TAB Bid Irregularity: Data-Driven Model and Its Application

Abstract

Noncompetitive and collusive bidding behaviors have recently become a major concern in public projects. Identifying the bidders involved in price manipulation protects the public interest as well as market integrity. However, the literature lacks an easy and fast approach to detecting abnormal bidding behaviors. This study fills this gap by presenting a data-driven model, referred to as Test of Abnormal Bid (TAB), for fast detection of price irregularity based on Benford’s law, which is widely used for fraud detection in the auditing and financial industry. Applying TAB to a recent West Virginia legal case, where paving companies established a monopoly to manipulate and inflate material costs, demonstrates how the model helps public agencies detect irregular bid patterns and possible price manipulations. The authors analyzed more than 100,000 asphalt bid items from 2011 to 2020 to test and validate this proposed model. Results revealed that TAB is highly effective in flagging irregular bidding behaviors and reporting the source of irregularities. This paper contributes to the body of knowledge by introducing a rapid, easy, and low-cost approach to detecting and monitoring potential collusive pricing practices.