Artificial Intelligence in the Financial Sector: Trends, Challenges, and Practices (Scientia Generalis)

Summary

• A Systematic Literature Review (SLR) based on the PRISMA protocol analyzed 59 articles published between 1996 and 2024 to map AI applications in the financial sector [p.1].p.1
• The potential economic impact of AI adoption in the financial sector is estimated at more than €11 billion by 2030 [p.1].p.1
• The initial search identified 3.140 articles across Scopus and Web of Science, which were refined to 189 unique articles and a final selection of 59 studies [p.3].p.3
• Lexical text analysis classified 89,15% of the unit context elements into 6 main thematic classes representing distinct areas of AI implementation [p.4].p.4
• Academic interest in AI within finance accelerated sharply after 2021, accounting for 78% of all analyzed publications (46 articles) [p.6].p.6
• The analyzed literature spans authors across 32 countries, with the United States, India, China, and the United Kingdom generating over 38% of publications [p.7].p.7

Key insights

1. The European Parliament reports that AI application could add over €11 billion to the global economy by 2030 [p.2].p.2
2. Academic literature on AI in finance shows concentrated recent growth, with 78% of selected articles published after 2021 [p.6].p.6
3. Technological innovation driven by fintechs (Class 1) constitutes 15,70% of the literature, highlighting process automation and operational cost reduction [p.9].p.9