Bibliometric Analysis of Digital Innovation in Investment Banking Services and the Effect on Efficiency and Client Satisfaction

Abstract

This study presents a bibliometric analysis of scholarly literature on digital innovation in investment banking, focusing on its impact on operational efficiency and client satisfaction. As the financial services industry undergoes rapid digital transformation, investment banks are increasingly leveraging technologies such as artificial intelligence (AI), blockchain, cloud computing, and big data analytics to streamline operations, reduce costs, and enhance customer experiences. The objective of this research is to systematically evaluate the trends, influential publications, key authors, and collaborative networks in this emerging domain. Using data extracted from the SCOPUS database, the analysis covers publications from 2019 to 2024. The Bibliometrix tool, using Biblioshiny in R, was employed to map co-authorship networks, citation patterns, and keyword co-occurrences. The results reveal a significant surge in publications after 2015, correlating with increased fintech activity and regulatory shifts that promote digital adoption. Key research clusters include artificial intelligence, quality of service, customer satisfaction, machine learning, and fintech. The study highlights a growing academic consensus that digital innovation enhances both back-office efficiency and front-end client engagement. However, it also identifies gaps in empirical studies measuring client satisfaction outcomes.