TY  - JOUR
A1  - Milkau, Udo
A1  - Bott, Jürgen
T1  - Active management of operational risk in the regimes of the "unknown": What can machine learning or heuristics deliver?
T2  - Risks
N2  - Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the “unknown unknown.” While machine learning has been tested successfully in the regime of the “known,” heuristics typically provide better results for an active operational risk management (in the sense of forecasting). However, precursors in existing data can open a chance for machine learning to provide early warnings even for the regime of the “unknown unknown.”
KW  - operational risk
KW  - artificial intelligence
KW  - machine learning
KW  - heuristics
KW  - machine reasoning
Y1  - 2018
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/51545
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-515458
SN  - 2227-9091
N1  - © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
VL  - 6
IS  - 41
PB  - MDPI
CY  - Basel
ER  -