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Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience
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Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience

A Special Issue of Systems (ISSN 2079-8954) belonging to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 31 March 2027 | Viewed by 6456

Editors

Dr. João Jungo

E-Mail Website
Guest Editor
Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Department of Economics Management and Industrial Engineering (DEGEIT), University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal
Interests: financial inclusion; financial stability; competitiveness; financial regulation; feasible generalized least squares model; banks; panel data; financial development; economic development; public finance; financial markets
Dr. Mara Madaleno

E-Mail Website
Guest Editor
Research Unit GOVCOPP, Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), Campus Universitario de Santiago, University of Aveiro, 3810-193 Aveiro, Portugal
Interests: financial markets; sustainable finance; energy finance; financial economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue seeks to reignite the debate on the stability of the financial system, highlighting how its dynamics and complexity increase systemic risk. By intermediating resources between economic agents, the financial system creates a network of interdependencies between them. As this network expands, complexity increases, and it becomes more difficult to predict the factors that affect stability. In addition, the structure of the financial system, composed of banking, capital markets, insurance, pension funds, and payment subsystems, reinforces this interconnection and requires an integrated understanding to ensure its efficient functioning.

Complex systems theory provides a useful framework for understanding this reality, arguing that strong interconnections between agents can generate emergent behaviors, an absence of linear cause-and-effect relationships, and limited predictability. On the other hand, due to the strong correlation between actors in the financial system, small shocks are easily amplified and quickly spread. Financial innovation results from the dynamics of the system and promotes financial inclusion, but it also increases complexity by changing the patterns of interaction between agents. Thus, our aim is to collate articles that address the dynamics and complexities of the financial system and suggest policies capable of predicting and mitigating systemic risk and fostering financial resilience and stability.

For this Special Issue, original research articles and reviews are welcome to be submitted. Research areas may include, but are not limited to, the following:

  • Dynamics and complexity of financial systems;
  • Interconnectivity, contagion, and risk transmission;
  • Credit risk;
  • Systemic risk and financial stability;
  • Macroprudential policies and financial supervision;
  • Financial innovation and digital transformation;
  • Central bank digital currencies (CBDCs) and crypto-assets;
  • Financial inclusion and economic development;
  • Financial literacy and behavior of economic agents;
  • Financial governance and institutional quality;
  • Corruption, ethics, and integrity in the financial system;
  • Financial resilience and response to external shocks;
  • Sustainability, green finance, and economic transition;
  • Models for forecasting and monitoring financial crises;
  • Contribution of financial institutions to long-term stability;
  • Financial regulation in complex environments;
  • Technological infrastructures and cybersecurity;
  • Banking competition and market structure;
  • International financial and geopolitical integration;
  • Digital platforms and electronic payments;
  • Behavioral finance and decision-making.

We look forward to receiving your contributions.

Dr. João Jungo
Dr. Mara Madaleno
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • financial stability
  • systemic risk
  • financial complexity
  • interdependence
  • financial inclusion
  • financial innovation
  • financial intermediation
  • complex systems
  • financial contagion
  • financial regulation
  • prudential supervision
  • emerging markets
  • institutional resilience

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Published Papers (7 papers)

