Contents |
Authors:
Svitlana Andros, National Science Center «Institute of Agrarian Economics» (Ukraine) Ludmila Melnyk, Uman National University of Horticulture (Ukraine) Nataliia Butenko, National Taras Shevchenko University of Kyiv (Ukraine) Hanna Zaikina, Ukrainian State Universiti of Railway Transport (Ukraine) Volodymyr Tykhenko, Sumy State University (Ukraine).
Pages: 129-139
Language: English
DOI: https://doi.org/10.21272/mmi.2019.4-11
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Abstract
The article analyzes the rates of credit turnover by branches of the economy and by types of loans using indicators of the dynamic range, indices of average values and aggregate indicators. The purpose of the article is to provide a business case for efficiently managing credit resources in commercial banks based on a factor analysis of credit turnover by sector of the economy as a condition for optimizing a bank’s activities. The analysis of the literature shows that the management of credit resources in commercial banks is limited to the use of Western methods that are not adapted to the Ukrainian reality. The relevance of the article is the need to use the methods of economic and mathematical modeling to optimize the process of managing borrowed funds in the banking industry of Ukraine. Calculated average balances of credit investments. The article analyzes the hourly repayment of interest on loans by enterprises. Calculations of the volume of credit turnover are based on real indicators of the financial statements of Credit Agricole Bank. The study period was elected 2016-2017. Calculated the share of loans by industry in the portfolio of the bank. Defined one-day turnover on the repayment of bank loans by business entities. Calculated the duration of use of bank loans by business entities. The factors affecting the change in the rate of turnover of credit operations using the index method are analyzed. The index of the average duration of use of the loan of a constant composition is calculated. The average duration of use of bank loans by business entities has been determined. The structural change index, variable composition index, constant composition index, structure influence index are calculated. The article used the methods of factor analysis, probability theory, methods of economic and mathematical statistics. The effectiveness of borrowed funds management in the banking industry of Ukraine (on the example of Credit Agricole Bank) was confirmed by the data of a factor analysis of the loan turnover. The system of tasks solved by the proposed models includes the calculation of reasonable limits for attracting each type of resources and the effective interest rate to ensure increasing returns from the production of bank credit products and an increase in the share of the banking sector in creating the gross domestic product of the country.
Keywords: bank, effective, index, credit turnover, position, interest rate, sum, term, manager
JEL Classification: C43, E43, Е51, G21, M21.
Cite as: Andros, S., Melnyk, L., Butenko, N., Zaikina, H. & Tykhenko, V. (2019). Efficiency of management of loan funds in the banking industry of Ukraine: data of the factor analysis of credit turnover. Marketing and Management of Innovations, 4, 129-139. https://doi.org/10.21272/mmi.2019.4-11
This work is licensed under a Creative Commons Attribution 4.0 International License
References
- Andros, S.V. (2015). Formation and Implementation of the Strategy of Credit and Investment Activity of Banks: Theory, Methodology, Practice. Monograph. Kyiv: State Higher Educational Institution «University of Banking», 550.
- Annual Financial Ctatements of «Credit Agricole Bank» 2017. (2018). Available from: https://credit-agricole.ua/storage/files/credit-agricole-audit-2017-ukr.pdf (Accessed 17.04.2018).
- Athanasoglou, P.P., Brissimis, S.N, and Delis, M.D. (2008). Bank-Specific, Industry-Specific and Macroeconomic Determinants of Bank Profitability. Journal of International Financial Markets, Institutions and Money, 18(2), 121–136.
- Behr, P. and Guettler, A. (2007). Credit Risk Assessment and Relationship Lending: An Empirical Analysis of German Small and Medium-Sized Enterprises. Journal of Small Business Management, 45(2), 194–213.
- Berger, A.N. and Udell, G. (1998). The Economics of Small Business Finance: The Roles of Private Equity, Debt Markets in the Financial Growth Cycle. Journal of Banking and Finance, 22(8), 613–673.
- Brignall, T. J. S. (2007). A Financial Perspective on Performance Management. In Irish Accounting Review, 14, Iss. 1, 15–29.
- Brcak, J. (2010). Makroekonomie. Vydavatelstvi a Nakladatelstvi Ales Cenek, 292.
- Cernohorska, L. and Kula, V. (2017). The Effect of M3 Monetary Aggregates and Bank Loans on the Economic Growth of Countries in the Eurozone, the USA and Japan. Scientific Papers of the University of Pardubice. Series D. Faculty of Economics and Administration, 40 (2), XXIV, 27–38.
- Civelek, M. and Kljucnikov A. (2018). Sectoral and International Diversities in the Perception of Bank Financing: Evidence from Slovak and Czech Smes. Scientific Papers of the University of Pardubice. Series D. Faculty of Economics and Administration, 44 (3), XXVI, 53–64.
