Borrowing alternatives for households in Lithuania: current situation, trends and challenges
Abstract
Purpose – to analyse the main borrowing alternatives available to Lithuanian households and the credit market as a whole, focusing on its peer-to-peer (P2P) segment, the forecast of its growth, and possible challenges.
Research methodology – the research methods applied were scientific literature analysis, statistical data analysis, comparative analysis, correlation-regression analysis, linear trend forecasting method.
Findings – the prevailing borrowing alternative for Lithuanian households still remain bank credits. Besides, borrowing from P2P market is becoming more and more popular. Although the macroeconomic environment for all the credit market segments is the same, the P2P segment is developing significantly faster. If this trend remains unchanged, the whole credit market is likely to face challenges, such as the growth of overdue loans, insolvent customers, the rising share of non-performing-loans (NPL), etc., that may affect its overall stability.
Research limitations – the empirical study relies on the country’s macroeconomic indicators that influence household borrowing. Such factors as borrower’s age, income level, marital status and others were not taken into account in this study. The forecast of the P2P segment growth of the consumer credit market and comparison with its banking segment is based on the analysis of 4 years of real monthly statistics for both segments.
Practical implications – the performed analysis and its results can be useful for the future research within the household borrowing trends, especially in Peer-to-Peer platforms, and specifically for the Central Bank, the Ministry of Finance and other institutions that regulate the credit market, as it provides information on modern borrowing trends and the challenges it might bring. Also, for P2P platforms themselves, planning and further developing their activities and adjusting lending conditions with the aim to attract higher-quality customers.
Originality/Value – household borrowing, the credit market and the P2P platforms are widely analysed by both academics and financial institutions, such as central banks. However, it is mainly limited to the analysis of statistical data and does not pay attention to possible market development issues. This study focuses on the analysis of the growth trends of the P2P market and the potential challenges that may arise thereafter.
Keyword : household borrowing, modern borrowing trends, credit market, commercial banks, P2P segment, overdue loans, non-performing loans
How to Cite
Taujanskaitė, K., & Karklytė, I. . (2021). Borrowing alternatives for households in Lithuania: current situation, trends and challenges. Business, Management and Economics Engineering, 19(2), 389-411. https://doi.org/10.3846/bmee.2021.13986
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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de Roure, C., Pelizzon, L., & Tasca, P. (2017). How does P2P lending fit into the consumer credit market? SSRN. https://doi.org/10.2139/ssrn.2848043
de Roure, C., Pelizzon, L., & Thakor, A. V. (2018). P2P lenders versus banks: Cream skimming or bottom fishing? SSRN. https://doi.org/10.2139/ssrn.3174632
Demertzis, M., Merler, S., & Wolff, G. B. (2018). Capital markets union and the Fintech opportunity. Journal of Financial Regulation, 4(2), 157–165. https://doi.org/10.1093/jfr/fjx012
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Dorfleitner, G., Oswald, E. M., & Zhang, R. (2021). From credit risk to social impact: On the funding determinants in interest-free peer-to-peer lending. Journal of Business Ethics, 170(2), 375–400. https://doi.org/10.1007/s10551-019-04311-8
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Ferrarini, G., & Macchiavello, E. (2017). Fintech and alternative finance in the CMU: The regulation of market place investment. Mimeo. https://doi.org/10.1093/oso/9780198813392.003.0010
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Foo, J., Lim, L.-H., & Wong, K. S.-W. (2017). Macroeconomics and FinTech: Uncovering latent macroeconomic effects on peer-to-peer lending. http://arxiv.org/abs/1710.11283
