Andreas Hoepner

Risk Analysis With & of AI: How Deeply Do We Learn With Which Statistical Approach

AI is one of the most addictive trends over the last years but how useful is which type of AI in a finance context? Does narrow or maybe even general Artificial Intelligence present the Holy Grail? Or will Augmented Intelligence be the winning formula for most use cases? Is AI a game of Man vs. Machine (e.g. AlphaGo) or is Kasparov right and AI is all about harmonizing teams of men & machine? Prof. Hoepner does not claim that there is one definite answer to the above questions. Instead, he argues that the nature of the use case is key. Repeated, real-time recognition tasks are highly suited for narrow Artificial intelligence solutions. However, the less repetitive, the more dynamic and the more predictive a use case, the more Augmented Intelligence becomes the viable business solution. In any case, AI will empower humans! It's just not clear which humans will empowered and which role these human will play in the emerging Data Factories of the 21st century.

Dr. Andreas G. F. Hoepner is Professor of Operational Risk, Banking & Finance at the Michael Smurfit Graduate Business School and the Lochlann Quinn School of Business of University College Dublin (UCD). Andreas is also heading the Practical Tools research group of the Mistra Financial Systems (MFS) research consortium, which aims to support Scandinavian and global asset owners with evidence-based tools for investment decision making. Prior to commencing his MISTRA role in March 2016, Andreas served over six years as lead academic advisor to the United Nations supported Principles for Responsible Investment and consulted organisations including the European Commission, the International Finance Corporation (IFC), and the University of Cambridge's Institute for Sustainability Leadership (CISL).

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