PLUS: A Semi-automated Pipeline for Fraud Detection in Public Bids

Abstract

The diversity of sources and formats of public bidding documents makes collecting, processing, and organizing such documents challenging from the point of view of data analysis. Thus, the development of approaches to deal with such data is relevant since the analysis of them allows to expand of the inclusion of people as they have more access to public decisions and expenditures, increase transparency in the public sector, and give citizens a greater sense of responsibility for having different points of view on the government’s performance in meeting its public policy goals. In this context, we propose PLUS, a semi-automated pipeline for fraud detection in public bids. PLUS comprises a heuristic meta-classifier for bidding documents and a data quality module. Both modules present promising results after a proof of concept, reinforcing the relevance of PLUS for automating the bidding process investigation. Then, we present two applications of PLUS on real-world data: the construction of audit trails for fraud detection and a price database for overpricing detection. Such applications evidence a significant reduction of specialists’ work searching for irregularities in public bids.