Fuster, A., & Willen, P. S. (2017). Payment size, negative equity, and mortgage default. American Economic Journal: Economic Policy, 9(4), 167–191. https://doi.org/10.1257/pol.20150007
Gilchrist, S., & Mojon, B. (2018). Credit risk in the Euro area. The Economic Journal, 128(608), 118–158. https://doi.org/10.1111/ecoj.12427
Hartmann, M., Hernandez-van Gijsel, L., Plooij, M., & Vandeweyer, Q. (2019). Are instant payments becoming the new normal? A comparative study (ECB Occasional Paper Series 229). https://doi.org/10.2139/ssrn.3441654
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Kurniasari, F., & Utomo, P. (2021). Determinants of effectiveness repayment apps at P2P lending platform during Covid 19 pandemic in Indonesia. Ultimaccounting: Jurnal Ilmu Akuntansi, 13(1), 156–172. https://doi.org/10.31937/akuntansi.v13i1.2094
Lenz, R. (2016). Peer-to-peer lending: Opportunities and risks. European Journal of Risk Regulation, 7(4), 688–700. https://doi.org/10.1017/S1867299X00010126
Loukoianova, E., Wong, Y. C., & Hussiada, I. (2019). Household debt, consumption, and monetary policy in Australia (IMF Working Papers 076). https://doi.org/10.5089/9781498303767.001
Lusardi, A. (2008). Financial literacy: An essential tool for informed consumer choice? SSRN. https://doi.org/10.2139/ssrn.1336389
Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5–44. https://doi.org/10.1257/jel.52.1.5
Mansilla-Fernández, J. M. (2018). A bird eye (re)view of key readings. In Fintech and banking: Friends or foes. European economy: Banks, regulation, and the real sector. https://european-economy.eu/wp-content/uploads/2018/01/EE_2.2017-2.pdf
Miknevicius, M. (2021). Credit history and rating: how not to damage, but to restore if damaged. https://www.vz.lt/mano-pinigai/2021/01/19/kredito-istorija-ir-reitingas-kaip-nesusigadinti-o-sugadinus-atstatyti
Murauskas, G., & Kregždė, A. (2015). Impact of sovereign credit risk on the Lithuanian interest rate on loans. Ekonomika, 94(2), 113–128. https://doi.org/10.15388/Ekon.2015.2.8236
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Navaretti, G. B., Calzolari, G., & Pozzolo, A. F. (2018b). Fintech and banking. Friends or foes? SSRN. https://doi.org/10.2139/ssrn.3099337
OECD. (2021). Household debt. https://data.oecd.org/hha/household-debt.htm
Oh, E.Y., & Rosenkranz, P. (2020). Determinants of peer-to-peer lending expansion: The roles of financial development and financial literacy (Working Paper No. 613). Asian Development Bank Economics. SSRN. https://doi.org/10.22617/WPS200107-2
Robocash. (2019). How does P2P lending affect banking? https://robo.cash/articles/how_does_p2p_lending_affect_banking
Papoušková, M., & Hajek, P. (2020). Modelling loss given default in peer-to-peer lending using random forests. In I. Czarnowski, R. Howlett, & L. Jain. (Eds.), Intelligent Decision technologies 2019. Springer, Singapore. https://doi.org/10.1007/978-981-13-8311-3_12
Paskolų Klubas. (2021). Statistics. https://www.paskoluklubas.lt/statistika
P2P Market Data. (2021). Top 70 financing platforms by funding volumes. https://p2pmarketdata.com
Savy.lt. (2021). Statistics. https://gosavy.com/lt/statistika/
SEB. (2021). Financial information for investors. https://www.seb.lt/en/about-seb/investors
Siemionek-Ruskań, M., & Fanea-Ivanovici, M. (2021). Peer-to-peer lending: evolution and trends. In D. Procházka (Eds.), Digitalization in finance and accounting. ACFA 2019. Springer proceedings in business and economics. Springer, Cham. https://doi.org/10.1007/978-3-030-55277-0_2
Son, J. C., & Park, H. (2019). U.S. Interest rate and household debt sustainability: The case of Korea. Sustainability, 11(14), 1–16. https://doi.org/10.3390/su11143759
Swedbank. (2021). Financial results. https://www.swedbank.lt/about/swedbank/about/financialResults
Tang, H. (2019). Peer-to-Peer lenders versus banks: Substitutes or complements? Review of Financial Studies, 32(5), 1900–1938. https://doi.org/10.1093/rfs/hhy137
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