Template-Type: ReDIF-Article 1.0

Author-Name: Gergely Lulok
Author-Workplace-Name: Budapest University of Technology and Economics
Author-Email: lulok.gergely@edu.bme.hu
Author-Person: 

Author-Name: Zoltan Sebestyen
Author-Workplace-Name: Budapest University of Technology and Economics
Author-Email: sebestyen.zoltan@gtk.bme.hu
Author-Person:

Title: 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.

Classification-JEL: C10, G21, O33
Keywords: artificial intelligence, banking sector, financial services, trend analysis
Pages: 47-72
Volume: 24
Issue: 2
Year: 2025
File-URL: https://hitelintezetiszemle.mnb.hu/sw/static/file/fer-24-2-st3-lulok-sebestyen.pdf
File-Format: Application/pdf
Handle: RePEc:mnb:finrev:v:24:y:2025:i:2:p:47-72