Big Data Applied to Tax Evasion Detection: A Systematic Review
Tax evasion fraud is an issue faced by all governments in the world and one way to improve its detection is the application of big data technologies. This work performs a systematic literature review with the objective of identifying primary studies that address the fraud tax detection by the use of big data. This review resulted in the finding of 56 works of which 5 were identified as primary study. An overview of the results is presented categorized by the studies that address the problem by the use of pattern recognition methodologies, natural language processing and data analytics in auditing. The results also present algorithms and models used in each solution.
2016 International Conference on Computational Science and Computational Intelligence (CSCI)