Digital transformation and strategic use of artificial in-telligence in the financial sector: a systematic review of recent evidence (2019–2025)

Abstract

The digital transformation of the financial sector has been rapidly accelerated by the strategic integration of artificial intelligence (AI) technologies, which have demonstrated high potential to enhance operational efficiency, customer experience, and decision-making processes. This study presents a systematic review of scientific literature published between 2019 and 2025, aiming to analyze the development and application of AI in banking, insurance, fintech, and investment sectors, while identifying technological patterns, ethical implications, regulatory challenges, and research gaps. The PRISMA 2020 protocol was applied for the selection process, along with thematic and categorical analysis, and tools such as VOSviewer and RobVis for data visualization. The review includes 32 high-impact studies retrieved from major databases such as Scopus, Web of Science, Redalyc, and SpringerOpen. The findings reveal that machine learning, natural language processing (NLP), and deep neural networks are the most widely used technologies, primarily for process automation, fraud detection, and predictive analytics. Significant advances were identified in financial inclusion through intelligent platforms, although challenges remain concerning cybersecurity, algorithmic bias, and the absence of adaptive regulatory frameworks. A predominance of European and Latin American quantitative studies was observed, enabling comparative lessons on implementation. This study contributes to structuring the scattered knowledge on AI in finance and proposes future research lines to promote its ethical and sustainable integration into the global financial system.