Knowledge and Data Management White Papers
Closing the Tax Gap: Accurately Identify and Prioritize Tax Returns That Have a High Likelihood of Underreporting and a High Magnitude of Potential Collections
Overview 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.
| Publisher | SAS Institute | File Format | |
|---|---|---|---|
| Date Published | May 2009 | ||
| Format | White Papers | ||
| Topics | |||
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