IRTED-TL An Inter-Region Tax Evasion Detection Method Based on Transfer Learning

Loading...
Thumbnail Image
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
Date
2018-09-05
Major/Subject
Mcode
Degree programme
Language
en
Pages
12
1224-1235
Series
Proceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018, IEEE International Conference on Trust, Security and Privacy in Computing and Communications
Abstract
Tax evasion detection plays a crucial role in addressing tax revenue loss. Many efforts have been made to develop tax evasion detection models by leveraging machine learning techniques, but they have not constructed a uniform model for different geographical regions because an ample supply of training examples is a fundamental prerequisite for an effective detection model. When sufficient tax data are not readily available, the development of a representative detection model is more difficult due to unequal feature distributions in different regions. Existing methods face a challenge in explaining and tracing derived results. To overcome these challenges, we propose an Inter-Region Tax Evasion Detection method based on Transfer Learning (IRTED-TL), which is optimized to simultaneously augment training data and induce interpretability into the detection model. We exploit evasion-related knowledge in one region and leverage transfer learning techniques to reinforce the tax evasion detection tasks of other regions in which training examples are lacking. We provide a unified framework that takes advantage of auxiliary data using a transfer learning mechanism and builds an interpretable classifier for inter-region tax evasion detection. Experimental tests based on real-world tax data demonstrate that the IRTED-TL can detect tax evaders with higher accuracy and better interpretability than existing methods.
Description
Keywords
inter-region detection, interpretability, tax evasion, transfer learning
Citation
Zhu , X , Yan , Z , Ruan , J , Zheng , Q & Dong , B 2018 , IRTED-TL An Inter-Region Tax Evasion Detection Method Based on Transfer Learning . in Proceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 . , 8456038 , IEEE International Conference on Trust, Security and Privacy in Computing and Communications , IEEE , pp. 1224-1235 , IEEE International Conference on Trust, Security and Privacy in Computing and Communications / IEEE International Conference on Big Data Science and Engineering , New York , New York , United States , 01/08/2018 . https://doi.org/10.1109/TrustCom/BigDataSE.2018.00169