Year: 2024
Type: article
Abstract: The purpose of this study is to explore challenges in Tax Fraud Investigations faced by the investigating officersand the study explores and highlights the real problems associated with such investigations. The study involvesin-depth interviews of fifteen investigating officers working in IRS Intelligence. Data collection involved focusedgroup interviews, individual indepth interviews and document analysis. The data were analyzed with the help ofgrounded theory and thematic analysis. Research study suggests that in order to achieve quality performance ofTax Fraud Investigations, it is very crucial to improve performance of investigating officers which may bepossible if the challenges highlighted by this research are overcome. It may further add value to the overalldomestic revenue mobilization efforts of Federal Board of Revenue besides creating deterrence for fraudulentelements. Findings of the study are limited to the perspectives of fifteen participants. A similar study with largerpopulation in all the offices of IRS Intelligence as well as other investigating agencies could have provided evenmore concrete and exhaustive results. Overcoming of such challenges and problems in Tax Fraud investigationsmay invariably enhance the performance of investigating officer entrusted with tax fraud investigations and mayfurther increase the effective and efficient monitoring and enforcement activities while minimizing the evasion ofdue taxes by fraudsters. The study further provides valuable insight into the prevalent investigation processeswhich may be used by the legislators for making policies accordingly. The valuable insights into the problemsfaced by the investigating officers may help the investigating agency to fix those problems for better performanceand in safeguarding the revenue of state. This is the first study of its kind conducted on problems and challengesfaced by the investigating officers conducting tax fraud investigations.
Authors: Syed Mahmood Ali Shah, Dr. Muhammad Asif
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4413907185