Predictive Analytics as A Service on Moroccan Tax Evasion

  • Authors

    • Houda Jihal
    • Mohamed Amine Talhaoui
    • Abderrahmane Daif
    • Mohamed Azzouazi
    2018-12-06
    https://doi.org/10.14419/ijet.v7i4.32.23253
  • Predictive Analytics, linear regression, Statistical Computing, Tax evasion.

  • Abstract

    Tax evasion is a global problem in governments. It affects society by damaging public accounts and compromising government performance. The government must take a multidisciplinary approach to face this phenomenon. Analytics on big data enables government organizations to improve existing processes and operations and engage in entirely new types of analyses that weren’t possible before. Predictive analytics combines the capabilities of machine learning, statistical analysis and data mining to forecast the future and allows tax authority to prevent tax fraud, reduce the cost of managing taxes and optimize public spending.

    The purpose of this paper is to predict income from direct Moroccan taxes based on the linear regression model as a first step in the fight of the tax evasion.

     

     

  • References

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  • How to Cite

    Jihal, H., Amine Talhaoui, M., Daif, A., & Azzouazi, M. (2018). Predictive Analytics as A Service on Moroccan Tax Evasion. International Journal of Engineering & Technology, 7(4.32), 90-92. https://doi.org/10.14419/ijet.v7i4.32.23253

    Received date: 2018-12-06

    Accepted date: 2018-12-06

    Published date: 2018-12-06