Deep Learning-based Synthetic Data for Money Laundering Control Simulations

Deep Learning-based Synthetic Data for Money Laundering Control Simulations

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Deep Learning-based Synthetic Data for Money Laundering Control Simulations

The purpose of this paper is to generate statistically significant and consistent data, where the probabilistic benefits and the parameters for the generation of new information that facilitate the simulation of the behaviors of the agents involved in money laundering are determined.

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