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Systems
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Resilience and Systemic Risk in Interconnected Financial Systems
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Resilience and Systemic Risk in Interconnected Financial Systems

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Practice in Social Science".

Deadline for manuscript submissions: 27 November 2026 | Viewed by 1423

Editors

Dr. Ivana Podhorska

E-Mail Website
Guest Editor
Department of Economics, Faculty of Operation and Economics of Trasport and Communications, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia
Interests: financial management; financial analysis; accounting; market value; goodwill; corporate finance
Dr. Roman Blazek

E-Mail Website
Guest Editor
Department of Economics, Faculty of Operation and Economics of Trasport and Communications, University of Zilina, Univerzitna 1, 010 26 Zilina, Slovakia
Interests: financial management; investment management; financial analysis; corporate finance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Complex financial systems consist of highly interconnected networks of institutions, markets, instruments, and heterogeneous agents characterized by nonlinear dynamics, feedback mechanisms, and emergent behavior. While globalization, financial innovation, and digitalization have enhanced the efficiency of capital allocation and financial intermediation, they have simultaneously increased structural complexity and interdependence, thereby amplifying systemic vulnerabilities. Evidence from recent financial crises demonstrates that localized shocks can propagate rapidly through financial networks, leading to systemic disruptions with significant economic and societal consequences.

This Special Issue aims to advance the understanding of the structure, dynamics, and resilience of complex financial systems from a systems-based perspective. It welcomes contributions employing methods from systems theory, network science, complex adaptive systems, and computational, data-driven, and agent-based modeling. Attention is devoted to the identification of structural sources of systemic risk, mechanisms of risk transmission and contagion, and the development of quantitative indicators and tools for monitoring and mitigating systemic instability. The topic is well aligned with the scope of Systems, as it emphasizes interdisciplinary approaches, holistic system-level analysis, and the integration of theory, empirical evidence, and modeling. By bringing together researchers from economics, finance, systems science, and related disciplines, this Special Issue seeks to deepen insights into the robustness, adaptability, and stability of modern financial systems under conditions of uncertainty and increasing complexity.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Structure and organization of complex financial systems and financial networks;
  • Systemic risk, financial stability, and systemic vulnerabilities;
  • Risk transmission, contagion, and interconnectedness in financial systems;
  • Nonlinear dynamics, feedback mechanisms, and emergent behavior in financial markets;
  • Systems-based modeling and analysis of financial systems;
  • Resilience, robustness, and adaptive behavior of financial systems;
  • Interactions between financial systems and the broader economic system.

We look forward to receiving your contributions.

Dr. Ivana Podhorska
Dr. Roman Blazek
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

  • complex financial systems
  • systemic risk
  • financial stability
  • financial markets
  • financial networks
  • risk transmission
  • macroprudential regulation
  • economic interdependence

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Published Papers (3 papers)

