Using Big Data and Predictive Analytics for Informed Decision-Making in Investment Banking

Abstract: The objective of this research is to analyze the significance of big data and predictive analytics through a thorough literature review within investment banking. We look further into how investment banks use these technologies for risk control, market forecasting, managing clients’ portfolios and preventing fraud. The problem sets out implementations at large institutions and considers gaps in the market for such implementations including data quality constraints, technology limitations, regulation issues, and skills gap. The evidence shows that although there are challenges with implementation, the broad use of big data and predictive analytics improves the effectiveness and efficiency of decision-making processes in investment banking. The paper provides a vision of further development of the market in AI technologies adoption in that area of research and practice.

Keywords: Big data analytics, predictive analytics, investment banking, risk management, machine learning, artificial intelligence