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Research

27 pages, 994 KB  
Article
Does Machine Learning Outperform Simple Investment Rules? Comparative Performance and Strategy Robustness in European Equity Markets
by Flavia Mirela Barna, Anca Țăranu and Grațiela Georgiana Noja
Systems 2026, 14(9), 1140; https://doi.org/10.3390/systems14091140 - 11 Sep 2026
Abstract
Artificial intelligence is increasingly used in asset management, although evidence that greater model complexity consistently improves investment performance remains limited. This study examines whether machine-learning methods generate incremental value in European equity selection beyond transparent investment rules. The analysis used 562 eligible monthly [...] Read more.
Artificial intelligence is increasingly used in asset management, although evidence that greater model complexity consistently improves investment performance remains limited. This study examines whether machine-learning methods generate incremental value in European equity selection beyond transparent investment rules. The analysis used 562 eligible monthly price series drawn from the March 2026 STOXX Europe 600 constituents and applied retrospectively as a common ex post reference universe. The models were trained on observations from January 2011 to December 2020 and evaluated out of sample using signals formed from January 2021 to March 2026, with corresponding portfolio returns realized from February 2021 to April 2026. Logistic regression, random forest, XGBoost, and an equal-probability ensemble are compared with momentum, low-volatility, and equal-weight strategies under common portfolio-construction rules. Logistic regression recorded the strongest classification results and the highest gross cumulative portfolio return. The transparent momentum strategy recorded the highest observed Sharpe ratio and substantially lower target-weight turnover, while the three-model ensemble underperformed both logistic regression and momentum. Newey–West inference did not establish a statistically significant difference in mean monthly returns between logistic regression and momentum. The results indicate that additional algorithmic complexity did not generate incremental investment value under the restricted technical information set and portfolio framework considered. The findings support evaluating model complexity jointly through predictive quality, gross performance, statistical uncertainty, implementation sensitivity, interpretability, and governance requirements. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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23 pages, 1822 KB  
Article
Digital Payment Ecosystems as Socio-Technical Systems: Digital-Infrastructure-Based Fintech Diffusion, Regulatory Coupling, and Private-Sector Credit Exposure in OECD Economies
by Musa Gün, Hasan Tutar, Haydar Karadağ and Hakan Güneş
Systems 2026, 14(8), 960; https://doi.org/10.3390/systems14080960 - 7 Aug 2026
Viewed by 317
Abstract
This study examines whether the diffusion of financial technology expands or constrains private-sector credit across OECD economies, and whether regulatory quality conditions that relationship. Fintech diffusion is operationalized through a composite index of general digital-infrastructure indicators (internet use, mobile subscriptions, and ICT-service exports); [...] Read more.
This study examines whether the diffusion of financial technology expands or constrains private-sector credit across OECD economies, and whether regulatory quality conditions that relationship. Fintech diffusion is operationalized through a composite index of general digital-infrastructure indicators (internet use, mobile subscriptions, and ICT-service exports); this index proxies the broader digitalization environment rather than measuring payment-platform use, embedded credit, or digital lending directly. It conceptualizes digital payment ecosystems as complex financial systems in which technological diffusion, regulatory capacity, and credit dynamics co-evolve through feedback mechanisms. The policy discourse often assumes that digital financial inclusion automatically enhances resilience, yet evidence on credit expansion and systemic exposure remains contested. Using an unbalanced panel of 37 OECD economies from 2015 to 2024, comprising 356 observations, the analysis employs Driscoll–Kraay standard errors to address cross-sectional dependence within a common-slope two-way fixed-effects framework, along with panel quantile regression at the 10th, 50th, and 90th percentiles and Dumitrescu–Hurlin causality testing. Fintech diffusion is positively and statistically significantly associated with private-sector credit exposure, and this association is robust to a two-way fixed-effects specification. The quantile estimates show that the association is present at these selected points of the conditional distribution and strongest at its lower and upper tails, a pattern consistent with complex-adaptive-system dynamics in which effects vary across system states. Contrary to the negative-feedback expectation, the interaction between fintech diffusion and regulatory quality is positive, consistent with high-quality institutions enabling rather than restraining the translation of fintech into credit, though the observational design identifies this interaction rather than the mechanism producing it. The findings therefore shift the discussion from fintech as a stand-alone inclusion tool to fintech as a system-shaping force with implications for institutional resilience, macroprudential supervision, and systemic credit exposure. Because domestic credit to the private sector aggregates household and corporate lending, the policy implication below is framed at this aggregate level: digital payment infrastructure should be governed jointly with consumer protection, credit reporting, and financial-resilience mechanisms rather than promoted as a neutral technological upgrade. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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27 pages, 1282 KB  
Article
How Stablecoins Reshape Interactions Within a Fragmented USD-Access System: Evidence from a Time-Frequency TVP-VAR Connectedness Model
