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Mapping Research Trends in Cybersecurity and Data Breaches within the Financial Sector: A Bibliometric Perspective

Author

Listed:
  • Nazneen Fatema

    (International Islamic University Chittagong, Bangladesh)

  • Abdullah Mohammed Ibrahim

    (College of Business, Westcliff University, USA)

  • Jesmin Sabnam

    (Independent Researcher, Bangladesh)

  • Abdullah Mohammad Ismail

    (Sunflower Preparatory School, Chittagong, Bangladesh)

Abstract

This bibliometric study maps research trends in cybersecurity and data breaches within the financial sector from 2020 to 2024, analyzing 7355 documents from the Web of Science. The findings reveal a rapidly expanding and interdisciplinary field, driven by the digital transformation of finance, heightened cyber threats, and the impact of global events such as the COVID-19 pandemic. The research landscape has evolved from descriptive, technical studies to sophisticated analyses incorporating network theory, econometrics, and risk management. Most prolific authors and sources, such as IEEE, demonstrate strong international collaboration and significant citation impact, with China, the USA, and the UK leading in citations. Co-citation network analysis identifies three major intellectual clusters: economic modeling of cyber risk, network-based risk propagation, and systemic macro-financial implications of cyberattacks. The study highlights an increasing focus on quantifying the financial and reputational impacts of cyber incidents, making research directly relevant to business and regulatory stakeholders. Limitations include reliance on a single database and quantitative methods. Future research directions emphasize the security implications of emerging technologies (e.g., quantum computing, decentralized finance, artificial intelligence), behavioral and cultural aspects of cybersecurity, and systemic regulatory challenges. The field is dynamic, reflecting the financial sector’s evolving risk landscape.

Suggested Citation

Handle: RePEc:epw:comput:v:6:y:2026:i:2:id:10329
DOI: 10.24018/compute.2026.6.2.10329
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