Latest Trends in the Use of Artificial Intelligence in the Banking Sector

Abstract

The study examines the latest trends in the application of artificial intelligence (AI) in the banking sector, with a focus on bank failure prediction, risk management and customer relationship optimisation. The research is based on a systematic literature search of relevant publications in the Scopus and Web of Science databases, using the PRISMA methodology for source selection and analysis. The results show that Unsupervised Learning Models dominate in bankruptcy prediction and risk analysis, while Natural Language Processing and Deep Learning techniques are mainly focused on improving customer relationships and increasing bank efficiency. The research shows that AI is playing an increasingly important role in banking decision-making, but that the different application areas face different regulatory and ethical challenges. The results underline the importance for financial institutions to improve the transparency and interpretability of AI and to develop adaptive regulatory frameworks to balance innovation and security.