Money laundering and terrorist financing is a risk to which different entities are exposed; but mainly the financial ones due to the nature of their activity, so that they especially must and are obliged to have an appropriate methodology to analyze and evaluate risks. The issue of money laundering is of the utmost importance, so this research aims to contribute to the solution
of this serious problem. In order to support the fight against money laundering and terrorist financing, this work proposes a methodology that identifies, measures, quantifies and manages the risk of ML and TF. The fundamental premise is the cause-effect relationship between the different risk factors for which the Bayesian network model was used.
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