Detection of shell companies in financial institutions using dynamic social network

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Rocha Salazar, José de Jesús and Segovia Vargas, María Jesús and Camacho Miñano, María del Mar (2022) Detection of shell companies in financial institutions using dynamic social network. Expert Systems with Applications, 207 . p. 117981. ISSN 0957-4174

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Official URL: https://doi.org/10.1016/j.eswa.2022.117981



Abstract

Shell companies work in financial interaction with other companies to commit several crimes such as concealing resources of illicit origin (money laundering), tax fraud (tax evasion), corruption, bribery, and drug trafficking, among others. This interaction can be represented by a set of nodes and connections that show the multiple relationships between entities over time. The current article proposes to detect transactions related to shell companies in financial systems, using legal person attributes and incorporating self and group comparisons into dynamic social networks. The months of June 2019, September 2020, and November 2021 are taken as evaluation periods to test the proposed methodology. Our methodology performs better than the traditional rules method, yielding balanced accuracies and true positive rates above 0.9 and 0.85, respectively. The false-positive rate was also lower in the proposed model than in the rule system for most evaluation periods. The latter translates into a reduction in costs by compliance investigations.


Item Type:Article
Additional Information:

CRUE-CSIC (Acuerdos Transformativos 2022)

Uncontrolled Keywords:Shell companies, Social networks, Crime, Dynamic, Detection
Subjects:Social sciences > Economics > Business enterprises
ID Code:73458
Deposited On:08 Jul 2022 11:05
Last Modified:08 Jul 2022 11:08

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