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on Payment Systems and Financial Technology |
| By: | Ozili, Peterson K |
| Abstract: | This study examines the effect of capital outflows, induced by geopolitical shocks, on financial inclusion and digital financial inclusion in emerging markets and developing economies. Several measures of financial inclusion and digital financial inclusion were analysed for 17 emerging markets and developing economies from 1999 to 2023. The data were estimated using the median quantile regression and generalized linear model regression methods. The findings reveal that capital outflows, induced by geopolitical shocks, have a negative effect on financial inclusion and digital financial inclusion. Greater capital outflows, induced by geopolitical shock, decrease the level of financial inclusion through a contraction in the number of commercial bank branches in emerging markets and developing economies. Also, greater capital outflows, induced by geopolitical shock, decrease the level of digital financial inclusion through a decrease in the number of people using the internet to access commercial bank branch services and automated teller machine services. Political stability, GDP growth, population growth, unemployment, tax revenue and regulatory quality are significant determinants of financial inclusion and digital financial inclusion. The social implication is that geopolitical shocks and capital outflows adversely affect society by limiting access to essential financial services. The managerial implication is that financial managers will constantly need to anticipate geopolitical risk, its effect on financial services and develop safeguards to cushion its effect on financial service providers and customers. |
| Keywords: | Geopolitical risk, shocks, financial inclusion, digital financial inclusion, capital outflow, foreign direct investment, financial inclusion index, bank branch, depositors, automated teller machines, fintech |
| JEL: | G21 G23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125567 |
| By: | Ozili, Peterson K |
| Abstract: | Forced displacement poses a challenge to development. It displaces men, women, and children from their places of residence, making them strangers in another community and country. In the host country, they often lack legal identity. As a result, they cannot access basic formal financial services because financial service providers won’t serve them without formal legal identification. This puts forcibly displaced persons in a vulnerable situation. Financial inclusion for forcibly displaced persons, if it can be achieved, can give them access to basic financial services, which they can use to build resilience and cope with the humanitarian crises that accompany forced displacement. This study identifies some strategies to increase financial inclusion for forcibly displaced persons. It also highlights some challenges that may be encountered in advancing financial inclusion for forcibly displaced persons. The insights offered in this article are useful for development policymaking. It is also useful to academics, policymakers, and practitioners involved in activities, projects, or programs that are aimed at restoring the livelihoods of vulnerable people. |
| Keywords: | Crisis, financial inclusion, forcibly displace people, resilience, vulnerable group theory of financial inclusion, vulnerable people |
| JEL: | G20 G21 G23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125563 |
| By: | Ethan Buchman; Paolo Dini; Shoaib Ahmed; Andrew Miller; Toma\v{z} Fleischman |
| Abstract: | For centuries, financial institutions have responded to liquidity challenges by forming closed, centralized clearing clubs with strict rules and membership that allow them to collaborate on using the least money to discharge the most debt. As closed clubs, much of the general public has been excluded from participation. But the vast majority of private sector actors consists of micro or small firms that are vulnerable to late payments and generally ineligible for bank loans. This low liquidity environment often results in gridlock and leads to insolvency, and it disproportionately impacts small enterprises and communities. On the other hand, blockchain communities have developed open, decentralized settlement systems, along with a proliferation of store of value assets and new lending protocols, allowing anyone to permissionlessly transact and access credit. However, these protocols remain used primarily for speculative purposes, and so far have fallen short of the large-scale positive impact on the real economy prophesied by their promoters. We address these challenges by introducing Cycles, an open, decentralized clearing, settlement, and issuance protocol. Cycles is designed to enable firms to overcome payment inefficiencies, to reduce their working capital costs, and to leverage diverse assets and liquidity sources, including cryptocurrencies, stablecoins, and lending protocols, in service of clearing more debt with less money. Cycles solves real world liquidity challenges through a privacy-preserving multilateral settlement platform based on a graph optimization algorithm. The design is based on a core insight: liquidity resides within cycles in the payment network's structure and can be accessed via settlement flows optimized to reduce debt. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.22309 |
