A Weighted Mean Model for Operational Risk Assessment

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.