Analyzing the academic discourse on RPA in banking: A bibliometric approach

Abstract

Robotic Process Automation (RPA) in the banking sector has gained significant attention for its potential to improve operational efficiency, accuracy, and customer service by automating repetitive tasks such as transaction processing, compliance checks, and customer inquiries. This bibliometric analysis provides a comprehensive overview of the research landscape on RPA in banking, utilizing data extracted from Scopus. The study follows PRISMA guidelines for document inclusion and exclusion to ensure a robust methodology. Various bibliometric tools, including Biblioshiny, VOSviewer, and Citespace, were employed to conduct a detailed analysis of the field. Key findings highlight trends in annual scientific production, allowing for the identification of the most prolific authors, sources, and documents in the domain. The study also conducts a citation analysis to pinpoint globally influential documents. Furthermore, visualizations such as thematic maps, trend topic analysis, and bibliographic coupling offer insights into the evolving research themes and their interconnectedness. Co-occurrence of keywords, historiography, and coauthorship networks shed light on the collaborative and intellectual structure of the field, while cocitation analysis reveals relationships among leading authors and their influence on the development of RPA in banking. The analysis also uncovers several research gaps, particularly in the underexplored areas of sales and enterprise resource planning. Practical implications for banking institutions include strategies for leveraging RPA to enhance efficiency and competitiveness. In conclusion, this study underscores the growing importance of RPA in banking and offers a blueprint for future research directions, emphasizing the need for interdisciplinary collaboration and further exploration of managerial and technological aspects. In addition to identifying key trends and influential works, the study emphasizes the need for further research into the integration of RPA with emerging technologies such as artificial intelligence and blockchain to optimize banking operations.