AI and Machine Learning for Risk Management
Published as: Aziz, S. and M. Dowling (2019). “Machine Learning and AI for Risk Management”, in T. Lynn, G. Mooney, P. Rosati, and M. Cummins (eds.), Disrupting Finance: FinTech and Strategy in the 21st Century, Palgrave, pp 33-50.
18 Pages Posted: 2 Jul 2018 Last revised: 10 Feb 2019
Date Written: July 14, 2018
We explore how artificial intelligence (AI) and machine learning solutions are transforming risk management. A non-technical overview is first given of the main AI and machine learning techniques of benefit to risk management. Then an analysis, using current practice and empirical evidence, is carried out of the application of these techniques to the risk management fields of credit risk, market risk, operational risk, and compliance (‘RegTech’). We conclude with some thoughts on current limitations and views on how the field is likely to develop in the short- to medium-term. Overall, we present an optimistic picture of the role of AI and machine learning in risk management, but note some practical limitations around suitable data management policies, transparency, and lack of necessary skillsets within firms.
Keywords: AI, Machine Learning, Risk Management, RegTech, Credit Risk, Operational Risk, Market Risk
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