Collusion Fraud Risk Mitigation with Integration of Data Analytics in E-Tendering

Abstract

There are already mandates and recommendations for detecting indications of tender collusion, but the risk of collusion in e-tendering has not been handled properly. Meanwhile, data analytics competency has become a prerequisite for successful digital transformation. This study aims to reveal the projection of data analytics integration in controlling collusion risk in e-tendering. This study uses a quantitative research method. The object of this study includes data on the risk of tender collusion and the KPPU’s Decisions for 2021 and 2022. The results of this study reveal that the average similarity of bids is 0.5308, a parameter indicating the risk of collusion in tenders. Existing controls have not been effective in dealing with this risk. Control development can be designed by referring to KPPU regulations and recommendations to LKPP. Maximum control standards can be applied by developing preventive controls in the form of data analytics competence training for the Selection Committee so that they are able to detect indications of collusion in tenders. In addition, data analytics tools need to be integrated into e-tendering in the Electronic Procurement System (SPSE).