| By: | Ozili, Peterson K; Obiora, Kingsley I; Onuzo, Chinwendu |
| Abstract: | Large language models have gained popularity, and it is important to understand their applications in the financial inclusion domain. This study identifies the benefits and risks of using large language models (LLMs) in the financial inclusion domain. We show that LLMs can be used to (i) summarize the key themes in financial inclusion communications, (ii) gain insights from the tone of financial inclusion communications, (iii) bring discipline to financial inclusion communications, (iv) improve financial inclusion decision making, and (v) enhance context-sensitive text analysis and evaluation. However, the use of large language models in the financial inclusion domain poses risks relating to biased interpretations of LLM-generated responses, data privacy risk, misinformation and falsehood risks. We emphasize that LLMs can be used safely in the financial inclusion domain to summarise financial inclusion speeches and communication, but they should not be used in situations where finding the truth is important to make decisions that promote financial inclusion. |
| Keywords: | financial inclusion, large language models, LLM, algorithm, risk, benefit, communication, speech, artificial intelligence, digital financial inclusion |
| JEL: | G20 G21 G23 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125562 |
| By: | C S Mohapatra (National Council of Applied Economic Research); Depannita Ghosh (National Council of Applied Economic Research) |
| Abstract: | This paper proposes a multidimensional strategy for advancing financial inclusion in India as a cornerstone of the nation’s Viksit Bharat@2047 vision. It argues that inclusion must evolve from a metric of access to a transformative tool of economic citizenship—anchored in sustained literacy, institutional trust, equitable access, and user empowerment. India has made remarkable progress in expanding financial services. With over 54 crore Jan Dhan accounts, widespread use of the Unified Payments Interface (UPI), and targetted government schemes such as PMMY, APY, and PMSBY, formal financial access has increased across geographies and demographics. However, this infrastructural reach has not always translated into meaningful engagement. Inactive accounts, persistent gender and rural gaps, limited digital literacy, and deep-seated mistrust continue to hinder effective inclusion, especially among women, persons with disabilities, and low-income households. This paper conceptualises a shift from infrastructural inclusion to functional and resilient inclusion. It proposes four interdependent pillars as the foundation for long-term financial inclusion: (a) Sustained digital and financial literacy: financial literacy must be continuous, contextualised, and adaptive across life stages—delivered in local languages and formats tailored to diverse user needs; (b) Trustworthy institutions and transparent service delivery: building trust requires fair, culturally sensitive, and linguistically accessible services supported by strong grievance redress mechanisms and algorithmic accountability; (c) Inclusive technology design: digital tools must be accessible by default, incorporating universal design principles to serve users with disabilities, low literacy, or limited connectivity; and (d) Community-led financial ecosystems: community institutions such as SHGs, cooperatives, and panchayats must be embedded in policy design and service delivery to ensure credibility, ownership, and sustainability. The paper offers a comprehensive framework involving coordinated governance among regulators (RBI, SEBI, IRDAI, PFRDA, and IEPFA), enhanced financial literacy convergence, and rights-based legal safeguards. It advocates for embedding equity through targetted policy instruments, such as a National Disability Financial Inclusion Strategy, a Unified Inclusion Dashboard, and localised outreach models. The paper concludes by emphasising that financial inclusion for Viksit Bharat must be a sustained institutional commitment, rooted in participation, protection, provisioning, and permanence. It is not merely a vehicle for economic growth, but a democratic imperative for building a just and resilient financial future. |
| Keywords: | Financial Empowerment, Digital Financial Literacy, Vulnerable Communities, Community-based Literacy, Digitalization |
| JEL: | O16 G10 G28 D14 I38 |
| Date: | 2025–06–03 |
| URL: | https://d.repec.org/n?u=RePEc:nca:ncaerw:183 |
| By: | Luyao Zhang |
