Fraud Detection In Supply Chain 40 A Machine Learning Model by -- instant download after payment.

The fourth industrial revolution has begun with the introduction of artificial intelligence into the manufacturing environment. As a result, flow management have accelerated and worldwide Supply chain have become more automated than ever. In this context, Supply Chain financial risks have increased which requires companies to be more vigilant about fraud detection in their interactions with the different stakeholders. In this paper, we establish a machine learning model to predict fraudulent operations between the different links of Supply Chain. Three models are deployed to that purpose: Random forest, K-Nearest Neighbor and logistic regression. The most optimal model is then upgraded by using grid search cross validation. Results shows that the forecasting model is more efficient when cross validation is employed with a score of 97,7%.