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Article
Publication date: 1 February 2004

KJETIL HØYLAND, ERIK RANBERG and STEIN W. WALLACE

Enterprise risk management has been defined as the strategy that aligns the firm's business with the risk factors of its environment in the pursuit of strategic objectives…

89

Abstract

Enterprise risk management has been defined as the strategy that aligns the firm's business with the risk factors of its environment in the pursuit of strategic objectives. Mathematical models will always be part of enterprise risk management. By means of a case study, we discuss why it is necessary to align a model with the organization in order to achieve the desired results. The structure of a model's input must fit with the structure of data collection in the firm, and the output must be consistent with the decision structure. Otherwise, data collection will not be properly taken care of and the results of a model will not find their way to where decisions are made.

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The Journal of Risk Finance, vol. 5 no. 2
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 1 March 2003

KJETIL HØYLAND, ERIK RANBERG and STEIN W. WALLACE

Enterprise risk management is the discipline that governs the integrated management of the aggregate risks for a given firm with consideration for its strategic and organizational…

96

Abstract

Enterprise risk management is the discipline that governs the integrated management of the aggregate risks for a given firm with consideration for its strategic and organizational context. The authors present, in three installments, a case study on developing and implementing a stochastic decision‐support model within an organization. This first installment describes the model.

Details

The Journal of Risk Finance, vol. 4 no. 4
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 1 February 2005

Kjetil Høyland, Erik Ranberg and Stein W. Wallace

Discusses why it is necessary to align a mathematical model with the organization in order to achieve the desired results. The structure of a model's input must fit with the…

453

Abstract

Purpose

Discusses why it is necessary to align a mathematical model with the organization in order to achieve the desired results. The structure of a model's input must fit with the structure of data collection in the firm, and the output must be consistent with the decision structure. Otherwise, data collection will not be properly taken care of and the results of a model will not find their way to where decisions are made. Five years passed from the cooperation first started with the university until the model came on‐line.

Design/methodology/approach

Parts 1 and 2 of this series of papers discussed the stochastic programming model itself and the relationship between the model and the organization. The results are now reported.

Findings

Reports on both organizational and financial results.

Practical implications

Shows that, although a lot of work is needed to implement a complicated stochastic programming model within an organization, it can be done and can lead to good results. However, it takes time to adjust an organization to a new way of thinking, as a model like this can never work unless supported by upper management as well as those who use the model daily.

Originality/value

The main value is to demonstrate in rather large detail how a somewhat complicated model can be developed and used in an organization, which, originally, was not well aligned with the ideas of the modellers.

Details

The Journal of Risk Finance, vol. 6 no. 1
Type: Research Article
ISSN: 1526-5943

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