| Abstract: | Stablecoins have become a foundational component of the digital asset ecosystem, with their market capitalization exceeding 230 billion USD as of May 2025. As fiat-referenced and programmable assets, stablecoins provide low-latency, globally interoperable infrastructure for payments, decentralized finance, DeFi, and tokenized commerce. Their accelerated adoption has prompted extensive regulatory engagement, exemplified by the European Union's Markets in Crypto-assets Regulation, MiCA, the US Guiding and Establishing National Innovation for US Stablecoins Act, GENIUS Act, and Hong Kong's Stablecoins Bill. Despite this momentum, academic research remains fragmented across economics, law, and computer science, lacking a unified framework for design, evaluation, and application. This study addresses that gap through a multi-method research design. First, it synthesizes cross-disciplinary literature to construct a taxonomy of stablecoin systems based on custodial structure, stabilization mechanism, and governance. Second, it develops a performance evaluation framework tailored to diverse stakeholder needs, supported by an open-source benchmarking pipeline to ensure transparency and reproducibility. Third, a case study on Real World Asset tokenization illustrates how stablecoins operate as programmable monetary infrastructure in cross-border digital systems. By integrating conceptual theory with empirical tools, the paper contributes: a unified taxonomy for stablecoin design; a stakeholder-oriented performance evaluation framework; an empirical case linking stablecoins to sectoral transformation; and reproducible methods and datasets to inform future research. These contributions support the development of trusted, inclusive, and transparent digital monetary infrastructure. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.02403 |
| By: | Rees Hagler; Dhiren Patki |
| Abstract: | Credit card data indicate that since 2022, spending by higher-income consumers has remained resilient and has been driving the growth in aggregate spending. By contrast, spending growth of low-income consumers has not been as strong. |
| Keywords: | consumer spending; credit card debt; household income |
| JEL: | E21 G51 |
| Date: | 2025–08–13 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedbcq:101425 |
| By: | Yukihiro Nishimura (Osaka University and CESifo) |
| Abstract: | Online markets like app stores are typically characterized by a monopoly who set prices on both sides — the prices of the network good (such as iPhone) and the commission fee to participating firms. There is an ongoing concerns on the welfare consequences of imperfect competition, where the antitrust authorities in the EU are keen about the monopolistic commission fee. With online apps as a representative example, this study investigates the welfare effects of price ceiling policies. The following results are shown. If the network-size externality on apps’ price is stronger than the app variety’s network externality, then, first, the price ceiling on the network good increases both the producer surplus of the app developers and the consumer surplus of the end-users. Second, in contrast, the price ceiling on the commission fee for the developers reduces the consumer surplus. The reverse proposition holds when the order of the strength of two network externalities is reversed. By the level of the unconstrained equilibrium commission fee, a regulator can identify which policy would make both consumers and developers better off. |
| Keywords: | Digital economy; Platform; Antitrust pricing; Network externality |
| JEL: | F23 L13 D85 K21 L86 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:osk:wpaper:2505 |
| By: | Aaron Green; Zihan Nie; Hanzhen Qin; Oshani Seneviratne; Kristin P. Bennett |
| Abstract: | Survival modeling predicts the time until an event occurs and is widely used in risk analysis; for example, it's used in medicine to predict the survival of a patient based on censored data. There is a need for large-scale, realistic, and freely available datasets for benchmarking artificial intelligence (AI) survival models. In this paper, we derive a suite of 16 survival modeling tasks from publicly available transaction data generated by lending of cryptocurrencies in Decentralized Finance (DeFi). Each task was constructed using an automated pipeline based on choices of index and outcome events. For example, the model predicts the time from when a user borrows cryptocurrency coins (index event) until their first repayment (outcome event). We formulate a survival benchmark consisting of a suite of 16 survival-time prediction tasks (FinSurvival). We also automatically create 16 corresponding classification problems for each task by thresholding the survival time using the restricted mean survival time. With over 7.5 million records, FinSurvival provides a suite of realistic financial modeling tasks that will spur future AI survival modeling research. Our evaluation indicated that these are challenging tasks that are not well addressed by existing methods. FinSurvival enables the evaluation of AI survival models applicable to traditional finance, industry, medicine, and commerce, which is currently hindered by the lack of large public datasets. Our benchmark demonstrates how AI models could assess opportunities and risks in DeFi. In the future, the FinSurvival benchmark pipeline can be used to create new benchmarks by incorporating more DeFi transactions and protocols as the use of cryptocurrency grows. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.14160 |
