Financial inclusion strategies, technology, and risk management: emerging trends and global perspectives

Closes:
Submissions Open on 1st September 2026

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Introduction

The conventional ways in which risk arises, spreads, and intensifies are changing due to phenomena such as climate change, financial digitalisation, extensive data use, and the development of new financial ecosystems. The convergence of data-driven methodologies with sustainable finance has ushered in a new era of transformative potential (de Oliveira et al., 2023; Saqib et al., 2023; Singh et al., 2023). As a result, these changes pose serious difficulties for supervision, financial stability, and macroprudential policy design.

The identification, assessment, and monitoring of climate, environmental, and operational risks have improved greatly thanks to the use of cutting-edge technologies such as satellite systems, big data analytics, artificial intelligence (AI), and machine learning (Venturini, 2022). Large volumes of data from various sources can be gathered and analysed thanks to these technologies. Data generated by data centres, manufacturing machinery, satellites, digital gadgets, and communication infrastructures such as 5G networks and internet of things (IoT) systems are a few examples. Machine-generated technology system (MTS) data is a common term used to describe such extensive, technologically enabled data sets (Usmani et al., 2024).

However, at the same time, these innovations have brought with them new risks associated with technology, modelling, cybersecurity, and governance, as well as a growing dependence on critical infrastructures. The effective integration of these advanced technologies is crucial to avoid mismatches in asset valuation, financial instability, and disorderly sustainable transitions.
Sustainable finance and data-driven sustainability are becoming more popular as instruments for long-term risk management and effective capital reallocation in this era of rapid technological advancement. However, the quality and comparability of environmental, social, and governance (ESG) data, the potential for greenwashing, and the genuine effectiveness of these tools in reducing systemic risks are still issues. Likewise, financial inclusion and the digitalisation of access to financial services are trends that play a fundamental role in strengthening the resilience of the financial system by broadening the base of intermediation and reducing the vulnerability of households and firms to economic shocks. To establish a more integrated framework for the economy, intentional economic inclusion is fundamental. In this process, green finance and a green financial system are vital mechanisms for generating and channelling the financial resources required to replenish the natural resource base and accelerate human resource development (van Niekerk, 2024).

In this environment, new financial ecosystems are developing. Fintech has evolved into a core component of 21st-century green finance. In advanced economies, it institutionalises sustainability through enhanced transparency and efficiency, while, in emerging markets, it promotes financial inclusion by expanding access to sustainable finance (Chien et al., 2025).
For instance, decentralised finance (DeFi) and regenerative finance (ReFi) offer opportunities to increase the effectiveness and alignment of financial flows with social and environmental goals. However, they also raise challenges associated with governance, regulation, investor protection, and financial stability.

The intersection of AI technologies such as large language models (LLMs) with blockchain can create new scenarios for information access, processing, and decision making. For example, it can support the classification of crypto-assets, helping investors, policymakers, and researchers perform the difficult task of understanding and comparing digital assets (López-Cabarcos et al., 2026).

This Call for Papers invites the submission of theoretical and empirical contributions that adopt a financial and risk management perspective to analyse the challenges and opportunities associated with these transformation processes. Submissions with implications for financial stability, prudential supervision, and the design of public policies are particularly encouraged.

List of Topic Areas

  • The use of satellite and alternative data in financial risk assessment
  • Financial technologies, artificial intelligence, and emerging risks
  • Technological, modelling, and cybersecurity risks in the financial system
  • Sustainable finance, capital allocation, and systemic risk
  • Financial inclusion, digitalisation, and resilience to economic shocks
  • Decentralised finance (DeFi) and risks to financial stability
  • Regenerative finance (ReFi) and long-term risk management
  • Blockchain, tokenisation, and traceability in sustainability and green finance projects
  • Regulatory and supervisory frameworks for sustainable finance, fintech, decentralised finance (DeFi), and regenerative finance (ReFi)
  • Applications of big data, artificial intelligence, and machine learning in sustainable finance
  • Supervision, regulation, and macroprudential policies in response to emerging risks.

Guest Editor

Juan Piñeiro Chousa; Santiago de Compostela University; Spain; j.pineiro@usc.es

Submissions Information

Submissions are made using ScholarOne Manuscripts. Author guidelines must be strictly followed.

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Author Guidelines

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”. Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key Deadlines

Opening date for manuscripts submissions: 1st September 2026

Closing date for manuscripts submission: 31st December 2026

References

Chien, F., Zhang, Y and Sadiq, M. (2025). “Fintech Innovation in Green Finance: A Disruptive Force or a Complementary Tool?” International Review of Economics and Finance 104: 104658. https://doi.org/10.1016/J.IREF.2025.104658.

de Oliveira, R. T., Ghobakhloo, M., & Figueira, S. (2023). Industry 4.0 towards social and environmental sustainability in multinationals: Enabling circular economy, organizational social practices, and corporate purpose. Journal of Cleaner Production, 139712.

López-Cabarcos MÁ, González López I, Pérez-Pérez A, Piñeiro-Chousa J. (2026). Managing cryptocurrencies: a decision-oriented classification. Management Decision. https://doi.org/10.1108/MD-05-2025-1460

Saqib, N., Mahmood, H., Murshed, M., Duran, I. A., & Douissa, I. B. (2023). Harnessing digital solutions for sustainable development: a quantile-based framework for designing an SDG framework for green transition. Environmental Science and Pollution Research, 30(51), 110851-110868.

Singh, S., Rajest, S. S., Hadoussa, S., Obaid, A. J., & Regin, R. (Eds.). (2023). Data-driven decision making for long-term business success. IGI Global. 
van Niekerk, A. J. (2024). Economic Inclusion: Green Finance and the SDGs. Sustainability, 16(3), 1128. https://doi.org/10.3390/su16031128

Venturini, A. (2022). Climate change, risk factors and stock returns: A review of the literature. International Review of Financial Analysis, 79, 101934. Doi:10.1016/j.irfa.2021.101934

Usmani, U. A., Abdul Aziz, I., Jaafar, J. & Watada J. (2024). Deep learning for anomaly detection in time-series data: An analysis of techniques, review of applications, and guidelines for future research. IEEE Access, 12, 174564–174590. doi:10.1109/ACCESS.2024.3495819