Exploring the Use of Predictive Analytics by Austrian Tax Authorities: A Qualitative Study within the Task-Technology Fit Model

Marina Luketina, Christoph Schütz

Research output: Contribution to conferenceAbstractpeer-review

Abstract

Taxes finance important government services that are now taken for granted in our society, such as infrastructure, health care, or
retirement pensions. Tax authorities everywhere strive to ensure that all individual persons and companies comply with applicable
tax laws. In this regard, tax authorities must prevent individual persons or companies from evading taxes in an illegal manner. To
this end, Austrian tax authorities employ state-of-the-art predictive analytics technology for the selection of suspicious cases for tax
audits, thus making efficient use of scarce resources for tax auditing. In this paper, we explore how Austrian tax authorities employ
predictive analytics technology in tax auditing and how well the use of such technology fits the characteristics of the task at hand.
We collaborated with the Austrian Federal Ministry of Finance’s Predictive Analytics Competence Center to obtain insights into the
application of predictive analytics technology by Austrian tax authorities. The thus obtained insights serve as the basis for a qualitative
analysis in the context of the task-technology fit framework.
Original languageEnglish
Publication statusPublished - 7 Mar 2025
EventINCIS-2025 (1st India Conference on
Information System)
- Kolkata, India
Duration: 11 Mar 202514 Mar 2025

Conference

ConferenceINCIS-2025 (1st India Conference on
Information System)
Abbreviated titleINCIS
Country/TerritoryIndia
CityKolkata
Period11.03.202514.03.2025

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