Ranqueamento de Licitações Públicas a partir de Alertas de Fraude

• Gabriel P. Oliveira UFMG
• Bárbara M. A. Mendes UFMG
• Camila S. Braz UFMG
• Lucas L. Costa UFMG
• Mariana O. Silva UFMG
• Michele A. Brandão UFMG / IFMG
• Anisio Lacerda UFMG
• Gisele L. Pappa UFMG

DOI: https://doi.org/10.5753/brasnam.2023.232105

Abstract

Fraud detection is a complex task in various scenarios. This work proposes an approach to rank public tenders suspected of fraud. For this, we have created 19 audit trails, which were modeled as a social network, and a strategy to consider the alerts they raised in the ranking. The results reveal that the proposed ranking approach can correctly identify bids suspected of fraud.

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