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.