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    An empirical analysis of the likelihood of detecting fraud in New Zealand

    Owusu Ansah Stephen; Moyes Glen, D.; Oyelere Peter, B.; Hay David
    Abstract
    The objective of this paper is to provide information on the perceived effectiveness of 56 fraud-detecting standard audit procedures normally used in stock and warehousing cycle, and to examine auditor and audit firm specific factors that influence the likelihood of detecting fraud in stock and warehousing cycle in New Zealand. We gathered data through a mail survey of New Zealand auditors in order to ascertain their opinion on the effectiveness of these audit procedures. The results suggest that relatively few (less than half) of the 56 standard audit procedures are perceived by our surveyed auditors as being more effective in detecting fraud in stock and warehousing cycle. Further, more than half of the 56 audit procedures are perceived by respondents as moderately effective in detecting fraud. Fifteen audit procedures are perceived as being less effective in detecting fraud the stock and warehousing audit cycle. A univariate analysis reveals no significant perpetual differences among our respondents on the basis of the location of their employers in New Zealand, and the type of audit firm employing them. We employed logit regression analysis to test a model to predict the likelihood of detecting fraud in stock and warehousing cycle, given certain auditor and audit firm specific factors. The results of the regression analysis suggest that size of audit firm (measured by the number of employees), auditor’s position tenure, and auditor’s years of experience are statistically significant predictors of the likelihood of detecting fraud in stock and warehousing cycle in New Zealand. Thus, the likelihood of fraud detection in stock and warehousing increases as the auditor acquires more years of auditing experience, and with the audit firms employing more members of staff.... [Show full abstract]
    Keywords
    auditing; audit procedures; fraud detection; inventory control; logit regression analysis; stock and warehousing cycle; univariate analysis
    Date
    2001-02
    Type
    Discussion Paper
    Collections
    • Commerce Division Discussion Paper series [116]
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