Abstract

Innovative banking supervision methods associated with the study of business models and the risk profile of banks are the top priorities. The European Banking Authority considers the business model as a set of tools and methods to organize work, generate profits, and sustain growth. For the first time, the European Central Bank introduced the assessment of the viability of business models and profitability factors as a supervisory priority. Appropriate mathematical tools are needed to identify business models and assess bank risks. It is necessary to use specific supervisory approaches and adequate measures of influence for different business models of banks. It is proposed to distribute jars to separate homogeneous structural-functional groups. Structural and functional analysis of the banking system is a special method for analysing qualitative changes through quantitative indicators of bank reports. Comparison of structural characteristics with previous reporting periods allows you to set changes for each group of banks, the relationship between groups. The basis of the analysis is the observation of the location and trajectory of each bank on the self-organized map Kohonen. Neighbouring banks on the map have similar characteristics of financial stability. The method allows considering a significant number of indicators for the formation of homogeneous groups of banks. A recent survey shows a reduction in banks in the central part of the map, which does not have significant deviations from the average characteristics of assets, liabilities, income and expenses. At the same time, banks with a high share of current resources are growing. Current resources do not provide the necessary sources for the development of bank loans. An important modern trend in the development of the banking services market is the growth of a group of banks that place assets in government securities. The activities of a large number of banks are associated with currency risks.

Keywords: Structural-functional analysis as innovation in public governance (case of of banking supervision in Ukraine)

JEL Classification: C45, G21.

Cite as: Zarutska, E., Pavlova, T., & Sinyuk, A. (2018). Structural-functional analysis as innovation in public governance (case of banking supervision). Marketing and Management of Innovations, 4, 349-360. https://doi.org/10.21272/mmi.2018.4-30

