Abstract
This survey represents a comprehensive elicitation of perspectives on operational risk (OpRisk) modelling and practice, obtained from practitioners in a wide range of countries and sectors. The survey was developed and executed by two leading organizations in operational risk in the financial industry, the Institute of Operational Risk (IOR) and the Center for Financial Professionals (CeFPro). This academic paper is a more detailed analysis of the industry report jointly created.
The goal of this analysis was to develop an understanding of the dynamic and evolving nature of operational risk management practice from industry practitioners perspectives. We sought out a large cross section of industry sectors with a truly global view of the disciplines responses.
In this regard we were focused on developing a survey that would facilitate a greater understanding of the following core aspects of operational risk practice, both at present as well as with regard to future possible directions: current best practices and approaches to operational risk; tools and skills being applied in practice; the disciplines current status in different regions and sectors; and what directions the discipline will go in future.
The survey was designed by the authors of this manuscript on behalf of the IOR and facilitated and collated by CeFPro.
The goal of this analysis was to develop an understanding of the dynamic and evolving nature of operational risk management practice from industry practitioners perspectives. We sought out a large cross section of industry sectors with a truly global view of the disciplines responses.
In this regard we were focused on developing a survey that would facilitate a greater understanding of the following core aspects of operational risk practice, both at present as well as with regard to future possible directions: current best practices and approaches to operational risk; tools and skills being applied in practice; the disciplines current status in different regions and sectors; and what directions the discipline will go in future.
The survey was designed by the authors of this manuscript on behalf of the IOR and facilitated and collated by CeFPro.
Original language | English |
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Pages (from-to) | 47-88 |
Number of pages | 42 |
Journal | Journal of Operational Risk |
Volume | 13 |
Issue number | 4 |
Early online date | 7 Dec 2018 |
DOIs | |
Publication status | Published - Dec 2018 |
Keywords
- Operational risk
- Risk Management
- machine learning
- clustering