IMPACT: This article highlights that while data preparers, auditors and final users of financial information in the public sector have been realizing the efficiency- and reliability-related benefits of data science tools, they may not be fully aware of the risks that may impact the transparency of financial documents and accountability-related processes. There is a very clear need to develop effective regulatory oversight mechanisms. The limited theoretical engagement of the literature reviewed in this article highlights the need for interdisciplinary approaches to conceptualizing data science and AI-driven financial reporting and decision-making.

Data science and public sector accounting: Reviewing impacts on reporting, auditing, and accountability practices

Agostino, Deborah;
2025-01-01

Abstract

IMPACT: This article highlights that while data preparers, auditors and final users of financial information in the public sector have been realizing the efficiency- and reliability-related benefits of data science tools, they may not be fully aware of the risks that may impact the transparency of financial documents and accountability-related processes. There is a very clear need to develop effective regulatory oversight mechanisms. The limited theoretical engagement of the literature reviewed in this article highlights the need for interdisciplinary approaches to conceptualizing data science and AI-driven financial reporting and decision-making.
2025
algorithms
Artificial intelligence
decision-making
governance
public financial management
research trends
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1309585
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