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Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Journal of Central Banking Theory and Practice [ISSN:] 2336-9205 [Volume:] 10 [Issue:] 3 [Year:] 2021 [Pages:] 41-57
Verlag: 
Sciendo, Warsaw
Zusammenfassung: 
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.
Schlagwörter: 
Banking
Risk Management
Artificial Intelligence
Machine Learning
Deep Learning
Big Data Analytics
JEL: 
C40
C45
C53
G17
G21
G28
G32
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Dokumentart: 
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