Technical Notes and Manuals

Tax Administration: Essential Analytics for Compliance Risk Management

By Joshua Aslett, Gustavo González, Stuart Hamilton, Miguel Pecho

February 26, 2024

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Format: Chicago

Joshua Aslett, Gustavo González, Stuart Hamilton, and Miguel Pecho. Tax Administration: Essential Analytics for Compliance Risk Management, (USA: International Monetary Fund, 2024) accessed November 21, 2024

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Disclaimer: This Technical Guidance Note should not be reported as representing the views of the IMF. The views expressed in this Note are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

This technical note introduces analytics for compliance risk management in tax administration. Together with its accompanying toolkit, the note is intended as a starter kit to support capacity development in compliance planning, risk, and intelligence groups. Developed primarily for emerging analysts new to tax administration, the note presents both theory and practical aspects of analytics. Its toolkit is comprised of an initial collection of analytics templates designed to assist in turning the theory presented into practice in the areas of: (1) compliance planning; (2) taxpayer profiling; and (3) audit case selection.

Subject: Compliance risk management, Expenditure, Machine learning, Revenue administration, Tax administration core functions, Taxes, Technology, Value-added tax

Keywords: Analytics, Analytics support compliance risk management, Compliance risk management, Compliance strategy, CRM theory, Data, Data quality, Digitalization, IMF Library, Information technology, Intelligence, Machine learning, Risk analysis, Support CRM analytics capability, Tax administration, Tax administration core functions, Value-added tax

Publication Details

  • Pages:

    49

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Technical Notes and Manuals No. 2024/001

  • Stock No:

    TNMEA2024001

  • ISBN:

    9798400260063

  • ISSN:

    2075-8669