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

References

1. SREP (supervisory review and evaluation process): Blessing or curse? Available at: https://www.bankinghub.eu.
2. Recent trends in euro area banks’ business models and implications for banking sector stability (2016). Financial Stability Review. Available at: https://www.ecb.europa.eu/pub/pdf/other/sfcfinancialstabilityreview201605.en.pdf?ecb712f83f124c11f45abe4e48cac2d0.
3. National Bank of Ukraine, NBU (2018). The Resolution of the NBU No. 64, 11 June 2018. Available at: https://bank.gov.ua/document/download?docId=71600453.
4. National Bank of Ukraine, NBU (2018). NBU Introduces New Requirements to Risk Management System Organization in Banks. Available at: https://bank.gov.ua.
5. National Bank of Ukraine, NBU (2018). The Resolution of the NBU No 47, May 2, 2018. Available at: http://zakon.rada.gov.ua/laws/show/z0703-01.
6. National Bank of Ukraine, NBU (2018). An analysis of business models of banks within the Supervisory review and evaluation process (SREP). Available at: https://bank.gov.ua/doccatalog/document?id=69900832.
7. Osterwalder, A., Pigneur, Y. (2009). Business Model Generation. Available at: http://radio.shabanali.com/business-model-generation-osterwalder.pdf.
8. Chesbrough H., Rosenbloom R.S. (2002). The role of the business models capturing value from innovation: evidence from Xerox Corporation’s technology spin-off companies. Industrial and Corporate Change, Jun 2002, 11, 3. Available at: http://www.sem.tsinghua.edu.cn/semcms_com_www/upload/home/store/2008/7/3/2969.pdf.
9. Investopedia. (n. d.). Аvailable at: http://www.investopedia.com.
10. Ayadi R. and De Groen W. Pieter (2014). Banking Business Models Monitor 2014: Europe, Journal of CEPS Paperbacks. Аvailable at: https://ssrn.com/abstract=2510323.
11. Ayadi R. et al. (2015). Banking business model monitor 2015: Europe. Centre for European Policy Studies and International Observatory on Financial Services Cooperatives. Available at: https://ssrn.com/с abstract=2784334.
12. Ayadi R., Arbak E. and De Groen W. Pieter (2014). Business Models in European Banking: A Pre-and Post-Crisis Screening, Center for European Policy Studies. Аvailable at: http://rymayadi.com/wp-content/uploads/2014/11/Business-Models-in-European-Banking.pdf.
13. Ayadi R. Arbak E. and De Groen W. Pieter (2012). Regulation of European Banks and Business Models: Towards a New Paradigm? Centre for European Policy Studies, Forth-coming. Аvailable at: https://ssrn.com/abstract=2098974.
14. Mergaerts, F., Vennet, R. V. (2015). Business models and bank performance. A long-term perspective. 4th EBA Policy Research Workshop. Available at: https://www.eba.europa.eu/documents/10180/1018121/Mergaerts%2C%20Vander+Vennet+-+Business+models+and+bank+performance.+A+long+term+perspective+-+Paper.pdf.
15. Tomkus, M. (2014). Identifying Business Models of Banks: Analysis of Biggest Banks from Europe and the United States of America. Aarhus: Business and Social Sciences. Аvailable at: http://pure.au.dk/portal-asb-student/fi les/69715984/be_apendixu.pdf.
16. Altunbas, Y., Manganelli, S., Marques-Ibanez, D. (2011). Bank risk during the financial crisis: do business models matter? Available at: https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1394.pdf.
17. Lyubich O., Bortnikov H., Panasenko H. (2016). Analysis business model of state banks in Ukraine, Finance of Ukraine, 10, 7-38.
18. Elena Zarutska. Structural-functional analysis of the Ukraine banking system // Financial Markets, Institutions and Risks, Volume 2, Issue 1, 2018. Pages: 79-96 DOI: 10.21272/fmir.2(1).79-96.2018.
19. European Central Bank, ECB (2014). Guide to banking supervision. Available at: https://www.bankingsupervision.europa.eu/ecb/pub/pdf/ssmguidebankingsupervision201411.en.pdf?807838fa2a8bb958749f411c432d1f3e.
20. European Central Bank, ECB (2017). SSM SREP Methodology Booklet. Available at: https://www.bankingsupervision.europa.eu/ecb/pub/pdf/ssm.srep_methodology_booklet_2017.en.pdf?508ca0e386f9b91369820bc927863456.
21. Basel Committee on Banking Supervision, BCBS (2000). Principles for the Management of Credit Risk. Available at: http://www.bis.org/publ/bcbs75.pdf.
22. Basel Committee on Banking Supervision, BCBS (2008). Principles for sound liquidity risk management and supervision. Available at: http://www.bis.org/publ/bcbs144.pdf.
23. National Bank of Ukraine, NBU (2018). Shock Contagion, Asset Quality and Lending Behavior. Available at: https://bank.gov.ua/doccatalog/document?id=62899125.
24. National Bank of Ukraine, NBU (2017). Secular Stagnation: Policy Options and the Cyclical Sensitivity in Estimates of Potential Output. Available at: https://bank.gov.ua/doccatalog/document?id=48800101.
25. Kohonen, T. (2001). Self-Organizing Maps. Berlin Heidelberg: Springer-Verlag.
26. Kohonen, T (2013). Essentials of the self-organizing map. Neural Networks, 37, 52-65.
27. Severin. E. (2010). Self-organizing maps in corporate finance: Quantitative and qualitative analysis of debt and leasing, Neurocomputing, 73 (10-12), 2061-2067.
28. AghaeiRad, A., Chen, N. and Ribeiro, B. (2017). Improve credit scoring using transfer of learned knowledge from self-organizing map, Neural Computing & Applications, 28 (6), 1329-1342.
29. Tkac, M. and Verner, R. (2015). Artificial neural networks in business: Two decades of research, Applied Soft Computing, 38, 788-804.
