Our firm partnered with Deloitte Consulting on a project with the Internal Revenue to support the rollout of a new type of taxpayer notice while optimizing case selection and treatments based on data analysis.

We implemented enhancements to the client’s ASP.NET-based case selection tool and the SQL-Server database backend. The case selection tool was used to identify the best inventory based on a scoring algorithm and selection rules. The criteria for selection were a result of our extensive analysis of historical results.

Tasks Performed:

• We performed data analysis based on proven data interrogation techniques such as correlation analysis and regression analysis and used statistically driven case sampling, pattern recognition, and predictive modeling of cases to better understand historical data and develop new models and procedures for the selection of the most productive cases.
• We worked with our client subject matter experts to coordinate and develop an improved methodology which enhanced procedures for facilitating the selection process, increased process and data transparency with other systems, and resulted in the optimal mix of volume, yield, and key population characteristics within AUR inventory.
• We supported the requirements definition, planning, and management related to the enhancement of an Oracle database to allow for a new type of taxpayer notice to be issued with the objective of improving taxpayer compliance.

Results:

• Our consultants played a key role in reducing improper taxpayer behavior, resulting in increased IRS revenue recovery of over $800 million.
• We implemented automated data quality checks and implemented an action plan for improvement that improved the accuracy of identifying noncompliant taxpayers
• We uncovered fraudulent schemes including identity theft and supported the development of procedures to help minimize the impact to the IRS