in first place both in terms of the number of citations and in terms of the number of published articles, from all the clusters the terms that occur the most for the whole period are learning, implication, tree, statistical method and risk evaluation. According to their occurrences, the terms that appear most concerning methods, models, and software in the last five years of the period are prediction model, correlation, discriminant analysis, statistical technique, classification method, and clustering. Originality/value The analysis of abstracts and citations is of great importance in the exchange of knowledge as well as the monitoring of trends. The obtained results and conclusions can be used for further research both by academics and by all those who have an interest in researching financial institutions and artificial intelligence. |
| Keywords: | AI, Artificial intelligence, Financial institutions |
| JEL: | G21 G22 J29 O31 |
| Date: | 2024–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:aoh:conpro:2024:i:5:p:244-247 |