Analytical procedures require that auditors develop and test hypotheses about possible fluctuations in a firm's financial data. Research in psychology suggests that the initial information ambiguity that exists prior to hypothesis generation may affect not only the initial hypothesis set, but also final judgment accuracy. We argue in this paper that information ambiguity can be caused by two primary variables, data sufficiency and data complexity, and examine how these variables affect judgment accuracy during analytical review. Ninety-four staff auditors completed analytical procedures for a company with an error seeded into its financial statements. Information ambiguity was varied across three levels by manipulating both the sufficiency and complexity of the data (insufficient/complex, sufficient/complex, and sufficient/not complex). Participants generated hypotheses that might explain the observed fluctuations in the data, then received a comprehensive financial data set (that was identical for all groups) and were asked to identify the cause of the fluctuations. The results indicate that when auditors are initially exposed to more ambiguous information (either due to its insufficiency or complexity), they are less likely to ultimately identify the error causing the fluctuations, even though they have access to the same unambiguous information set prior to making their final judgments. Implications of these results for audit research and practice are discussed.

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