<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Journal of Central Banking Theory and Practice

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial...

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

Publié en ligne: 06 sept. 2021

Pages: 41 - 57

Reçu: 04 juil. 2020

Accepté: 27 nov. 2020

DOI: https://doi.org/10.2478/jcbtp-2021-0023

Mots clés
Banking, Risk Management, Artificial Intelligence, Machine Learning, Deep Learning, Big Data Analytics

© 2021 Nenad Milojević et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Publié en ligne: 06 sept. 2021

Pages: 41 - 57

Reçu: 04 juil. 2020

Accepté: 27 nov. 2020

DOI: https://doi.org/10.2478/jcbtp-2021-0023

Mots clésBanking, Risk Management, Artificial Intelligence, Machine Learning, Deep Learning, Big Data Analytics

© 2021 Nenad Milojević et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Banking, Risk Management, Artificial Intelligence, Machine Learning, Deep Learning, Big Data Analytics