Modeling the dynamic patterns of banking and non-banking financial intermediaries’ performance
-
DOIhttp://dx.doi.org/10.21511/bbs.17(1).2022.05
-
Article InfoVolume 17 2022, Issue #1, pp. 49-66
- Cited by
- 919 Views
-
370 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Nowadays, there are many preconditions and circumstances for conducting shadow schemes in the financial market. Therefore, the level of risk of participation of bank and non-bank financial intermediaries in such schemes is assessed as high. The lack of a practical methodology for assessing the development trajectory of financial intermediaries raises the question of the need for preventive control and quality modeling of their growth dynamics. The study aims to identify and formalize the patterns of development paths of banking and non-banking financial intermediaries based on the Harrington desirability function, which will be used to identify risk patterns as indicative patterns of financial intermediaries’ participation in shadow schemes. The sample includes 13 banking institutions, 3 credit unions, 3 pawnshops, 3 insurance companies, and 3 financial companies. The obtained results showed the relationship between the financial intermediary risk level in terms of its participation in shadow schemes and the phases of the economic cycle as a catalyst for the economic dynamics of the formal and informal economy. Thus, in 2012–2015, most financial intermediaries were in the zone of most significant risk, especially banks, characterized by economic, social, and political instability. Today, banks are in the group with a controlled level of risk of participation in scheme operations. Over the years analyzed, a stable neutral level of risk of participation in shadow schemes was inherent in most non-bank financial institutions. They were less sensitive than banks to the phases of the economic cycle.
Acknowledgment
Alina Bukhtiarova and Yevgeniya Mordan gratefully acknowledge financial support from the Ministry of Education and Science of Ukraine (0120U100473, 0121U100469).
- Keywords
-
JEL Classification (Paper profile tab)G17, G21, G23, O17
-
References21
-
Tables16
-
Figures5
-
- Figure 1. Kohonen maps obtained
- Figure 2. General Kohonen map
- Figure 3. New Kohonen map with conditional financial intermediaries
- Figure 4. Obtained Kohonen maps by groups of indicators, considering conditional financial intermediaries
- Figure A1. Development patterns of financial intermediaries’ trajectories
-
- Table 1. List of financial intermediaries included in the model as of January 1, 2021
- Table 2. Description of input model variables
- Table 3. Description of intermediate model variables
- Table 4. Description of Pivdennyi Bank’s indicators as of January 1, 2021
- Table 5. Synthesis function G for each group of indicators as of January 1, 2021
- Table 6. Financial intermediaries included in pattern C1
- Table 7. Distribution of points for cluster evaluation
- Table 8. Cluster rank formation
- Table 9. Cluster rating
- Table 10. Assessment of financial intermediaries by groups within clusters
- Table 11. Cluster rank formation
- Table 12. Cluster ranking
- Table 13. Assessment of conditional financial intermediaries by new groups within clusters
- Table 14. Financial intermediaries of the newly formed pattern C7
- Table 15. Financial intermediaries of the newly formed pattern C5
- Table 16. A set of development patterns of financial intermediaries’ trajectories according to the probability of participation in shadow operations
-
- Aramonte, S., Schrimpf, A., & Hyun Song Shin. (2021). Non-bank financial intermediaries and financial stability (BIS Working Papers No. 972). Bank for International Settlements.
- Boda, M., & Zimkova, E. (2018). Measuring financial intermediation: a model and application to the Slovak banking sector. EaM: Ekonomie a Management, 21(3), 155-170.
- Frolov S., & Shukairi, F. (2020). Bank-centric nature of the financial system of Ukraine: analysis of the current situation. Banks and Bank Systems, 15(3), 184-198.
- Ghasemi, A., Akbari M. B., & Tavakolian, H. (2020). A Study of the Financial Instability and Banking Intermediaries by Using a DSGE Modeling Approach. Iranian Economic Review, 24(4), 1025-1047.
- Harrington, E. C. (1965). The Desirability Function. Industrial Quality Control, 21, 494-498.
- Hughes, J. P., & Mester, L. J. (2018). The Performance of Financial Institutions: Modeling, Evidence, and Some Policy Implications. Oxford Handbook of Banking (3rd ed.). Forthcoming.
- Islam, M., & Shah, J. S. A. (2012). An Empirical Analysis of Causality between Development of Non-Bank Financial Intermediaries and the Economic Growth in Malaysia. European Journal of Social Sciences, 30(4), 654-664.
- Kohonen, T. (1982). Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43, 59-69.
- Kozmenko, S., Shkolnyk, I., & Bukhtiarova A. (2016). Dynamics patterns of banks evaluations on the basis of Kohonen self-organizing maps. Banks and Bank Systems, 11(4-1), 179-192.
- Martinez-Miera, D., & Repullo, R. (2019). Markets, Banks, and Shadow Banks (ECB Working Paper No. 2234).
- Miles, W. (2011). The Role of Non-Bank Financial Intermediaries in Propagating Korea’s Financial Crisis. Review of Pacific Basin Financial Markets and Policies, 6(1), 45-64.
- Oliynyk, V., Zhuravka, F., Bolgar, T., & Yevtushenko, O. (2017). Optimal control of continuous life insurance model. Investment Management and Financial Innovations, 14(4), 21-29.
- Ozgur, G. (2021). Shadow banking and financial intermediation. Metroeconomica, 72(4), 731-757.
- Pantielieieva, N., Rogova, N., Zaporozhets, S., & Tretiak, N. (2020). Transformation in the ecosystem of financial intermediaries in the context of digitalization. Scientific Bulletin of Polissia, 1, 49-59.
- Plastun, A., Makarenko, I., & Balatskyi, Ye. (2018). Competitiveness in the Ukrainian stock market and local crisis of 2013–2015. Investment Management and Financial Innovations, 15(2), 29-39.
- Reverchuk, S., Vovchak, O., Yavorska, T., Voytovych, L., & Irshak, O. (2020). Investment activities of banks, insurance companies, and non-government pension funds in Ukraine. Investment Management and Financial Innovations, 17(2), 353-363.
- Santandrea, M., Agasisti, T., Giorgino, M., & Patrucco, A. S. (2018) Business models in the search for efficiency: the case of public financial intermediaries. Public Money & Management, 38(3), 234-243.
- Shkolnyk, I., Frolov, S., Orlov, V., Dziuba, V., & Balatskyi, Ye. (2021). Influence of world stock markets on the development of the stock market in Ukraine. Investment Management and Financial Innovations, 18(4), 223-240.
- Shkolnyk, I., Kozmenko, O., Nowacki, R., & Mershchii, B. (2020). Dependence of the state of public finances on their transparency and the level of corruption in a country. Economics and Sociology, 13(4), 281-296.
- Tiutiunyk, I., & Humenna, Yu. (2021). Role of Financial Intermediaries in Shadow Schemes: Risk-Based Approach. Financial Markets, Institutions and Risks, 5(3), 87-92.
- Yang, Chi-Chun, & Chang, Ya-Kai. (2020). Asymmetric Impact of Financial Intermediary Development in Low- and High-Income Countries. Sustainability, 12(15), 5960.