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.

Analyses the use of European Funds between countries to gather insight for better use of these economic aids Explores ways to strengthen fraud detection, response, and coordination between different member state Offers an in-depth analysis of fraud in the framework of public procurement

Autorentext

David Blanco-Alcántara is a Senior Lecturer in Corporate Finance at the University of

Burgos, Spain.

Fernando García-Moreno Rodríguez is a Senior Lecturer in Administrative Law in the

Faculty of Law, University of Burgos, Spain.

Óscar López-de-Foronda Pérez is a Senior Lecturer in Corporate Finance and

Accounting at the University of Burgos, Spain.

Inhalt

Chapter 1. The Corruption Problem in Europe.- Chapter 2: An Analysis of the Efficiency of European Funds.- Chapter 3: Fighting Fraud and Corruption in European Structural and Investments Funds.- Chapter 4: Innovative Methods for Predicting Fraud and Corruption.- Chapter 5: Conclusion.