The UIF study, no. 27 of April 2025, analyzes the risk of infiltration by organized crime into Italian local administrations, through the emergence of recurring anomalies, derived from the examination of municipal financial data from 2016 to 2021, thanks to an innovative process of automation in the analysis of certain recurring elements. This process automation is based on an approach from which useful data can be drawn to assess the risk of criminal infiltration within municipalities through the use of parameters ranging from descriptive statistical analysis, through statistical tests and machine learning models, to the validation of data from external sources. More specifically, descriptive statistical analysis was used to compare municipalities dissolved due to mafia infiltration with a control group, highlighting differences in municipal budgets and identifying the most vulnerable spending sectors. As for the statistical tests, their execution, based on the significance of the findings, provided evidence of the relationship between criminal infiltration and specific financial indicators, using socio-economic variables as a reference parameter. Based on this data, using machine learning models, it was then possible to structure an algorithm aimed at classifying municipalities at risk of mafia infiltration with ...