-
Digital Transformation and Corruption: BridgeGap Maps Where AI Helps, Where the Gaps Remain
The research report by Aleksej Heinze, Alfredo Jimenez, Julien Hanoteau and Virginie Vial (KEDGE Business School), with contributions from Joras Ferwerda (Utrecht University) sets out a clear picture of how digital transformation, and especially artificial intelligence, is being discussed in anti-corruption research. It shows an area showing a real dynamic, which still depends on stronger…
-
Machine Learning Detects Corruption Risk in Public Procurement
A case study on Danish public procurement contracts, 2016–2022 A new study from Utrecht University tests whether machine learning models can identify corruption risk in public procurement before a contract is awarded. The research applies twelve algorithms to 20,777 Danish procurement contracts covering the period 2016 to 2022. Its central finding is that the right…
-
Working Paper 25-01: Report Maps Public Procurement Data Across Europe
The BridgeGap Working Paper Series presents the first edition by BridgeGap members Andrea Longobucco and Joras Ferwerda of the University of Utrecht, part of the Work Package 6 on Artificial Intelligence on “Fighting Corruption with Artificial Intelligence: Searching for Suitable Public Procurement Data in the EU”. This report provides a groundbreaking comparative analysis of the…
-
WP6 – Artificial Intelligence
The key objective of WP6 is to assess the adequacy, equity, explainability and effectiveness of digital technologies, in particular, artificial intelligence, to control corruption more effectively as both top-down and bottom-up approaches. WP 6: Artificial Intelligence Comparative study on public procurement data suitability for AI purposes in EU MSs and accession countries 2025 Paper on…