Business Intelligence (BI) and Big Data are indispensable technologies for banks seeking to improve their competitiveness and customer experience. They enable large volumes of data to be efficiently exploited to enhance the quality of decision-making, performance, and risk management. To map research related to the convergence of BI and Big Data in banking practices, we carried out a systematic literature review (SLR) according to the PRISMA model, presenting works published in the Elsevier Scopus database. The study extracts and analyzes 332 articles published over the last decade, using a bibliometric approach via VOSviewer; more specifically through the analysis parameters, keyword co-occurrence and co-authorship by country. Drawing on the results of the SLR, we have provided an answer to the main research problem based on an up-to-date overview of scientific contributions. There are also contributions from leading countries, influential journals, and key themes, identifying promising research perspectives on the future of BI and Big Data in banking.