Search for statistically approved criteria for identifying money laundering risk


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The paper focuses on the theoretical justification and theoretical foundations of using statistical criteria for identifying money laundering risk as a tool to prevent and counteract the legalization of bank clients’ proceeds.
The hypothesis is that the coefficient of variation can be appropriately used as an identifier for money laundering risk. To prove this hypothesis, a special methodology was used: generalization, grouping, statistical analysis of time series, and correlation analysis – to identify and analyze the hidden signs of the customer income legalization in the financial activities of a bank; mathematical statistics and scaling – to determine the quantitative values of risk levels for the use of bank services for legalizing customer income. The analysis of financial activities of 32 Ukrainian banks aimed at identifying money-laundering risks showed that banks in which the National Bank of Ukraine revealed suspicious transactions with money-laundering features (16 operating banks) had much higher coefficients of variation in the volume of cash flows, in cash flows for on-demand accounts of economic entities, in cash flows of on-demand accounts for individuals, compared with banks in which violations of legislation in the field of financial monitoring were revealed (eight banks), and with banks where violations were not found (eight banks). This proves that sudden changes in customer transaction volume can be a sign of money laundering risk.

State grant for fundamental scientific research “Risk-oriented approach in countering money laundering, terrorist financing and proliferation of weapons of mass destruction” (state registration number 0118U000058).

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    • Table 1. Generalized information on inspections of banks by the NBU and enforcement measures applied to them for violation of legal requirements on financial monitoring
    • Table 2. Statistical characteristics of the dynamics of cash turnover and funds on on-demand accounts from September 1, 2017 to April 1, 2019 for JSC “JSCB “CONCORD”
    • Table 3. Shapiro-Wilk test value for 20 observations
    • Table 4. Coefficients of pairwise correlation between indicators of cash and non-cash flows of clients of JSC “JSCB “CONCORD”
    • Table 5. Statistical characteristics of the dynamics of cash turnover and funds on the on-demand accounts from September 1, 2017 to April 1, 2019 for JSC “ASVIO BANK”
    • Table 6. Generalized results of calculating the coefficient of variation of cash flow by cash registers and accounts on demand of bank customers for the period August 2017 – May 2019
    • Conceptualization
      Olesia Lebid
    • Methodology
      Olesia Lebid
    • Project administration
      Olesia Lebid
    • Software
      Olesia Lebid
    • Validation
      Olesia Lebid
    • Visualization
      Olesia Lebid
    • Writing – review & editing
      Olesia Lebid
    • Data curation
      Oleksandr Veits
    • Formal Analysis
      Oleksandr Veits
    • Investigation
      Oleksandr Veits
    • Writing – original draft
      Oleksandr Veits