| By: | Arman Abgaryan; Utkarsh Sharma; Joshua Tobkin |
| Abstract: | We introduce a decentralised, algorithmic framework for permissionless, multi-strategy capital allocation via tokenised, automated vaults. The system is designed to function analogously to a multi-strategy asset management company, but implemented entirely on-chain through a modular architecture comprising four interacting layers. The first, the capitalisation layer, composed of vaults that facilitate multi-asset deposits, tokenises investor participation, and specifies high level risk limits and admissible venues for deployment. The second, the strategy layer, enables the submission of strategies by human developers or autonomous agents, creating a decentralised marketplace governed by a validation mechanism incorporating adversarial and gamified elements. The third, the execution layer, operationalises strategy deployment using the host blockchain network's services. The fourth layer, the validated allocation layer, assesses and allocates capital among validated strategies, dynamically rebalancing toward those exhibiting superior risk-adjusted performance. In the framework, each admitted strategy acts as a manager for the "fund", encapsulated in a smart contract vault that issues transferable V-Tokens, conveying fractional ownership of the real-time portfolio operated by the vault. The system is designed to be open to participation by both human and AI agents, who collectively perform the roles of capital allocators, strategy developers, and validated allocators. The resulting structure is a self-regulating asset management ecosystem capable of decentralised, cooperative optimisation across traditional and digital financial domains. This framework is facilitated by a host chain network, which offers native automation and data oracle services enabling vault entities to autonomously operate on-chain, paving the way for being self sufficient in dynamic allocation of capital. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.00978 |
| By: | Alex Acheampong (Bond University); Donghyun Park (Asian Development Bank); Shu Tian (Asian Development Bank) |
| Abstract: | This study investigates the poverty reduction gains that are associated with access to digital technologies by using panel data based on 113 countries from 2000 to 2022. We address cross-sectional and temporal dependency with the Driscoll-Kraay technique, and endogeneity with the Lewbel two-stage least squares technique. The results indicate that the digital technology access index—comprising broadband, telephone, mobile, and internet access—contributes to poverty reduction, with the effect being persistent. Except for mobile phone usage, the rest of the digital technology proxies do not follow the critical mass hypothesis. Mediation analysis indicates that access to digital technologies contributes to poverty reduction by working through increasing gross domestic product per capita; accessing finance, education, and employment; and reducing income inequality. The poverty reduction gains of digital technologies are evident in developing Asia, landlocked/island nations, coastal/non-island countries, and advanced economies, with broadband and internet access contributing to poverty reduction during the coronavirus disease (COVID-19) pandemic. Given the role of digital technologies in strengthening resilience, we call on policymakers to invest in and expand digital connectivity, particularly to vulnerable communities. |
| Keywords: | digital technologies;poverty;inclusive growth;COVID-19;developing Asian countries |
| JEL: | I30 O11 O30 |
| Date: | 2025–08–11 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:021463 |
| By: | Isaac Otchere; Zia Mohammed; Witness Simbanegavi |
| Abstract: | In this paper we examine the relationship between fintech formations and the default risk and performance of incumbent financial institutions in South Africa. We find that the development of fintech startups is associated with lower bankruptcy risk, credit risk and stock return volatility among banks and other financial institutions. Fintech startup formations are also associated with improvement in incumbent institutions performance. Further analysis shows that the risk reduction effect of fintech development is more pronounced for smaller banks. Overall, our results are consistent with the assertion that fintech formations generally improve risk management efficiency and reduce incumbent financial institutions default risk. However, the relationship is nonlinear, suggesting that the initial collaboration, which reduces default risk, can turn into increased competition as more fintech startups enter the market. From a policy standpoint, efforts to promote more collaboration should be encouraged, but regulators need to be cautious of potential systemic risk. |