by Qiqi Gu, Ying Liu, Junda Wu and Xuan Zhu
Systems 2026, 14(8), 932; https://doi.org/10.3390/systems14080932 - 2 Aug 2026
Viewed by 365
Abstract
This paper examines return connectedness among four channels for obtaining U.S.-dollar exposure in Argentina: the official USD/ARS rate, the informal Blue Dollar rate, and USDT/ARS prices on Binance and Bitso. We use 669 matched-date daily returns and a time-varying parameter VAR connectedness model [...] Read more.
This paper examines return connectedness among four channels for obtaining U.S.-dollar exposure in Argentina: the official USD/ARS rate, the informal Blue Dollar rate, and USDT/ARS prices on Binance and Bitso. We use 669 matched-date daily returns and a time-varying parameter VAR connectedness model with Barunik–Krehlik frequency decomposition. The analysis is descriptive: generalized forecast-error variance shares measure directional dependence within the estimated system but do not identify structural causality, price discovery, or systemic risk. Baseline estimates indicate that total connectedness rises from 43.57% under exchange controls and 45.26% during the crawling-peg period to 64.53% after liberalization. The two stablecoin venues have positive net-connectedness positions in the baseline estimates, while the official rate becomes a net receiver in Periods 2 and 3. Connectedness is concentrated within five- and ten-day horizons, although the share attributed to a strict three-day band is materially lower. Period 3 transmitter signs remain stable in contiguous subsamples, single-venue and aggregate-stablecoin specifications, and a six-variable system augmented with Bitcoin and a broad U.S.-dollar factor. By contrast, Period 2 directional rankings are more sensitive to alternative period boundaries and stablecoin representations and should therefore be interpreted cautiously. Rankings are also less stable in Period 1 and under deliberate one-day shifts in stablecoin closing dates, highlighting the importance of outliers and market synchronization. The results therefore provide conditional evidence on changing return interactions across segmented dollar-access venues rather than causal evidence that one venue drives another. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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32 pages, 9959 KB  
Article
Financial Statement Fraud Risk Analysis Using Fuzzy Logic
by Georgiana Burlacu, Ioan-Bogdan Robu, Adriana Florina Popa and Ionuț Viorel Herghiligiu
Systems 2026, 14(8), 931; https://doi.org/10.3390/systems14080931 - 2 Aug 2026
Viewed by 490
Abstract
As financial markets are characterized by the increasing incidence and complexity of fraudulent activities, generating substantial losses for companies while posing serious risks to potential investors, financial fraud is a constantly debated issue, particularly with regard to its prevention and detection. As classical [...] Read more.
As financial markets are characterized by the increasing incidence and complexity of fraudulent activities, generating substantial losses for companies while posing serious risks to potential investors, financial fraud is a constantly debated issue, particularly with regard to its prevention and detection. As classical methods for detecting financial fraud have proven inefficient and time-consuming, many researchers have turned to artificial-intelligence-based methods. The use of AI-based methods for fraud detection is currently a widely debated topic, particularly regarding fraudulent financial statements. This study aims to determine the extent to which fuzzy logic contributes to financial statement fraud risk assessment. The target population comprises Romanian companies listed on the Bucharest Stock Exchange. Following analysis, a sample of 62 listed companies was selected. The analysis covers the last seven completed financial years (2018–2024). The dependent variable is represented by financial statement fraud risk (FSF), measured using the modified F-score model, under the influence of some independent variables that are defined by a series of financial ratios: return on assets, return on equity, net profit margin, leverage and working capital. Additionally, taking into account the audit opinion type and advanced statistical methods for data analysis, the research results demonstrated the importance of using fuzzy logic in fraud risk assessment by improving the process of detecting fraud in financial statements, based on specific financial ratios and statistical associations between these ratios, as fuzzy rules. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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33 pages, 2634 KB  
Article
Supply Chain Shocks and the Reconfiguration of Green Finance Markets: A Quantile-on-Quantile Connectedness Analysis
by Jian Yao, Junda Wu, Haoyuan Feng and Jiajing Sun
Systems 2026, 14(6), 652; https://doi.org/10.3390/systems14060652 - 6 Jun 2026
Cited by 1 | Viewed by 693
Abstract
Supply chain disruptions have become a major source of macro-financial stress, yet their implications for green finance remain underexplored. This paper investigates the state-dependent connectedness between supply-side bottlenecks and the green finance market, represented by clean energy equities, green bonds, and carbon prices. [...] Read more.
