2026-06-17T20:31:32Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/86452024-05-10T11:38:47Zcom_10259_7380com_10259_5086com_10259_2604col_10259_8643

Blanco Alcántara, David García-Moreno Rodríguez, Fernando López de Foronda Pérez, Óscar 2024-02-08T13:39:28Z 2024-02-08T13:39:28Z 2022-11-30 978-3-031-19051-3 978-3-031-19050-6 2523-336X http://hdl.handle.net/10259/8645 10.1007/978-3-031-19051-3 2523-3378 This book provides systematic comparative research of antifraud laws and context at EU countries using a Artificial Neural Network (ANN) model to predict illegal activities in ERDF and CF. It also details a map of corruption risk with the goal of reducing corruption and fraud in the management of European Regional Development Funds and Cohesion Funds through the incorporation of adequate measures and strategies derived from the resulting of EUMODFRAUD EU Project. The authors analyse the specific situations, observe the risks and finally, propose an innovative method that allows predicting fraudulent acts, which will be of interest to both academics, researchers, and policy makers in financial services, public finance, and financial crime. application/pdf eng Palgrave Macmillan Fraud Corruption European Funds Corruption Perception Index European Structural and Investment Funds Detecting Fraud Anti-fraud laws Artificial Neural Networks (ANN) model Fighting corruption in private and public institutions Economía Política económica Derecho y economía Economics Economic policy Law and economics Fraud and Corruption in EU Funding. The Problematic Use of European Funds and Solutions info:eu-repo/semantics/book info:eu-repo/semantics/acceptedVersion info:eu-repo/semantics/closedAccess https://doi.org/10.1007/978-3-031-19051-3