A methodology for highlighting nodes in graphs applied to the analysis of financial intelligence reports (in Portuguese)

Abstract

Money laundering is a category of crime that requires great efforts by criminal investigators to gather a variety of information in order to set the context for an investigation. One of the sources for starting the investigation and the search for adjacent information is the Financial Intelligence Report. From this report, the researcher dives into a large set of data and information to form the panorama of the investigation. With all the information gathered and interconnected, a graph is obtained in which one can use computational techniques to search for and highlight the main ones involved in the report. Since the size of the graph and the number of nodes can take on large proportions, which would make it difficult to identify the main people, companies and financial operations, this work presents as a 2 Zaina, Roberto; Araujo*, Gustavo Medeiros de; Ramos, Vinicius Faria Culmant (2020). Uma metodologia para destaque de nós em grafos aplicada à análise de relatórios de inteligência financeira (preprint). Ciência da Informação. Disponibilizado em EmeRI - Emerging Research Information. (preprints.ibict.br) DOI: 10.21452/15188353202000002. proposal, a methodology supported by technology to highlight the main ones involved in the investigation. The methodology adopted was data mining guided by metrics such as "suspicious companies" and "suspicious accountants". With the result of the data mining, a link analysis program was loaded forming the graph with the information from the highlighted nodes, representing the main ones involved in the investigation. This methodology helps the criminal investigator, as it facilitates the processing of large volumes of data and helps to decrease the complexity of the information arising from the Financial Intelligence Reports.