30. Sarlin, P and Peltonen, T. (2013). Mapping the state of financial stability» Journal Of International Financial Markets Institutions & Money, 26, 46-76.
31. Severin, E (2012). Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time» European Journal Of Operational Research, 221 (2), 378-396.
32. Rutherford, M.W. (2016). Proposing a Financial Legitimacy Threshold in Emerging Ventures: A Multi-Method Investigation. Group & Organization Management, 41, (6), 751-785.
33. Koc, Elcin K et al. (2014). Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance. Journal Of Global Optimization, 60(1), 103-120.
34. Jarvinen, J., Linnakangas, J (2012) Firm Capabilities in the Finnish Forest Cluster: Comparisons Based on Self-Organizing Map. Silva Fennica, 46(1), 131-150.
35. Lin, W.Y., Hu, Y.H. and Tsai, C.F. (2012). «Machine Learning in Financial Crisis Prediction: A Survey». Ieee Transactions On Systems Man And Cybernetics Part C-Applications And Reviews, 42(4), 421-436.
36. Hsu, C.M. (2012). A hybrid procedure for stock price prediction by integrating self-organizing map and genetic programming, Expert Systems With Applications, 38(11), 14026-14036.
37. Beltratti, A. and Stulz, R.M., (2012). The credit crisis around the globe: Why did some banks perform better? Journal of Financial Economics, 105(1), 1-17.
38. Huang, X., Zhou H. and Zhu H. (2011). Systemic Risk Contributions, Federal Reserve Board Finance and Economics Discussion Series 2011-08.
39. Drehmann, M. and Tarashev, N. (2011). Systemic Importance: Some Simple Indicators, Bank for International Settlements Quarterly Review, Bank for International Settlements, March.
40. Brownlees, C.T. and Engle R.F. (2010). Volatility, Correlation and Tails for Systemic Risk Measurement. Available at SSRN: http://ssrn.com/abstract=1611229.
41. Boot, A. and Thakor, A.V. (2010). The Accelerating Integration of Banks and Markets and its Implications for Regulation, in A. Berger, P. Molyneux and J. Wilson (eds.), The Oxford Handbook of Banking, 58-90.
42. Bekaert, G., Ehrmann, M., Fratzscher, M. and Mehl, A. (2011). Global Crises and Equity Market Contagion. Available at: http://ssrn.com/abstract=1856881.
43. Acharya, V., Cooley T., Richardson M. and Walter I. (2010). Manufacturing Tail Risk: A Perspective on the Financial Crisis of 2007-09, Foundations and Trends in Finance, 4, 247-325.
44. Berger, A. and Bouwman C. (2010). How Does Capital Affect Bank Performance During Financial Crises? Wharton Financial Institutions Center Working Paper, 11-22.
45. De Jonghe, O. (2010). Back to the Basics in Banking? A Micro-analysis of Banking System Stability, Journal of Financial Intermediation, 19(3), 387-417.
46. Maddaloni, A. and Peydró J.L. (2011). Bank Risk Taking, Securitization, Supervision, and Low Interest Rates: Evidence from Lending Standards, Review of Financial Studies, 24(6), 2121-2165.
47. Baele, L., De Jonghe, O., and Vander Vennet, R. (2007). Does the stock market value bank diversification? Journal of Banking and Finance, 31(7), 1999-2023.
48. Hasan, I., Lozano-Vivas, A. and Pastor, J.T. (2001). European bank performance beyond country borders: what really matters? European Finance Review, 5(2), 141-165.
49. Billio, M., Getmansky, M., Lo, A.W. and Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors, Journal of Financial Economics, 104(3), 535-559.
50. Brandt, M.W., Brav, A., Graham, J. and Kumar, A. (2010). The idiosyncratic volatility puzzle: time trend or speculative episodes? Review of Financial Studies, 23(2), 863-899.
51. Coughlan, J., Shale, E. and Dyson, R. (2010). Including the customer in efficiency analysis: evidence of a hybrid relational-transactional approach”, International Journal of Bank Marketing, 28(2), 136-149.
52. Greenwood, R., Landier, A. and Thesmar, D. (2015). Vulnerable banks, Journal of Financial Economics, 115(3), 471-485.
53. Hays, F., de Lurgio, S. and Gilbert, A. (2009). Efficiency ratios and community bank performance, Journal of Finance and Accountancy, 1(1), 1-15.
54. Paleologo, G., Elisseeff, A. and Antonini, G. (2010). Subagging for credit scoring models”, European Journal of Operational Research, 201(2), 490-499.
55. Petersen, M. (2009). Estimating standard errors in finance panel data sets: comparing approaches, Review of Financial Studies, 22(1), 435-480.
56. Pistol, G. (2010). The role and importance of the strategic planning in bank marketing”, Аnnals of Spiru Haret University. Economic Series, 1(2), 153-161.
57. Zheng, D., Zhang, Y. and Wen, L. (2012). The credibility models with time changeable effects, Journal of Jiangxi Normal University: Natural Science Edition, 36(1), 249-252.
58. Köhler M. (2015). Which banks are more risky? The impact of business models on bank stability, Journal of Financial Stability, 16, 195-212.
59. Khmarskyi V. Relation between marketing expenses and bank’s financial position: Ukrainian reality / V. Khmarskyi, R. Pavlov // Benchmarking: An International Journal. – 2017. – Vol. 24, Iss. 4. – Р. 903–933. doi:10.1108/BIJ-02-2016-0026.
60. Laeven L. (2013)/ Corporate governance: What’s special about banks? Annual Review of Financial Economics, 5, 63-92.
61. Roengpitya, R. (2014). Bank business models, Bank for International Settlements. Available at: http://www.imf.org/external/pubs/ft/sdn/2014/sdn1404.pdf.