Using increasingly powerful data analytics models and tools, tax administrations are able to benefit from their data-holdings, better understand complex business structures, including the evolving new business models of the digital economy, and to identify patterns of fraudulent tax schemes.
IOTA, in close collaboration with Predictive Analytics Competence Center of the Austrian Federal Ministry of Finance and with support of the Austrian Federal Finance Academy, organised a case study workshop “Use of Data Analytics in Tax Fraud Detection” in Vienna on 20 – 22 September 2017 attracting over 50 data analysts and tax fraud investigators from 23 IOTA member countries to discuss the practical use of different data analytics methods and tools for the detection of tax fraud schemes.
At the plenary session, participants had the opportunity to get acquainted with the data analytics models and tools developed by tax administrations in Austria, Belgium, Czech Republic, Estonia, France, Germany, Ireland, Netherlands, Norway and Sweden that have been effectively supported the detection of tax fraud cases (e.g. social benefits, fraudulent VAT refunds, fake VAT inputs, missing trader fraud in energy market, etc.).
The workshop continued with group discussions sharing the insights into the analytical approaches adopted to recognise patterns of income tax, wage, social benefits and VAT fraud. They also discussed the ways to enhance collaboration and information sharing between data analysts and tax fraud investigators.
During the workshop, the IOTA Secretariat also presented the results of the project on the development IOTA Good Practice Guide ‘Applying Data and Analytics in Tax Administrations’ with some of the examples of data analytics models implemented in the IOTA member tax administrations.
Further information about the workshop, including all presentations, is available here.