Uncertainty Quantification in risk modeling: the case of customs supply chain

In this paper, Uncertainty Quantification (UQ) is used in risk modeling to describe the time series describing the risks in customs supply chain. We start by introducing the Hilbertian approach related to representation of Random Variables and addressing these approximations and their applications in UQ. Then an extension where these models are applied to the time series in order to handle the seasonal components of risks in customs supply chain. The models are fitted to time series describing the seized quantities of the smuggling of drugs on two sites using Moment Matching Method. the results furnish a good description of important properties of the data, namely, the polynomial expansion and Cumulative Distribution Function (CDF).