2026-06-17T23:26:35Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/86452024-05-10T11:38:47Zcom_10259_7380com_10259_5086com_10259_2604col_10259_8643
Repositorio Institucional de la Universidad de Burgos
author
Blanco Alcántara, David
author
García-Moreno Rodríguez, Fernando
author
López de Foronda Pérez, Óscar
2024-02-08T13:39:28Z
2024-02-08T13:39:28Z
2022-11-30
978-3-031-19051-3
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.
eng
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
Fraud and Corruption in EU Funding. The Problematic Use of European Funds and Solutions
info:eu-repo/semantics/book
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URL
https://riubu.ubu.es/bitstream/10259/8645/1/Blanco-Fraud_Corruption_EU_Funding_2022.pdf
File
MD5
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3113772
application/pdf
Blanco-Fraud_Corruption_EU_Funding_2022.pdf