Antifraud participates in the COrruption Risk indicators in Emergency project organized by Transparency International Portugal

The objective of the project is to develop and validate a composite indicator of the risk of corruption in emergency public procurement

The head of the Antifraud Data Analysis Team, Bruno González, in a presentation at the work days
The head of the Antifraud Data Analysis Team, Bruno González, in a presentation at the work days

June 28, 2023. The head of Antifrau's Data Analysis Team has participated in two working sessions organised in Lisbon by Tranparencia Internacional (TI) Portugal, in the framework of the EU-funded research project COrruption Risk indicators in Emergency (CO.R.E), on 19 and 20/06/2023. In addition to Antifrau together with the Universitat Oberta de Catalunya (UOC), the Università degli Studi di Perugia, which leads the project, the Hallgarten-Franchetti Centro Studi Vila Montesca Foundation, the Italian NGO Info.Nodes, and Dublin City University.

The aim of the project is to develop and validate a composite indicator of corruption risk in emergency public procurement, based on the experience gained in the extraordinary context of the pandemic. In emergency situations, the rules and regulations governing public procurement are subject to very significant alterations, making the risk indicators and alerts usually used much less effective. In addition, emergency procurement, due to its characteristics —maximum urgency in the award and execution of contracts; extreme simplification of procedures; etc.— is particularly irreversible: once contracts have been awarded and executed, the possibilities of correcting irregularities or reversing undue payments or services are minimal or non-existent. The development of an indicator specially adapted to these circumstances would allow the early detection of corruption risks and provide an objective basis on which to base the adoption of anti-corruption measures by the authorities, investigative journalists, and the public in the context of public sector accountability.

Antifrau's participation took place, during the year 2022, in the Work Package 2, led by the UOC under the title: Data availability and privacy constraints, which has culminated in the formulation of a synthesis document entitled CO.R.E Data Principles for Procurement Integrity under Emergency Times.

Noting that the above-mentioned decalogue of principles is fully in line with the statements, forecasts and prescriptions of the European Commission's Communication entitled: Public Procurement: A data space to improve public spending, boost data-driven policy-making and improve access to tenders for SMEs (2023/C 98 I/01), published in the OJEU of 16/03/2023, in these working sessions the UOC and Antifrau have proposed to the other participants the convenience of revising and updating said document, incorporating the lessons and findings from the development of the other work packages of the project, and to add a technical annex of recommendations and considerations addressed to the European Commission. The proposal has been accepted by the other participants.

The University of Perugia also presented the package of computer applications that calculate the different simple indicators that will make up the composite indicator of corruption risk, as well as the progress made in the statistical design of the composite indicator.

The NGO Info. Nodes presented the first version of the website where it will be possible to access the procurement data used for the development of the composite indicator as well as the values of both the simple indicators and the composite indicator for each public contracting authority and for each private contractor.

The Dublin City University team presented the model for transferring the knowledge and tools developed by the CO.R.E. project to the various potentially interested stakeholders (public or private anti-corruption bodies, citizens, journalists, etc.), as well as a research on the university-anti-corruption bodies-journalism collaboration model that is at the heart of the CO.R.E. project.

The project is financed by the European Union in the framework of the ISFP-2020-AG-CORRUPT programme.