Abstract
This article introduces a new framework for risk assessment. Risk management is evolving from the well-established one-year horizon dominated by the value-at-risk concept into a multi-period risk projection framework. This enables organizations to compare the planned and actual risk situations, thus ensuring risks taken are in line with the long-term risk roadmap. We also include the principle of value driver analysis in this framework and discuss the potential of agent-based modeling within the context of developing value drivers .
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Notes
- 1.
European Market Infrastructure Regulation.
- 2.
More precisely the Dodd–Frank Wall Street Reform and Consumer Protection Act was the US regulatory response to the 2008 global financial crisis.
- 3.
Capital requirements regulation.
- 4.
Capital requirements directive.
- 5.
European Banking Authority.
- 6.
European Central Bank.
- 7.
Federal Deposit Insurance Corporation.
- 8.
Federal Reserve.
- 9.
Financial Accounting Standards Board.
- 10.
Swiss Financial Markets Authority (Eidgenössische Finanzmarktaufsicht).
- 11.
Transversal risk refers to a risk with an impact across multiple risk types (e.g., credit risk or liquidity risk).
- 12.
Daniéle Nouy at a the conference in Frankfurt see also (Deters & Kröner, 2018).
- 13.
We define risk profile as the aggregate and measurable condition of the institution in terms of risk exposure and other key risk indicators established in the organization.
- 14.
ICAAP—Internal Capital Adequacy Assessment Process.
- 15.
ILAAP—Internal Liquidity Adequacy Assessment Process.
- 16.
- 17.
Since the effect unfolds, not through climate change itself, but through regulations based on climate change, it is irrelevant whether or not climate change is a real threat.
- 18.
The debt service coverage ratio (DSCR) is the ratio of cash available for interest and principal payments.
- 19.
The following remarks are not restricted to model parameters but also hold true for market data and transactional data.
References
Deters, J., & Kröner, A. (2018). EZB-Chefaufseherin Danièle Nouy regt Änderungen beim EU-Bankencheck an. Der aktuelle Test liefere für die Finanzaufsicht zu wenige neue Erkenntnisse.
Dombret, A. (2018). Bankenaufsicht im Dialog 2018 - Schriftenreihe zum Bundesbank Symposium, Band 4. Frankfurt: Deutsche Bundesbank.
Li, S., Liermann, V., & Schaudinus, N. (2019). Introduction in machine learning. In V. Liermann & C. Stegmann (Eds.), The impact of digital transformation and fintech on the finance professional. New York: Palgrave Macmillan.
PWC. (2013). Exploring green finance incentives in China—Final report. Shenzhen: PWC.
Taleb, N. N. (2008). The black swan: The impact of the highly improbable. New York: Random House.
Valjanow, S., Enzinger, P., & Dinges, F. (2019). Digital planning—Driver-based planning levaraged by predictive analytics. In V. Lierman & C. Stegmann (Eds.), The impact of digital transformation and fintech on the finance professional. New York: Palgrave Macmillan.
Zadek, S., & Flynn, C. (2013). South-originating green finance: Exploring the potential. Geneva: The Geneva International Finance.
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Liermann, V., Viets, N. (2019). Predictive Risk Management. In: Liermann, V., Stegmann, C. (eds) The Impact of Digital Transformation and FinTech on the Finance Professional. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-23719-6_8
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DOI: https://doi.org/10.1007/978-3-030-23719-6_8
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