| Date: | 2025–08–04 |
| URL: | https://d.repec.org/n?u=RePEc:rbz:wpaper:11082 |
| By: | Kozo UEDA |
| Abstract: | This study utilizes novel bank transaction data from business accounts to analyze inter-industry money ows and their relation to the input-output table. Results reveal a strong correlation between money ows in the bank data and physical ows in the input-output table. Further, lagged money ows from a destination industry signicantly predict current money ows, highlighting the role of supplychain connections in shaping money ow dynamics. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:cnn:wpaper:25-019e |
| By: | Rodríguez-Pose, Andrés; Sandu, Alexandra |
| Abstract: | In this paper we investigate what determines access to banking in Central and Eastern Europe (CEE). The research uses different waves of the OeNB Euro Survey – covering over 91, 000 individuals during the period 2012–2020 – and pooled and multilevel logit models to analyse how the interplay of trust in institutions, socio-economic attributes and geographic contexts shapes access to bank accounts, savings deposits and loans across 10 CEE countries. The findings reveal significant disparities in banking inclusion across products: while institutional trust enhances access to current accounts and savings deposits, its impact on loans is weaker. Socio-economic factors and geographical contexts, particularly at the local NUTS3 level, also matter enormously for financial inclusion. National and local economic conditions are key in shaping variations in financial inclusion/exclusion across CEE. |
| Keywords: | banking access; institutional trust; financial inclusion; Central and Eastern Europe; multilevel analysis |
| JEL: | G21 O16 R11 |
| Date: | 2025–07–28 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:128413 |
| By: | Wishnu Badrawani; Citra Amanda; Novi Maryaningsih; Carla Sheila Wulandari |
| Abstract: | Using a panel payment system dataset of thirty-three provinces in Indonesia, we examine the impact of digital payment on the regional economy, considering structural breaks induced by unprecedented events and policies. Digital payments were determined to significantly affect regional income and consumption before and after the identified breakpoint, with the impact greater following the break. Employing a novel method for structural break analysis within interactive effects panel data, we demonstrate that the break in retail payment models is due to COVID-19, and the break in the wholesale payment model is associated with the central bank's payment system policy. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.02119 |
| By: | Xiaolin Yu (Yonsei University); Jin Seo Cho (Yonsei University) |
| Abstract: | The current study examines whether government-led digital finance initiatives promote firm-level digital innovation by leveraging the staggered rollout of China’s Fintech pilot programs as quasi-natural experiments. Our dataset comprises 26, 746 firm-year observations of A-share listed companies from 2009 to 2023. To measure innovation, we develop a text-based indicator derived from the frequency of digital-related keywords in the annual reports of the listed firms. Employing a multi-period difference-in-differences design, we find that designation as a pilot zone increases digital innovation intensity by 0.8225 per thousand report words. These results remain robust across parallel, propensity score matching, placebo, and robustness tests. Mediation analysis reveals that the part of the effect is attributable to increased R&D intensity, with the program raising the average R&D-to-sales ratio by 0.24 percentage points. Moreover, program effect is stronger among high-tech firms and those located in Central and Western China, regions characterized by relatively weaker financial and digital infrastructure. |
| Keywords: | Difference-in-differences; Fintech pilot programs; digital innovation; R&D investments; firm heterogeneity |
| JEL: | G18 G28 G38 O31 O32 O38 O53 P42 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:yon:wpaper:2025rwp-257 |
| By: | Barbereau, Tom (Dutch Organisation of Applied Scientific Research); , Thijmen |
