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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.
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