Abstract
The bibliometric analysis plays a crucial role in understanding the evolution of research trends and knowledge in various fields. This study applies bibliometric analysis to explore the growth of the research paradigm on agility in the fintech literature, using co-citation analysis and bibliographic coupling of selected articles. Based on this bibliometric analysis, the evolution of research on agility in the fintech domain has been prepared, focusing on the literature related to fintech agility between 1984 and 2022. In this study, we also address the limitations of individual analyses from Scopus and Web of Science (WOS) and propose a comprehensive approach by merging the two research databases. The results reveal significant disparities between authors, publication influences, and keyword occurrences between the WOS and merged databases. Our research highlights the importance of combining a database approach in bibliometric studies, providing valuable insights for scholars, researchers, and stakeholders. Finally, the in-depth bibliometric analysis demonstrates the significance of “fintech agility” in the rapidly evolving fintech sector. Financial technology companies' agility, or ability to adapt quickly, is the foundation of their success and innovation.”
Key Terms in this Chapter
Incident Response: The process of detecting, analyzing, and responding to cybersecurity incidents to minimize damage and recover from attacks.
Maturity Model: A framework for evaluating the maturity level of processes within an organization, helping to identify strengths, weaknesses, and areas for improvement.
Automation: The use of technology to perform tasks without human intervention, increasing the efficiency and effectiveness of security operations.
Compliance: Adherence to laws, regulations, standards, and guidelines relevant to cybersecurity and data protection.
SIEM (Security Information and Event Management): A system that collects, aggregates, and analyzes log data from various sources to detect security threats and incidents.
Vulnerability Management: The process of identifying, evaluating, and mitigating vulnerabilities in an organization's IT infrastructure to prevent potential security breaches.
Advanced Analytics: The use of artificial intelligence and machine learning techniques to analyze data and detect anomalies or patterns that indicate potential security threats.
Security Operations Center (SOC): A centralized unit within an organization that continuously monitors, detects, and responds to cybersecurity threats and incidents.
Threat Intelligence: Information about potential or current attacks on an organization's systems, which helps in proactive threat identification and response.
Threat Hunting: The proactive search for threats and vulnerabilities within an organization’s IT environment that may have bypassed existing security measures.