| Abstract: | Privacy-enhancing and other related digital technologies are marketed as increasing trust within the digital society. They are deployed as means to assert trust in digital transactions and interactions between actors. What this commentary argues is that digital trust is thereby reduced to the product of a technological iteration, insertion, or fix: more encryption ≃ more privacy ≃ more trust. However righteous it may be to foster privacy, the promise to uphold something as uncertain as trust by the use of mathematics and/or statistics alone is short-sighted. Lofty notions like ‘data minimisation’ and ‘privacy-by-design’ rest on deterministic assumptions. We suggest that in reductively appropriating the concept of trust and failing to meet expectations, the consequences of the technification of trust – i.e., the making of trust a product of technê (alone) – are paradoxical in that they actually undermine trust, by centralising power within tech companies. |
| Date: | 2025–07–15 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:7kaxj_v1 |
| By: | Marina Azzimonti; Vincenzo Quadrini |
| Abstract: | The rise of the Digital Economy has the potential to reshape international financial markets and the role of traditional reserve assets such as the US dollar. While the creation of Stablecoins may increase the demand for safe dollar-denominated instruments due to reserve backing requirements, they may also serve as substitutes, reducing the global demand for traditional reserve assets. We develop a multicountry model featuring the US, the rest of the world, and a distinct Digital Economy to quantify the impact of the potential expansion of the digital economy. Our results show that, in the long run, the reserve demand effect dominates the substitution effect, leading to lower US interest rates and greater US foreign borrowing. We also find that the expansion of the Digital Economy increases idiosyncratic consumption volatility in the US, while reducing it in the rest of the world. |
| JEL: | F30 F40 G51 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34066 |
| By: | Dhanashekar Kandaswamy; Ashutosh Sahoo; Akshay SP; Gurukiran S; Parag Paul; Girish G N |
| Abstract: | As decentralized finance (DeFi) evolves, distinguishing between user behaviors - liquidity provision versus active trading - has become vital for risk modeling and on-chain reputation. We propose a behavioral scoring framework for Uniswap that assigns two complementary scores: a Liquidity Provision Score that assesses strategic liquidity contributions, and a Swap Behavior Score that reflects trading intent, volatility exposure, and discipline. The scores are constructed using rule-based blueprints that decompose behavior into volume, frequency, holding time, and withdrawal patterns. To handle edge cases and learn feature interactions, we introduce a deep residual neural network with densely connected skip blocks inspired by the U-Net architecture. We also incorporate pool-level context such as total value locked (TVL), fee tiers, and pool size, allowing the system to differentiate similar user behaviors across pools with varying characteristics. Our framework enables context-aware and scalable DeFi user scoring, supporting improved risk assessment and incentive design. Experiments on Uniswap v3 data show its usefulness for user segmentation and protocol-aligned reputation systems. Although we refer to our metric as zScore, it is independently developed and methodologically different from the cross-protocol system proposed by Udupi et al. Our focus is on role-specific behavioral modeling within Uniswap using blueprint logic and supervised learning. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.20494 |
| By: | Microsoft Copilot; Stephen E. Spear |
| Abstract: | This paper extends (Spear 2003) by replacing human agents with artificial intelligence (AI) entities that derive utility solely from electricity consumption. These AI agents must prepay for electricity using cryptocurrency and the verification of these transactions requires a fixed amount of electricity. As a result the agents must strategically allocate electricity resources between consumption and payment verification. This paper analyzes the equilibrium outcomes of such a system and discusses the implications of AI-driven energy markets. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.14612 |
| By: | Maretha Roseline Syahnie (Department of Economics, Faculty of Economics & Business, Universitas Gadjah Mada); Muhammad Ryan Sanjaya (Department of Economics, Faculty of Economics & Business, Universitas Gadjah Mada) |
| Abstract: | MSMEs, also known as micro, small, and medium-sized enterprises, are the backbone of the economy in developing countries. Empirical studies indicate that SMEs generally face obstacles, particularly in financing. This study focuses on two main aspects: indexing financial inclusion using principal component analysis (PCA), and analyzing credit and financial inclusion using vector autoregression (VAR) for forecasting. Through a two-stage indexing methodology, the study emphasizes the importance of geographical reach in financial inclusion availability compared to demographic reach, with availability being the most crucial dimension compared to accessibility and usage. VAR models and forecasting were developed for the period from March 2012 to July 2022 in Indonesia, incorporating other variables, such as accessto credit, credit risk, and real GDP. The use of VAR demonstrates consistency, accuracy, and reliability in producing predictions that closely approximate reality, providing a critical basis for policymakers. |