Supply chain disruptions have become a major source of macro-financial stress, yet their implications for green finance remain underexplored. This paper investigates the state-dependent connectedness between supply-side bottlenecks and the green finance market, represented by clean energy equities, green bonds, and carbon prices. Using daily data on regional Supply Bottleneck Indices (SBIs) for China, the United States, and the euro area, we first construct a global Supply Bottleneck Index (GSBI) by principal component analysis and then estimate pairwise quantile-on-quantile connectedness (QQC) between supply bottleneck indicators and each green finance submarket. The results show that connectedness is strongly nonlinear, asymmetric, and time-varying. For the global indicator, connectedness intensifies at both joint and cross-tail quantile combinations, while mid-quantile states exhibit weak coupling. Regional results reveal clear heterogeneity: China and the United States display the strongest connectedness with clean energy equities in extreme upper-tail states, whereas the euro-area indicator is most tightly linked with the carbon market. Across many extreme states, supply bottleneck indicators show positive net connectedness with green finance markets, but green finance markets, especially carbon prices, can dominate the bilateral connectedness relation under calmer or intermediate regimes. Robustness checks based on average and quantile-rank GSBI constructions, a post-2023 subsample, and alternative QQC tuning choices support the tail-dominance pattern. These findings suggest that supply bottlenecks are not uniformly related to all green assets; rather, they are associated with state-dependent changes in the internal connectedness architecture of the green finance system. The paper contributes to the literature on financial connectedness and sustainable finance by showing how a real-economy disturbance is associated with changes in the connectedness and resilience of green financial markets. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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38 pages, 2177 KB  
Article
Digital Financial Inclusion, DeFi Capability, and AI Analytics in Payment Market Infrastructure: Implications for System Resilience and Performance
by Imdadullah Hidayat-ur-Rehman, Sultan Bader Aljehani, Khalid Waleed Ahmed Abdo, Mohammad Nurul Alam and Mohd Shuaib Siddiqui
Systems 2026, 14(5), 577; https://doi.org/10.3390/systems14050577 - 19 May 2026
Viewed by 1440
Abstract
Digital payment and settlement markets operate as interconnected financial systems shaped by institutional, technological, and capability-based elements. This study examines how digital transformation and digital financial inclusion interact within this system to influence Sustainable Digital Payment and Settlement Market Performance (SDPSMP), with DeFi [...] Read more.
Digital payment and settlement markets operate as interconnected financial systems shaped by institutional, technological, and capability-based elements. This study examines how digital transformation and digital financial inclusion interact within this system to influence Sustainable Digital Payment and Settlement Market Performance (SDPSMP), with DeFi adoption capability acting as a structural translation mechanism and AI and big data analytics functioning as adaptive enablers. Integrating the Resource-Based View and Diffusion of Innovation, the study explains why technology diffusion does not consistently produce stable market-level outcomes. Cross-sectional data were collected from 422 professionals in Saudi financial institutions engaged in payment, settlement, and FinTech functions. A dual-stage SEM–ANN approach was employed, using PLS-SEM to test direct, mediating, and moderating effects and Artificial Neural Networks (ANN) to capture nonlinear predictive patterns. Results show that digital transformation and digital financial inclusion enhance DeFi adoption capability and directly improve SDPSMP. DeFi capability partially mediates both relationships. Analytics capability strengthens the effects of inclusion and DeFi capability on system performance but does not moderate the transformation–performance link. ANN findings identify analytics capability and financial inclusion as dominant predictors. The study advances understanding of digital payment markets as complex adaptive systems and provides evidence on how coordinated capability development supports long-term resilience and structural stability. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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19 pages, 797 KB  
Article
Climate Shocks, Stock Price Crash Risk, and Corporate Sustainability: Evidence from China’s Financial System
by Tian Liu and Wei Zhao
Systems 2026, 14(1), 18; https://doi.org/10.3390/systems14010018 - 24 Dec 2025
Cited by 3 | Viewed by 2134
Abstract
Climate shocks are increasingly recognized as systemic stressors that disrupt financial stability and undermine sustainable development. Using a comprehensive panel of Chinese listed firms from 2007 to 2023, this study examines how physical climate shocks propagate through the financial system. Specifically, we investigate [...] Read more.
Climate shocks are increasingly recognized as systemic stressors that disrupt financial stability and undermine sustainable development. Using a comprehensive panel of Chinese listed firms from 2007 to 2023, this study examines how physical climate shocks propagate through the financial system. Specifically, we investigate their impact on elevating stock price crash risk and impairing corporate sustainability. We construct a firm-level physical climate risk indicator by applying machine learning and text analysis to annual reports. The empirical evidence demonstrates that climate shocks significantly increase stock price crash risk, indicating heightened systemic vulnerability within the financial system. Mechanism analysis identifies two key transmission channels linking climate shocks to crash risk: tightened liquidity constraints and diminished risk-taking capacity. Furthermore, we find that firms with stronger green transformation efforts exhibit lower sensitivity to climate-induced crash risk. This highlights the crucial role of green initiatives in enhancing institutional and financial resilience. Additional analyses reveal that the rise in crash risk subsequently weakens corporate sustainable development performance. Overall, these findings provide micro-level evidence of how climate shocks generate asymmetric effects within the financial system. The study concludes with policy implications for strengthening climate resilience, stabilizing capital markets, and advancing sustainability in emerging economies. Full article
(This article belongs to the Special Issue Dynamics of Modern Financial Systems: Inclusion, Complexity, and Institutional Resilience)
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