Analyzing Irregularities in Public Bids with a Focus on Small Businesses

• Camila S. Braz UFMG
• Bárbara M. A. Mendes UFMG
• Gabriel P. Oliveira 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/wcge.2023.230254

Abstract

Analyzing public bids can reveal several negotiating characteristics between companies and the public sector. Unfortunately, this analysis can also give evidence of fraud involving companies. This paper describes two approaches that help identify irregularities in small businesses based on data extracted from public tenders in the State of Minas Gerais. The results indicate that both approaches can locate small companies suspected of involvement in fraud. Such approaches are essential as they can improve mechanisms for controlling and preventing fraud in the bidding process.

Keywords: government data, public bids, small businesses, data analysis

References

Buryakov, D., Kovacs, M., Kryssanov, V., and Serdült, U. (2023). Using open government data to facilitate the design of voting advice applications. In Electronic Participation: 14th IFIP WG 8.5 International Conference, ePart 2022, Linköping, Sweden, September 6–8, 2022, Proceedings, pages 19–34. Springer.

Coelho, G. M., Ramos, A. C., de Sousa, J., Cavaliere, M., de Lima, M. J., Mangeth, A., Frajhof, I. Z., Cury, C., and Casanova, M. A. (2022). Text classification in the brazilian legal domain. In ICEIS (1), pages 355–363.

Costa, L. L. et al. (2022). Alertas de fraude em licitações: Uma abordagem baseada em redes sociais. In BraSNAM, pages 37–48, Porto Alegre, Brasil. SBC.

Gabardo, A. C. and Lopes, H. S. (2014). Using social network analysis to unveil cartels in public bids. In ENIC, pages 17–21. IEEE.

Lima, M. et al. (2020). Inferring about fraudulent collusion risk on brazilian public works contracts in official texts using a bi-lstm approach. In EMNLP, pages 1580–1588.

Luna, R. S. and Figueiredo, D. R. (2022). Caracterização das licitações públicas no estado do rio de janeiro: Diversidade, licitantes únicos e redes. In Anais do X Workshop de Computação Aplicada em Governo Eletrônico, pages 145–156. SBC.

Lyra, M. S. et al. (2021). Characterization of the firm–firm public procurement co-bidding network from the State of Ceará (Brazil) municipalities. Appl. Network Sci., 6(1):1–10.

Nai, R., Sulis, E., and Meo, R. (2022). Public procurement fraud detection and artificial intelligence techniques: a literature review. In Companion Proceedings of the 23rd International Conference on Knowledge Engineering and Knowledge Management, Bozen-Bolzano, Italy.

Oliveira, G. P., Reis, A. P., Freitas, F. A., Costa, L. L., Silva, M. O., Brum, P. P., Oliveira, S. E., Brandão, M. A., Lacerda, A., and Pappa, G. L. (2022). Detecting inconsistencies in public bids: An automated and data-based approach. In Proceedings of the Brazilian Symposium on Multimedia and the Web, pages 182–190.

Silva, M. O., Paula, A. F., Oliveira, G. P., Vaz, I. A., Hott, H., Gomide, L. D., Reis, A. P., Mendes, B. M., Bacha, C. A., Costa, L. L., et al. (2022). Lipset: Um conjunto de dados com documentos rotulados de licitaçoes públicas. In Anais do IV Dataset Showcase Workshop – SBBD, pages 13–24. SBC.

Silva Pereira, A. K. d., Vita, Y. M., Silva Felix da, G., Gimaque, J. M. F., Damasceno, M. L. S., and de Figueirêdo, B. C. B. (2022). Usando redes complexas na identificação de empresas fraudulentas em licitações públicas. In Anais do X Workshop de Computação Aplicada em Governo Eletrônico, pages 13–24. SBC.