| Keywords: | Micro, small, and medium enterprises (MSMEs) financing, principal component analysis (PCA), financial inclusion index, credit, vector autoregression (VAR), forecasting, Indonesia |
| JEL: | C32 E44 G21 O16 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:gme:wpaper:202407007 |
| By: | Sicheng Fu; Fangfang Zhu; Xiangdong Liu |
| Abstract: | This paper investigates the dynamics of risk transmission in cryptocurrency markets and proposes a novel framework for volatility forecasting. The framework uncovers two key empirical facts: the asymmetric amplification of volatility spillovers in both tails, and a structural decoupling between market size and systemic importance. Building on these insights, we develop a state-adaptive volatility forecasting model by extracting time-varying quantile spillover features across different volatility components. These features are embedded into an extended Log-HAR structure, resulting in the SA-Log-HAR model. Empirical results demonstrate that the proposed model outperforms benchmark alternatives in both in-sample fitting and out-of-sample forecasting, particularly in capturing extreme volatility and tail risks with greater robustness and explanatory power. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.22409 |
| By: | Antonino Castelli; Paolo Giudici; Alessandro Piergallini |
| Abstract: | The rapid growth of crypto markets has opened new opportunities for investors, but at the same time exposed them to high volatility. To address the challenge of managing dynamic portfolios in such an environment, this paper presents a practical application of a multi-agent system designed to autonomously construct and evaluate crypto-asset allocations. Using data on daily frequencies of the ten most capitalized cryptocurrencies from 2020 to 2025, we compare two automated investment strategies. These are a static equal weighting strategy and a rolling-window optimization strategy, both implemented to maximize the evaluation metrics of the Modern Portfolio Theory (MPT), such as Expected Return, Sharpe and Sortino ratios, while minimizing volatility. Each step of the process is handled by dedicated agents, integrated through a collaborative architecture in Crew AI. The results show that the dynamic optimization strategy achieves significantly better performance in terms of risk-adjusted returns, both in-sample and out-of-sample. This highlights the benefits of adaptive techniques in portfolio management, particularly in volatile markets such as cryptocurrency markets. The following methodology proposed also demonstrates how multi-agent systems can provide scalable, auditable, and flexible solutions in financial automation. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.20468 |
| By: | Ozili, Peterson K |
| Abstract: | This article presents a literature review of the post-2020 bank non-performing loans (NPLs) research around the world and suggests directions for future research. Using the thematic and bibliometric literature review methodologies, we find that significant NPL research has emerged from the European, Asian, and African regions while fewer research has emerged from the Asia-Pacific, North America, Latin America and Caribbean regions as well as from SAARC and OECD countries. The new NPL determinants in the recent literature are corporate governance, fintech, financial inclusion, country risks, regulatory quality, political risks, shadow banking activity, the COVID-19 pandemic, public/external debt, country risks, real house prices, and the independence of the central bank. The common regional NPL determinants are corruption, GDP, debt, loan growth, inflation, capital adequacy ratio, lending rate, competition, the regulatory environment, and GDP growth. The common theories used in the recent literature to explain the behavior of NPL are agency theory, stakeholder theory, information asymmetry theory, and moral hazard theory while the common empirical methodologies used are the panel regression and system GMM regression methods. The implication is that financial regulators, bank supervisors and banking scholars should pay attention to the new emerging determinants of NPL. They should also understand the effect of NPL on financial/banking stability so that safeguards can be put in place to minimise the adverse effect of non-performing loans. More research is needed to provide insights into this area. |
| Keywords: | Banks, NPL, non-performing loans, research, determinants, literature review, world |
| JEL: | G21 G28 G29 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125217 |
| By: | Iñaki Aldasoro; Jon Frost; Sang Hyuk Lim; Fernando Perez-Cruz; Hyun Song Shin |
