Data mining in the context of the electronic auctions

Abstract

The government has sought to follow developments and trends in information and communication technologies in the context of the bidding process. Thus, electronic trading is one of the products of these efforts, being characterized as a modality that presented structural solutions to reduce the excess of bureaucracy in the acquisition of common goods and services. Its implementation contributed to increase the participation of suppliers and competitiveness in the fairs, as it reduced and even eliminated, in some cases, the need for physical presence of suppliers. The modality represents today more than 94% of the tenders that took place in the country, totaling more than 84% of the amount of resources spent through tenders. Despite their benefits, failures have been identified in a number of ways, one of which is the possibility of using bots, software programmed to connect to electronic trading platforms and bidding immediately and automatically, obtaining disproportionate advantages over humans. A second product of government efforts to modernize procurement is increased transparency through the availability of open bidding and contract data, including e-bidding, as part of the Open Government and digital transformation context. The overall purpose of this study is to discuss how data analysis can be useful in preventing fraud in electronic trading processes, based on the Federal Government's open data premise. Finally, it is concluded that this study supports the importance of discussing the effects of the use of bots in electronic trading sessions and believes in the potential for greater social control by citizens through access and analysis of government openings.