Prospects of Artificial Intelligence and Machine Learning Application in Banking Risk Management

Nenad Milojević () and Srdjan Redzepagic ()
Additional contact information
Nenad Milojević: Mirabank a.d. Belgrade, Republic of Serbia
Srdjan Redzepagic: Université Côte d'Azur, Graduate School in Economics and Management, Nice, France

Journal of Central Banking Theory and Practice, 2021, vol. 10, issue 3, 41-57

Abstract: Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The research focus is on artificial intelligence and machine learning potential for further banking risk management improvement. The paper seeks to explore the possibility for successful implementation yet taking into account challenges and problems which might occur as well as potential solutions. Artificial intelligence and machine learning have potential to support the mitigation measures for the contemporary global economic and financial challenges, including those caused by the COVID-19 crisis. The main focus in this paper is on credit risk management, but also on analysing artificial intelligence and machine learning application in other risk management areas. It is concluded that a measured and well-prepared further application of artificial intelligence, machine learning, deep learning and big data analytics can have further positive impact, especially on the following risk management areas: credit, market, liquidity, operational risk, and other related areas.

Keywords: Banking; Risk Management; Artificial Intelligence; Machine Learning; Deep Learning; Big Data Analytics. (search for similar items in EconPapers)
JEL-codes: C40 C45 C53 G17 G21 G28 G32 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.cbcg.me/repec/cbk/journl/vol10no3-3.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cbk:journl:v:10:y:2021:i:3:p:41-57

Access Statistics for this article

More articles in Journal of Central Banking Theory and Practice from Central bank of Montenegro Contact information at EDIRC.
Bibliographic data for series maintained by ().