- Conti, G., Fruhwirth-Schnatter, S., Heckmanc, J.J., Piateke, R. (2014). Bayesian Exploratory Factor Analysis. In Journal of Econometrics, 183, Iss. 1, 31–57. Doi: 10.1016/j.jeconom.2014.06.008.
- Dietsch M. and Petey, J. (2002). The Credit Risk in SMEs Loans Portfolios: Modeling Issues, Pricing, and Capital Requirements. Journal of Banking and Finance, 26, 303–322.
- Dohcheva, D. (2009). Credit Rationing In Agricultural Credit Markets In Bulgaria. Trakia Journal of Sciences, 7 (3), 57–62.
- Dvorak, J., Heralecky, T., DvoraK, J. (2007). Trendy v Elektronickem Bankovnictvi. Scientific Conference on the Occasion of 15th Anniversary of the Establishment of Faculty of Business and Management Brno University of Technology, 1–5.
- Golin, J. (2001). The Bank Credit Analysis Handbook: A Guide for Analysts, Bankers and Investors. John Wiley & Sons (Asia) Pre Ltd.
- Heffernan, S. and Fu, M. (2010). Determinants of Financial Performance in Chinese Banking. Applied Financial Economics, 20(20), 1585–1600.
- Hornungova, J. and Milichovsky F. (2016). Financial Performance Evaluation of the Czech Agricultural Companies with Factor Fnalysis. Scientific Papers of the University of Pardubice. Series D. Faculty of Economics and Administration, 37 (2), XXII, 26–38.
- Jac, I., Sedlar, J., Zajcev, A. a Zajcev, V. (2013). Principles of Creating a Cost-cutting Strategy At an Enterprise by Means of the Lean Production Concept E+M. Ekonomie a management. Vyd. Liberec: Technicka Univerzita v Liberci, 75–84.
- Khalid, H.A. and Kalsom, A.W. (2014). Financing of Small and Medium Enterprises (SMEs): Determinants of Bank Loan Application. African Journal of Business Management, 8(17), 717–727.
- Kotane, I., Kuzmina-Merlino, I. (2012). Assessment of Financial Indicators for Evaluation of Business Performance. In European Integration Studies, 6, 216–224. Doi: 10.5755/j01.eis.0.6.1554.
- Lebas, M.J. (1995). Performance Measurement and Performance Management. International Journal of Production Economics, 41, Iss. 1, 23–35.
- Neely, A. (2004). Business Performance Measurement: Theory and Practice. Cambridge University Press.
- O’sullivan, D., Abela, A.V., Hutchinson, M. (2009). Marketing Performance Measurement and Firm Performance: Evidence from European High-Technology Sector. European Journal of Marketing, 43, Iss. 5/6, 843–862. Doi: 10.1108/03090560910947070.
- Polach, J., Drabek, J., Merkova, M., Polach, J. jr. (2012). Realne a Financni Investice. Vydani Praha: C.H. Beck, 280.
- Prieto, I.M., Revilla, E. (2016). Learning Capability and Business Performance: a Nonfinancial and Financial Assessment. In Learning Organization, 13, Iss. 2, 166–185. Doi: 10.1108/09696470610645494.
- Roodman, D.M. (2009). A Note on the Theme of Too Many Instruments. Oxford Bulletin of Economics and Statistics, 71(1), 135–158.
- Shih, V., Zhang, Q. and Liu, M. (2007). Comparing the Performance of Chinese Banks: a Principle Component Approach. China Economic Review, 18(1), 15–34.
- Sufian, F. and Habibullah, M.S. (2009). Bank Specific and Macroeconomic Determinants of bank Profitability: Empirical Evidence from the China Banking Sector. Frontier of Economics in China, 4(2), 274–291.
- Sulak, M., Vacik, E. (2005). Mereni Vykonnosti Firem. Praha: Eupress, 90.
- Tan, Y. and Anchor, J. (2016). Stability and Profitability in the Chinese Banking Industry: Evidence from an Auto-Regressive-Distributed Linear Specification. Journal of Investment Management and Financial Innovations, 13, Iss. 4, 155–163. Available from: https://www.researchgate.net/publication/315662520_Stability_and_Profitability_in_the_Chinese_Banking_Industry_evidence_from_an_auto-regressive-distributed_linear_specification (Accessed 07.12.2018).
- Tan, Y. and Floros, C. (2014). Risk, Profitability and Competition: Evidence from the Chinese Banking, Journal of Developing Areas, 48(3), 303–319.
- Tyrychtr, J., Ulman, M., Vostrovsky, V. (2015). Evaluation of the State of the Business Intelligence Among Small Czech farms. In Agricultural Economics, 61, Iss. 2, 63–71. Doi: 10.17221/108/2014-AGRICECON.
- Zhang, J. J., Lawrence, B., Anderson, Ch. K. (2015). An Agency Perspective on Service Triads: Linking Operational and Financial Performance. Journal of Operations Management, 35, 56–66. Doi: 10.1016/j.jom.2014.10.005.
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