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Journal Article

A Roadmap for Analytics in Taxpayer Supervision  pp19-32

Mark Pijnenburg, Wojtek Kowalczyk, Lisette van der Hel-van Dijk

© Feb 2017 Volume 15 Issue 1, Editor: Mitja Dečman and Tina Jukić, pp1 - 56

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Abstract

Tax administrations need to become more efficient due to a growing workload, higher demands from citizens, and, in many countries, staff reduction and budget cuts. The novel field of analytics has achieved successes in improving efficiencies in areas such as banking, insurance and retail. Analytics, which is often described as an extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact‑based management to drive decisions and actions (Davenport and Harris, 2007: 7), fits well in tax administrations, that typically have access to large volumes of data. In this paper we will answer the question how analytics contributes to a Compliance Risk Management approach – a major trend in taxpayer supervision in the last decade. The main tasks within compliance risk management include risk identification, risk analysis, prioritization, treatment, and evaluation. The answer of the research question gives more insight in what we can expect from analytics, and will assist tax administrations that want to improve their analytical capabilities. Attention is paid as well to limitations of analytics. Findings include that over half of the activities in taxpayer supervision can be supported by analytics. Additionally, a match is presented between supervision activities and specific analytical techniques that can be applied for these activities. The article also contains a short case study of the Netherlands Tax and Customs Administration on selection of VAT refunds with analytical techniques.

 

Keywords: tax administration, taxpayer supervision, compliance risk management, analytics and data mining

 

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