2 papers
cs.LG2025
Learning from sanctioned government suppliers: A machine learning and network science approach to detecting fraud and corruption in Mexico
Martí Medina-Hernández, Janos Kertész, Mihály Fazekas
Detecting fraud and corruption in public procurement remains a major challenge for governments worldwide. Most research to-date builds on domain-knowledge-based corruption risk ind…
q-fin.GN2019
Corruption Risk in Contracting Markets: A Network Science Perspective
Johannes Wachs, Mihály Fazekas, János Kertész
We use methods from network science to analyze corruption risk in a large administrative dataset of over 4 million public procurement contracts from European Union member states co…