This chapter focuses on the subjective ratings and their use in predicting high

This chapter focuses on the subjective ratings and

This preview shows page 232 - 234 out of 311 pages.

This chapter focuses on the subjective ratings and their use in predicting high risk. It is therefore of interest to ask if the dollars at risk for any issue adds significantly to the prediction after the flags from Table 10.3 have been included. This was analysed several ways and the dollars at risk for ‘property held in a listed (non-tax-haven) country – real estate’ consistently added to the prediction of high overall risk after subjective ratings were included. From our analyses it would appear that the subjective, informed assessment of the analyst is a useful approach to detecting risk, with the quantitative data providing further clues to follow. This is contrary to the notion that the dollars at risk, being a more objective measure, would have superior predictive capacity to predict: Better to analyse subjective risk assessments first, then add some value with a diagnosis of unusually large dollar amounts. Our experience of the regulatory craft (Sparrow, 2000) leads us to suspect that analysts need both the skills of a detective and those of an accountant. Nuance of judgment is needed; things have to pass the smell test. When the good analyst smells a rat, they are more likely to chase it down a hole than to further analyse numbers. While quantitative analysis provides clues, systemic wisdom must then be applied to the specific case. That case should be looked at through many different lenses, of which the quantitative lens is only one.
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Tax Compliance by the Very Wealthy 223 These data suggest to us that there might be a case for a two-step process with aggressive tax planning analysis. Step 1 is a qualitative diagnosis of returns and other intelligence surrounding the case that is informed by knowledge of red flags of systemic risk. Step 2 is a re-examination of objectively unusually large amounts of money that occur under labels that are not viewed as red flags, but that might become red flags when the dollars in them are extraordinary. Step 2 does not mean further interrogation of all extraordinary amounts. It means a harder look only when exceptionally large amounts occur under non-red-flag issues that the kind of analysis in Tables 10.6 and 10.7 reveal to be significant predictors of overall risk. The analyses reported in this chapter only take us as far as making some practical suggestions for the identification of red flags for Step 1. Step 2 would only make sense to become a standard methodology after complementing the quantitative analyses in Tables 10.6 and 10.7 with qualitative intelligence on the operations of aggressive tax planners. Final Red Flags Models Having carried out the above analyses, our final task is to convert the results shown in Tables 10.3 to 10.7 into a more useful form for discussion and practical application. It is clear that most of our potential red flags were consistent with what we referred to as standard niches. Other issues appeared to be indicative of more boutique niches. It has further been demonstrated that the number of HWIs rated as
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  • Fall '16
  • tax authority, Australian Taxation Office, Tax Office, Compliance Model

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