A cognitive computational model of risk hypothesis generation

Article Abstract:

A risk hypothesis generation model, a computer program for generating risk hypotheses during audit planning, was developed and researched. The risk hypothesis generation model, which is a cognitive computational model, yields the knowledge auditors use to develop risk hypotheses, applications of the knowledge, risk hypotheses' forms, and the risk hypotheses' content. The results of research indicate that auditors examine control, risk, and inherent cues when developing risk hypotheses; place more emphasis on developing causal explanations of potential sources of risk than generating approximations of risk levels; systematically develop risk hypotheses; use both general and specific knowledge; and use quantitative and qualitative knowledge when developing risk hypotheses.

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Discussion of a cognitive computational model of risk hypothesis generation

Article Abstract:

James M. Peters (1990) developed a computer model of the process by which auditors develop risk hypotheses during the audit planning process. Peters' long-term goal is to create an expert computer system or decision aid to help auditors plan audits. While Peters states that the research is based upon a computational cognitive simulation model, the design of the model does not fit traditional parameters. Peters' research gives rise to the question of what part of the audit process really is modelled. The likely answer is that the model is a generic process for solving audit problems.

Peters, James M.

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