Money laundering risk management in multiple-purpose financial institutions in Mexico: a Bayesian network approach

Purpose: This paper aims to develop a money laundering risk management model for multiple-purpose financial institutions (SOFOMES, Spanish acronym for “Sociedades Financieras de Objeto Múltiple”) based on the best international practices. Design/methodology/approach: A study of a sample of several SOFOMES is carried out through representative surveys and focus groups to collect information to develop a causal model of risk management under a Bayesian network approach together with a Monte Carlo simulation. Findings: The probability that SOFOMES has a high incidence to be used as a mean of money laundering is 29.3%, correspondingly with a probability of 33.1% of having medium incidence and 37.4% of low incidence. Research limitations/implications: Only nine SOFOMES were willing to provide information for this study. Practical implications: In Mexico, there is a large registry in the Ministry of Finance and the Attorney General’s Office of this type of practices in the SOFOMES sector, impacting tax collection and affecting the growth of the real sector. The proposed model serves to establish several preventive policies that reduce the incidence of this type of crime. Originality/value: As far as the authors know, there is no other study as this one in Mexico or in the rest of the world.