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22 pages, 949 KB  
Article
Mapping Systemic Contagion of Consumer Sentiment Shocks Across National Financial Markets: A Network Analysis of Interconnected Socio-Economic Systems
by Abdülkadir Öztürk, Hasan Tutar, Kamer Ilgın Çakıroğlu, Musa Gün and Arzu Demirci
Systems 2026, 14(8), 950; https://doi.org/10.3390/systems14080950 - 6 Aug 2026
Abstract
Consumer sentiment shocks rarely remain confined to their economy of origin. Adopting a systems-thinking perspective, this study treats the equity markets of thirteen advanced economies as one interconnected socio-technical system, bounded by its environment. It maps how unexpected shifts in consumer confidence propagate [...] Read more.
Consumer sentiment shocks rarely remain confined to their economy of origin. Adopting a systems-thinking perspective, this study treats the equity markets of thirteen advanced economies as one interconnected socio-technical system, bounded by its environment. It maps how unexpected shifts in consumer confidence propagate across it between 2015 and 2025. Rather than isolating a single channel, the analysis examines the system as a whole, where a social subsystem of household sentiment interacts with a technical subsystem of market infrastructure. Sentiment shocks are identified as the unexpected component of the OECD Composite Consumer Confidence Index, and the dependency structure linking markets is estimated through return-based networks. The analysis combines the Diebold-Yılmaz connectedness framework, Granger-causal contagion testing, network centrality measures, and panel estimation with cross-sectionally consistent standard errors. Total connectedness reaches 81.6 percent, confirming a densely integrated system in which the Euro-area core acts as the principal return transmitter; sentiment-shock contagion, once corrected for multiple testing, is sparse rather than pervasive. A small set of economies occupies structurally central positions, yet the small-sample centrality diagnostic provides no robust evidence that threshold-network centrality predicts VAR-based net spillover roles. The findings refine the standard assumption that central nodes are necessarily the main propagators of systemic disturbance and offer concrete guidance for cross-border financial monitoring. This guidance is structural rather than a real-time monitoring signal since it derives from a full sample rather than a rolling or live analysis. Full article
(This article belongs to the Special Issue Resilience and Systemic Risk in Interconnected Financial Systems)
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36 pages, 1959 KB  
Article
Corporate Loan Default Prediction in the Slovak Banking Context: An Interpretable and Ensemble CRISP-DM Pipeline for Credit Risk Assessment
by Lucia Duricova and Veronika Labosova
Systems 2026, 14(7), 738; https://doi.org/10.3390/systems14070738 - 25 Jun 2026
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Abstract
In bank-dominated financial systems, the accumulation of non-performing loans is a recognised source of systemic vulnerability, as correlated corporate defaults can erode bank capital, impair liquidity, and propagate stress across interconnected portfolios. Firm-level default detection thus constitutes a microprudential foundation of macroprudential stability: [...] Read more.
In bank-dominated financial systems, the accumulation of non-performing loans is a recognised source of systemic vulnerability, as correlated corporate defaults can erode bank capital, impair liquidity, and propagate stress across interconnected portfolios. Firm-level default detection thus constitutes a microprudential foundation of macroprudential stability: the reliable early identification of risky borrowers reduces both individual credit losses and the aggregate exposures that drive system-level fragility. Yet the use of structured data-mining pipelines for this task remains underexplored in Central and Eastern Europe. This study applies the CRISP-DM methodology to predict corporate loan default using data on 302 Slovak corporate borrowers, combining financial ratios from publicly available financial statements with selected company and loan-related information from internal bank records. Seven individual classifiers were developed and compared: decision trees (CART, CHAID, C5.0), logistic regression, discriminant analysis, and neural networks (MLP, RBF), together with a stacked ensemble based on their outputs. Model performance was evaluated using sensitivity, overall classification accuracy, and area under the ROC curve (AUC), with sensitivity treated as the primary criterion because of the asymmetric costs of misclassification in credit risk assessment. The results confirm that historical firm-level information provides a reliable basis for default prediction, with tree-based models consistently outperforming statistical and neural network approaches. The stacked ensemble achieved the strongest overall performance, whereas C5.0 and CHAID showed that interpretable classifiers can also deliver competitive predictive accuracy. A champion–challenger deployment architecture is proposed, in which the ensemble serves as the performance-oriented champion and interpretable models act as challengers; this arrangement contributes to the operational resilience of the credit-risk assessment process and aligns with macroprudential expectations of model governance, auditability, and explainability. The study offers a replicable methodological framework for integrating data-driven decision support into credit evaluation in comparable banking settings. Full article
(This article belongs to the Special Issue Resilience and Systemic Risk in Interconnected Financial Systems)
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26 pages, 1663 KB  
Systematic Review
AI Adoption in Local Government: Productivity, Systemic Risk, and Institutional Resilience: Evidence from a PRISMA 2020 Review
by Abayomi Ogunrinde and Carmen De-Pablos-Heredero
Systems 2026, 14(6), 671; https://doi.org/10.3390/systems14060671 - 11 Jun 2026
Viewed by 489
Abstract
Artificial intelligence (AI) is becoming increasingly embedded in the digital infrastructure of local government, creating new opportunities to improve public sector productivity while also influencing systemic risk and organisational resilience across interconnected public systems. As municipalities adopt AI to automate, support, and transform [...] Read more.
Artificial intelligence (AI) is becoming increasingly embedded in the digital infrastructure of local government, creating new opportunities to improve public sector productivity while also influencing systemic risk and organisational resilience across interconnected public systems. As municipalities adopt AI to automate, support, and transform administrative processes, organisational performance becomes more dependent on the reliability of algorithms, the quality of data, effective governance, and coordination among public institutions. These growing interconnections create new vulnerabilities that can spread across public service networks, yet evidence on the productivity, risk, and resilience implications of AI adoption remains fragmented and dispersed across different fields of research. This study develops an integrative conceptual framework that examines the relationship between AI adoption, public sector productivity, systemic risk, and organisational resilience within interconnected sociotechnical systems. Drawing on insights from productivity economics, systems theory, and public governance, the framework positions total factor productivity (TFP) within a broader public value and risk governance perspective. Using the PRISMA 2020 methodology, the study systematically reviews 68 peer reviewed empirical studies published between 2015 and 2025, assessing productivity outcomes, methodological quality, effect sizes, and contextual factors relevant to local government and networked public administration. The findings show that productivity gains associated with AI are strongly influenced by organisational readiness, including digital maturity, workforce capabilities, governance quality, and institutional coordination. While AI has the potential to improve operational efficiency and strengthen adaptive capacity, inadequate readiness can increase systemic risks arising from algorithmic opacity, cybersecurity challenges, data dependence, coordination failures, and disruptions that may spread across interconnected administrative systems. The review also highlights that resilience depends on the ability of public organisations to anticipate, absorb, adapt to, and recover from AI-related disruptions while maintaining the continuity and quality of public services. The study contributes to theory by integrating perspectives from productivity economics, public administration, and systemic risk within a sociotechnical systems framework. It contributes empirically through a comprehensive synthesis of evidence on AI and public sector productivity and methodologically through the application of transparent PRISMA 2020 review procedures. From a practical perspective, the study offers a conceptual measurement framework and policy guidance for municipal decision makers seeking to improve productivity while strengthening resilience and reducing systemic risks in increasingly interconnected public governance systems. Full article
(This article belongs to the Special Issue Resilience and Systemic Risk in Interconnected Financial Systems)
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