A Weighted Mean Model for Operational Risk Assessment

Journal of Law and Financial Management, Vol. 12, No. 1, July 2013

13 Pages Posted: 8 Jun 2013

See all articles by Yundong Huang

Yundong Huang

Murray State University

Murphy Smith

Texas A&M University-Corpus Christi-Department of Accounting

David Durr

Murray State University - College of Business

Date Written: June 7, 2013

Abstract

Assessing operational risk, particularly related to internal control, is increasingly important to business firms. This is especially the case for publicly-traded companies that are engaged in multinational operations, which involve additional complexity and risk. In the United States, for example, the Sarbanes-Oxley Act requires public companies to document adequate internal control in their annual report. However, there is no standard or uniformly accepted solution for internal risk analysis. Several complex methods have been introduced in the academic field. These complex methods, while theoretically sound, may be problematic in practice due to the necessity of sufficient historical data. When insufficient data are available for measuring operational risk, most of the models, which are based on probability theory, do not work. As a consequence, in most companies’ annual reports, the internal risk disclosure is still rather ambiguous and intuitive. In this paper, we will present a simple weighted mean model that can be used for internal risk assessment. This weighted mean model offers an approach that is relatively easy to use and overcomes deficiencies of more complex models. This model can be a viable alternative to empirical or intuitive methods.

Keywords: finance, law

JEL Classification: M40, M41

Suggested Citation

Huang, Yundong and Smith, Murphy and Durr, David Wright, A Weighted Mean Model for Operational Risk Assessment (June 7, 2013). Journal of Law and Financial Management, Vol. 12, No. 1, July 2013. Available at SSRN: https://ssrn.com/abstract=2276284

Yundong Huang (Contact Author)

Murray State University ( email )

351 Business Building
Murray, KY 42071-3314
United States

HOME PAGE: http://yundong-huang.com

Murphy Smith

Texas A&M University-Corpus Christi-Department of Accounting ( email )

6300 Ocean Dr
Corpus Christi, TX 78412
United States

David Wright Durr

Murray State University - College of Business ( email )

351 Business Building
Murray, KY 42071-3314
United States

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