Money laundering risk management tools based on determining the level of co-ordination of financial companies and credit unions

  • Received December 1, 2018;
    Accepted December 18, 2018;
    Published February 4, 2019
  • Author(s)
  • DOI
  • Article Info
    Volume 16 2018, Issue #4, pp. 40-51
  • Cited by
    2 articles

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

The article proposes a tool for managing money laundering risk based on the definition of the level of coherence of financial companies and credit unions, the application of which will contribute to introduction of a risk-based approach to anti-money laundering, terrorist financing and proliferation of weapons of mass destruction. It was revealed that among the investigated during 2010-2017 financial corporations and credit unions there are financial conglomerates. This confirms the existence of close ties between them. Associated financial companies and credit unions may form or join networks that can be used for possible money laundering. It was established that the share of connected credit unions and financial companies corresponds to the principle of Pareto – 20:80. The proposed methodological support allowed selecting a large number of independent credit unions and financial companies. This will help to prevent the impact of the risk of connected individuals on the high ability of the borrower to fulfill their loan obligations and not to be involved in processes for money laundering using networks. Meanwhile, dedicated joint financial institutions belong to a high-risk group for controlling their financial operations to prevent the legalization of proceeds from crime.

view full abstract hide full abstract
    • Рисунок 1. Загальний вид не орієнтовного графа зв’язків для фінансових компаній
    • Рисунок 2. Загальний вид не орієнтовного графа зв’язків для КС
    • Таблиця 1. Етапи оцінки рівня зв’язності фінансових компаній та кредитних спілок
    • Таблиця 2. Розраховані середні показники за множинами фінансових установ
    • Таблиця 3. Ранги коефіцієнтів зв’язності з корекцією за фінансовими компаніями та кредитними спілками
    • Таблиця 4. Кількість зв’язків фінансових компаній та кредитних спілок між собою у 2017 році
    • Таблиця 5. Підсумковий аналіз отриманих даних щодо зв’язності фінансових установ