| Publisher | SAS Institute | ||
|---|---|---|---|
| Format | 624.8KB PDF | Date added | 01 May 2009 |
| Topics | Knowledge and Data Management, Law and Government | ||
| Downloads | 0 | ||
More sophisticated revenue departments are starting to augment their rules-based systems with scores generated by analytical modeling. SAS analytical models assess a multitude of data points across the entire tax-filer base -looking at thousands of variables and conditions - to more effectively determine which returns are the most likely candidates for review, identify the reason and rank-order them by severity. Scoring capability can improve audit success by as much as 20 to 50 percent, compared to traditional rules-based approaches. Advanced, nonlinear modeling from SAS adds even more precision, which translates into even better rank ordering, fewer false positives, higher revenues and faster return on investment.
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