IBM Case Studies Predictive Analytics Boosts Revenue Collection for California Franchise Tax Board

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	Predictive Analytics Boosts Revenue Collection for California Franchise Tax Board IBM

Predictive Analytics Boosts Revenue Collection for California Franchise Tax Board

IBM

Technology Category	Analytics & Modeling - Predictive Analytics Networks & Connectivity - NFC
Challenge	The California Franchise Tax Board (FTB), a part of the California Government Operations Agency, was faced with a daunting task. They had a list of over three million delinquent or non-filing taxpayers and were struggling to determine where to start the collection process. The traditional methods of relying on experience and anecdotal evidence were no longer effective, and state revenue was suffering as a result. The board was grappling with a multibillion-dollar gap between the amount they collected and the amount they were owed. The challenge was to find a more efficient and effective way to prioritize nonpayment cases and increase revenue collection. Read More
About Customer	The California Franchise Tax Board (FTB) is a part of the California Government Operations Agency. It is responsible for collecting state personal income tax and corporate income tax in California. The board is composed of the California State Controller, the director of the California Department of Finance, and the chair of the California Board of Equalization. The FTB was faced with the challenge of collecting taxes from over three million delinquent or non-filing taxpayers, which was causing a significant decrease in state revenue. Read More
Solution	The FTB developed an advanced analytics solution using IBM® SPSS® Modeler and IBM SPSS Collaboration and Deployment Services, in partnership with IBM Business Partner Elite Analytics, LLC. The solution uses information from state and federal sources to identify the attributes and attribute combinations that are most common among successfully resolved cases. Sophisticated algorithms are then used to score millions of cases based on these attributes. This scoring system allows the department to prioritize its workload according to how likely each case is to result in payment and how much that payment might be. This strategic approach enables the staff to focus on the cases with the highest potential for revenue reclamation, thereby maximizing efficiency for its audit, nonfiler, and collections departments. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Networks & Connectivity - NFC

Challenge

The California Franchise Tax Board (FTB), a part of the California Government Operations Agency, was faced with a daunting task. They had a list of over three million delinquent or non-filing taxpayers and were struggling to determine where to start the collection process. The traditional methods of relying on experience and anecdotal evidence were no longer effective, and state revenue was suffering as a result. The board was grappling with a multibillion-dollar gap between the amount they collected and the amount they were owed. The challenge was to find a more efficient and effective way to prioritize nonpayment cases and increase revenue collection.

About Customer

The California Franchise Tax Board (FTB) is a part of the California Government Operations Agency. It is responsible for collecting state personal income tax and corporate income tax in California. The board is composed of the California State Controller, the director of the California Department of Finance, and the chair of the California Board of Equalization. The FTB was faced with the challenge of collecting taxes from over three million delinquent or non-filing taxpayers, which was causing a significant decrease in state revenue.

Solution

The FTB developed an advanced analytics solution using IBM® SPSS® Modeler and IBM SPSS Collaboration and Deployment Services, in partnership with IBM Business Partner Elite Analytics, LLC. The solution uses information from state and federal sources to identify the attributes and attribute combinations that are most common among successfully resolved cases. Sophisticated algorithms are then used to score millions of cases based on these attributes. This scoring system allows the department to prioritize its workload according to how likely each case is to result in payment and how much that payment might be. This strategic approach enables the staff to focus on the cases with the highest potential for revenue reclamation, thereby maximizing efficiency for its audit, nonfiler, and collections departments.

Impact #1	The implementation of the advanced analytics solution has revolutionized the way the California FTB operates. The ability to prioritize cases based on their likelihood of payment and potential payment amount has significantly improved the efficiency of the department. The staff can now focus on the cases with the highest potential for revenue reclamation, which has not only increased revenue but also improved the success rate of contacting business-entity nonfilers. The solution has effectively bridged the gap between the amount the board collected and what it was owed, thereby significantly boosting state revenue.

Impact #1

The implementation of the advanced analytics solution has revolutionized the way the California FTB operates. The ability to prioritize cases based on their likelihood of payment and potential payment amount has significantly improved the efficiency of the department. The staff can now focus on the cases with the highest potential for revenue reclamation, which has not only increased revenue but also improved the success rate of contacting business-entity nonfilers. The solution has effectively bridged the gap between the amount the board collected and what it was owed, thereby significantly boosting state revenue.

Benefit #1	Increased revenue by more than USD 400 million in the first two years after implementation
Benefit #2	Achieved a 300 percent improvement in the number of successful attempts to contact business-entity nonfilers
Benefit #3	Maximized efficiency for its audit, nonfiler, and collections departments by focusing on cases with the highest potential for revenue reclamation

Benefit #1

Increased revenue by more than USD 400 million in the first two years after implementation

Benefit #2

Achieved a 300 percent improvement in the number of successful attempts to contact business-entity nonfilers

Benefit #3

Maximized efficiency for its audit, nonfiler, and collections departments by focusing on cases with the highest potential for revenue reclamation

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Overview

Predictive Analytics Boosts Revenue Collection for California Franchise Tax Board

Operational Impact

Quantitative Benefit