AI and Machine Learning for Risk Management

18 Pages Posted: 2 Jul 2018 Last revised: 25 Jul 2018

See all articles by Saqib Aziz

Saqib Aziz

ESC Rennes School of Business; Université de Rennes 1

Michael M. Dowling

ESC Rennes School of Business

Date Written: July 14, 2018

Abstract

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

Suggested Citation

Aziz, Saqib and Dowling, Michael M., AI and Machine Learning for Risk Management (July 14, 2018). Available at SSRN: https://ssrn.com/abstract=3201337 or http://dx.doi.org/10.2139/ssrn.3201337

Saqib Aziz

ESC Rennes School of Business ( email )

Rue Robert d'arbrissel, 2
Rennes, 35000
France

Université de Rennes 1 ( email )

11 Rue Jean Macé
Rennes, Rennes 35700
France

Michael M. Dowling (Contact Author)

ESC Rennes School of Business ( email )

Rue Robert d'arbrissel, 2
Rennes, 35000
France

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