Good Practice Guide on Applying Data and Analytics in Tax Administrations

The evolution of big data is dramatically reshaping the way businesses operate. Technologies emerge rapidly and the world expects tax administrations to join the revolution. In the Good Practice Guide, a wide variety of good practices in applying data and analytics within tax administrations is collected. Along the edges of five different topics, more than ten European countries have shared their valuable insights.

Link to the e-book


0. Introduction
1. Data management

  • Data quadrant model (by Ronald Damhof)
  • Data layer architecture
  • The DAMA framework
  • Standard audit file for tax (SAF-T)

2. Predictive modelling

  • Risk indicators – Business rules
  • Risk indicators – Hierarchical clustering on declaration data
  • Risk indicators – Network analysis with Panorama
  • Combine and optimize – VAT risk model
  • Combine and optimize – Risk matrix
  • Combine and optimize – Predicting income using Big Data and regression

3. Social network analysis

  • Basic good practices in SNA
  • Social network analysis for fraud detection
  • Transaction Network Analysis in the EU

4. Data visualisation

  • Visualising complex taxpayer relationships and risk management results at the same time
  • Multifunctional system with data visualisation functions
  • The choices of visualisation

5. Random audits

  • The random audits program in the Norwegian Tax Administration
  • The importance of random samples

6. Other topics

  • Channel strategy
  • Debt management
  • Web scraping

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