E-File, Enterprise Structures, and Tax Compliance Risk Assessment
U.S. Department of Treasury - Office of Tax Analysis (OTA)
University of Illinois at Urbana-Champaign - Department of Accountancy
William B. Trautman
Internal Revenue Service - LMSB Research East
September 15, 2008
Tax Notes, Vol. 120, No. 11, 2008
Charles Boynton is a project manager at the IRS, Petro Lisowsky is an assistant professor of accounting at the University of Illinois at Urbana-Champaign, and William B. Trautman is a senior economist at the IRS. An earlier version of this paper was presented at the 2008 IRS Research Conference on June 11.
The electronic filing of large corporate and partnership tax returns in XML format makes it feasible for the IRS and other tax administrations to consider assessing tax compliance risk in the context of broad business enterprises instead of just tax return filing entities. This paper proposes enterprise data structures as the foundation for such analysis and describes how to construct them in real time using open-source XML and object-oriented programming technologies. It describes a software program which has been developed by one of the authors, runs on a personal computer, and is easily adaptable to other platforms. Finally, it discusses a number of exciting opportunities the technology makes possible for improving tax compliance risk analysis in the areas of tax shelter detection, book-tax reconciliation, and simulation modeling. This programming can further aid state, federal, and foreign tax administrations alike, thereby increasing the efficiency of the audit resource allocation process.
The authors would like to thank John Miller and other managers in LMSB Research and Workload Identification (RWI) for supporting this work, as well as Ken Cantrell, Dennis Chan, Margaret Finegan, David Heitmeyer, Jeff Johnson, Bill Kloeckner, Jack Loggia, Terrance O'Malley, Lois Petzing, George Plesko, Kithsiri De Silva, Nick Ward, and Joe West for additional valuable comments. The opinions expressed in this report, however, are those of the authors and do not necessarily reflect those of the IRS.
Accepted Paper Series
Date posted: September 15, 2008
© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo4 in 0.297 seconds