The state of Texas has harnessed SPSS predictive analytics software to enhance its “Advanced Database System (ADS)” tax compliance function. Predictive models are a key component of ADS and played an important role to recover more than $400 million in unpaid taxes since its inception in 1998. The Audit Division of the Texas Comptroller of Public Accounts (CPA) uses SPSS and Elite Analytics, a data mining consulting service, to maximize taxpayer compliance and maintain revenue streams.

State tax agencies are charged with reducing the “tax gap” between the tax owed and the amount collected. Audits are critical to enforcing tax laws and helping tax agencies achieve revenue objectives. With SPSS’ data mining workbench, Clementine, Texas CPA and Elite Analytics developed an audit selection strategy that more accurately predicts which audit leads are more likely to yield greater tax adjustments.   

“State tax agencies have limited staff and resources, and predictive analytics enable the agencies to more efficiently and effectively identify delinquent taxpayers and make effective resource allocation decisions,“ said Daniele Micci-Barreca, Ph.D., a principal at Elite Analytics. “With SPSS predictive analytics, the Texas CPA was able to refine its traditional audit selection strategies to produce more accurate results.”     

“SPSS predictive analytics has many applications in tax administration,” said SPSS President and CEO Jack Noonan. “Predictive analytics translates mountains of data into actionable information that can improve everything from audit selection to collections prioritization.”

All 50 U.S. state governments use SPSS software for such purposes as fraud, waste and abuse prevention; homeland security; law enforcement; survey research; and e-government initiatives.

This BeyeNETWORK news item contains information from a recent press release by the company mentioned.

SOURCE: SPSS Predictive Analytics Helps Texas Recover $400 Million in Unpaid Taxes