Identifying the volatility of compliance risks for the pension custodian banks

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The high probability of risk transfer from banks to their counterparties in the field of non-state pension provision (pension account owners, non-state pension funds, insurance companies, asset management companies, etc.) determines the relevance of this study. The paper aims to develop a toolkit for identifying the compliance risk volatility for pension custodian banks based on causal modeling.
This toolkit contributes to: 1) tentative cognitive mapping of the causal relationship between the compliance risks of pension custodian banks in the field of financial monitoring and financial and reputational risks to assess their acceptability by stakeholders in non-state pension programs, and 2) impulse modeling.
The created toolkit is based on the performance data provided by Ukrainian banks, as well as on the reports of the National Bank of Ukraine. Apparently, an increase in penalty rates by 0.1% would reduce the compliance risks for banks by 0.03%, and the number of violations in financial monitoring (specifically the improper assessment/reassessment of customer risks) by 0.01%. In turn, the compliance risk volatility inherent in custodian banks affects the variability of their reputational and financial risks. Thus, reducing the compliance risks by 0.1% would improve the reputation of banks and increase their regulatory capital by 0.01%.
The study findings substantiate the use of the created toolkit to supplement the risk profile components for pension custodian banks, thereby demonstrating the potential volatility of their compliance risks and their consequences for banks and individual groups of their stakeholders.

Acknowledgment
The work is prepared and financed within the framework of the state budget research work No. 45/20202021 “Formation of a risk-oriented system of accumulative pension provision” (DR No. 0120U101508).

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    • Figure 1. Forecasted variability of compliance indicators and expectations of the bank’s counterparties in the field of non-state pension in response to the change in the amount of penalties
    • Figure 2. Forecasted variability of compliance indicators and expectations of bank’s counterparties in the non-state pension sphere affected by changes in the intrabank compliance system
    • Figure 3. Forecasted variability of compliance indicators and the bank’s counterparties’ expectations in the non-state pension sphere affected by the changes in capitalization
    • Figure A1. Cognitive map of acceptance criterion variability applicable to banks acting as pension custodians in light of the counterparties’ expectations for non-state pension provision, taking into account the impact factors (violations and measures of
    • Table 1. Analytical background for modeling banks’ compliance risks (pension custodians) in the field of financial monitoring and their consequences
    • Table 2. Formalization of compliance criteria for banks acting as pension custodians, financial monitoring measures, the extent of banks’ internal compliance and NBU regulations
    • Table B1. Matrix of mutual impact on the acceptance criteria applied to banks acting as pension custodians due to the NBU’s measures and violations committed by banks in the field of financial monitoring, as well as potential actualization of network sche
    • Conceptualization
      Svіtlana Achkasova, Olena Bezrodna, Yevheniia Ohorodnia
    • Investigation
      Svіtlana Achkasova, Olena Bezrodna
    • Methodology
      Svіtlana Achkasova, Olena Bezrodna, Yevheniia Ohorodnia
    • Supervision
      Svіtlana Achkasova
    • Validation
      Svіtlana Achkasova, Olena Bezrodna
    • Visualization
      Svіtlana Achkasova, Yevheniia Ohorodnia
    • Writing – original draft
      Svіtlana Achkasova, Yevheniia Ohorodnia
    • Writing – review & editing
      Svіtlana Achkasova, Olena Bezrodna, Yevheniia Ohorodnia
    • Data curation
      Olena Bezrodna, Yevheniia Ohorodnia
    • Formal Analysis
      Olena Bezrodna, Yevheniia Ohorodnia
    • Project administration
      Olena Bezrodna, Yevheniia Ohorodnia
    • Software
      Yevheniia Ohorodnia