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Machine Learning Application for SAIs

Tiare Rivera

International Journal of Government Auditing2026https://doi.org/10.56251/watu4873article
ABDC C
Weight
0.50

What the paper says

Supreme Audit Institutions (SAIs) are the cornerstone of maintaining accountability, transparency and effectiveness in the public sector, particularly in government operations. However, as technology evolves at breakneck speed, it is imperative that SAIs embrace cutting-edge data technologies, such as Machine Learning (ML), to revolutionize their auditing processes. With ML, SAIs can enhance efficiency, accuracy and effectiveness, providing a more comprehensive, data-driven analysis of government operations, thus ensuring the highest standards of accountability and trust.

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https://doi.org/https://doi.org/10.56251/watu4873

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@article{tiare2026,
  title        = {{Machine Learning Application for SAIs}},
  author       = {Tiare Rivera},
  journal      = {International Journal of Government Auditing},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.56251/watu4873},
}

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Machine Learning Application for SAIs

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.