• Media type: E-Book
  • Title: AI and Machine Learning for Risk Management
  • Contributor: Aziz, Saqib [Author]; Dowling, Michael M. [Other]
  • imprint: [S.l.]: SSRN, [2019]
  • Extent: 1 Online-Ressource (18 p)
  • Language: English
  • DOI: 10.2139/ssrn.3201337
  • Identifier:
  • Origination:
  • Footnote: In: 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
    Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 14, 2018 erstellt
  • Description: 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
  • Access State: Open Access