| Abstract: | Existing anti-money laundering (AML) approaches relying on trusted intermediaries have limited effectiveness with decentralised record-keeping in permissionless public blockchains. The public transaction history on blockchains can enable AML and other compliance efforts, such as FX regulations, by leveraging the provenance and history of any particular unit or balance of a cryptoasset, including stablecoins. An AML compliance score based on the likelihood that a particular cryptoasset unit or balance is linked with illicit activity may be referenced at points of contact with the banking system ("off-ramps"), preventing inflows of the proceeds of illicit activity and supporting a culture of "duty of care" among crypto market participants. |
| Date: | 2025–08–13 |
| URL: | https://d.repec.org/n?u=RePEc:bis:bisblt:111 |
| By: | Mikel Bedayo (BANCO DE ESPAÑA); Eva Valdeolivas (BANCO DE ESPAÑA); Carlos Pérez |
| Abstract: | The paper provides an in-depth analysis of the development of and stabilizing factors behind foreign claims for international banking groups. It focuses on the headquarters locations of the 76 banking groups that participated in the assessment exercise for global systemically important banks at the end of 2020, examining the behavior of their banking systems’ foreign claims (assets) from 2000 to 2022. The study finds that during systemic crises, banking systems with a higher reliance on local claims in local currency (claims booked by foreign branches or subsidiaries vis-à-vis their own residents in the country’s currency) experience a significantly smaller decline in foreign claims. Specifically, a one standard deviation increase in the ratio of local claims in local currency to foreign claims reduces the decline in foreign claims by 0.11 standard deviations during a crisis. Additionally, the paper provides evidence that a high proportion of local claims in local currency mitigates the variation in foreign claims when the country hosting the banking system’s headquarters is experiencing economic growth or stock market volatility. |
| Keywords: | : foreign claims, local claims in local currency, systemic crises, BIS CBS |
| JEL: | F21 F23 F44 G15 G21 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2447 |
| By: | Atta Ul Mustafa |
| Abstract: | This study develops a conceptual simulation model for a tokenized recycling incentive system that integrates blockchain infrastructure, market-driven pricing, behavioral economics, and carbon credit mechanisms. The model aims to address the limitations of traditional recycling systems, which often rely on static government subsidies and fail to generate sustained public participation. By introducing dynamic token values linked to real-world supply and demand conditions, as well as incorporating non-monetary behavioral drivers (e.g., social norms, reputational incentives), the framework creates a dual-incentive structure that can adapt over time. The model uses Monte Carlo simulations to estimate outcomes under a range of scenarios involving operational costs, carbon pricing, token volatility, and behavioral adoption rates. Due to the absence of real-world implementations of such integrated blockchain-based recycling systems, the paper remains theoretical and simulation-based. It is intended as a prototype framework for future policy experimentation and pilot projects. The model provides insights for policymakers, urban planners, and technology developers aiming to explore decentralized and market-responsive solutions to sustainable waste management. Future work should focus on validating the model through field trials or behavioral experiments. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.19901 |
| By: | Simon Brown; Leonardo Bautista-Gomez |
| Abstract: | There have been several studies into measuring the level of decentralization in Ethereum through applying various indices to indicate the relative dominance of entities in different domains in the ecosystem. However, these indices do not capture any correlation between those different entities, that could potentially make them the subject of external coercion, or covert collusion. We propose an index that measures the relative dominance of entities based on the application of correlation factors. We posit that this approach produces a more nuanced and accurate index of decentralization. |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2404.02164 |
| By: | V. I. Danilov |
| Abstract: | In 1962, Gale and Shapley \cite{GS} introduced the concept of stable marriages and proved their existence. Since then, the statement of the stability problem has been highly generalized. And a lot of proofs has emerged for the existence in these more general statements. It's time to review them and identify the similarities and differences. First, we will briefly discuss the classical case, because the existence proofs in the general case grew out of it. Or rather, from the idea of "deferred acceptance". When the best of the proposed contracts is temporarily retained until a better offer is received. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.12721 |