Borrowing alternatives for households in Lithuania: current situation, trends and challenges


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.
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Dec 22, 2021
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Alisauskaite-Seskiene, I., Remeikiene, R., & Gaspareniene, L. (2015). The factors that determine physical entities’ borrowing: Lithuanian case. Procedia Economics and Finance, 26, 616–622.

Almenberg, J., Lusardi, A., Säve-Söderbergh, J., & Vestman, R. (2020). Attitudes toward debt and debt behavior. The Scandinavian Journal of Economics, 123(3), 780–809.

Angelucci, M., Karlan, D., & Zinman, J. (2015). Microcredit impacts: Evidence from a randomised microcredit program placement experiment by Compartamos Banco. American Economic Journal: Applied Economics, 7(1), 151–182.

Bloomberg. (2021). Mortgage boom drives biggest jump in household debt since 2013.

Boot, A. W. A. (2017). The future of banking: From scale & scope economies to fintech. European Economy: Banks, Regulation and the Real Sector, (2), 77–95.

CEIC Data. (2021). Lithuania non-performing loans ratio.

Cekanavicius, V., & Murauskas, G. (2014). Taikomoji regresine analize socialiniuose tyrimuose. Vilniaus universiteto leidykla.

Claessens, S., Turner, G., Frost, J., & Zhu, F. (2018). Fintech credit markets around the world: size, drivers and policy issues, BIS Quarterly Review.

Cloyne, J., Ferreira, C., & Surico, P. (2020). Monetary policy when households have debt: New evidence on the transmission mechanism. Review of Economic Studies, 87(1), 102–129.

Chishti, S. (2016). How peer to peer lending and crowdfunding drive the FinTech revolution in the UK. In P. Tasca, T. Aste, L. Pelizzon, & N. Perony (Eds.), Banking beyond banks and money. New economic windows. Springer, Cham.

de Roure, C., Pelizzon, L., & Tasca, P. (2017). How does P2P lending fit into the consumer credit market? SSRN.

de Roure, C., Pelizzon, L., & Thakor, A. V. (2018). P2P lenders versus banks: Cream skimming or bottom fishing? SSRN.

Demertzis, M., Merler, S., & Wolff, G. B. (2018). Capital markets union and the Fintech opportunity. Journal of Financial Regulation, 4(2), 157–165.

Demirgüç-Kunt, A., Klapper, L., Singer, D., Ansar, S., & Hess, J. (2017). The Global Findex Database 2017 – measuring financial inclusion and the fintech revolution. World Bank Group.

Ding, C., Kavuri, A. S., & Milne, A. (2021). Correction to: Lessons from the rise and fall of Chinese peer-to-peer lending. Journal of Banking Regulation, 22(2), 144.

Ding, J., Huang, J., Li, Y., & Meng, M. (2018). Is there an effective reputation mechanism in peer-to-peer lending? Evidence from China. Finance Research Letters, 30, 208–215.

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.

European Central Bank. (2017). Guidance to banks on non-performing loans.

European Central Bank. (2020). What are provisions and non-performing loan (NPL) coverage?

European Central Bank. (2021a). Household sector report.

European Central Bank. (2021b). Volumes of new euro-denominated loans to euro area households.

Faia, E., & Paiella, M. (2017). P2P Lending: Information externalities, social networks and loans’ substitution (CEPR Discussion Paper, DP12235, 65).

Federal Reserve Bank. (2021). Household debt overview.

Federal Reserve Bank of New York. (2021). Household debt and credit report.

Feginn, T., Udnesseter, M., & Einfeldt, T. (2019). An analysis of the future of peer-to-peer lending.

Ferrarini, G., & Macchiavello, E. (2017). Fintech and alternative finance in the CMU: The regulation of market place investment. Mimeo.

Financial Stability Board. (2017). Financial stability implications from fintech: Supervisory and regulatory issues that merit authorities’ attention.

Financial Times. (2015). Start-ups aim at banks’ income streams.

Foo, J., Lim, L.-H., & Wong, K. S.-W. (2017). Macroeconomics and FinTech: Uncovering latent macroeconomic effects on peer-to-peer lending.

Fuster, A., & Willen, P. S. (2017). Payment size, negative equity, and mortgage default. American Economic Journal: Economic Policy, 9(4), 167–191.

Gilchrist, S., & Mojon, B. (2018). Credit risk in the Euro area. The Economic Journal, 128(608), 118–158.

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).

International Monetary Fund. (2019). Household debt, consumption, and monetary policy in Australia.

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.

Lenz, R. (2016). Peer-to-peer lending: Opportunities and risks. European Journal of Risk Regulation, 7(4), 688–700.

Loukoianova, E., Wong, Y. C., & Hussiada, I. (2019). Household debt, consumption, and monetary policy in Australia (IMF Working Papers 076).

Lusardi, A. (2008). Financial literacy: An essential tool for informed consumer choice? SSRN.

Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5–44.

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.

Miknevicius, M. (2021). Credit history and rating: how not to damage, but to restore if damaged.

Murauskas, G., & Kregždė, A. (2015). Impact of sovereign credit risk on the Lithuanian interest rate on loans. Ekonomika, 94(2), 113–128.

Navaretti, G. B., Calzolari, G., & Pozzolo, A. F. (2018a). European economy banks, regulation, and the real sector fintech and banking. Friends or foes? SSRN.

Navaretti, G. B., Calzolari, G., & Pozzolo, A. F. (2018b). Fintech and banking. Friends or foes? SSRN.

OECD. (2021). Household debt.

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.

Robocash. (2019). 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.

Paskolų Klubas. (2021). Statistics.

P2P Market Data. (2021). Top 70 financing platforms by funding volumes. (2021). Statistics.

SEB. (2021). Financial information for 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.

Son, J. C., & Park, H. (2019). U.S. Interest rate and household debt sustainability: The case of Korea. Sustainability, 11(14), 1–16.

Swedbank. (2021). Financial results.

Tang, H. (2019). Peer-to-Peer lenders versus banks: Substitutes or complements? Review of Financial Studies, 32(5), 1900–1938.

Tarasevičienė, J. (2019). Tarpusavio skolinimas: ką reiktų žinoti investuojant ir skolinantis? Kas yra tarpusavio skolinimas? Lietuvos Bankas.

The Central Bank of Lithuania. (2019). Financial market participants – list of mutual lending platform operators.

The Central Bank of Lithuania. (2020). Mutual lending platform operator performance review.

The Central Bank of Lithuania. (2021a). Assets of financial corporations engaged in lending.

The Central Bank of Lithuania. (2021b). Banking review.

The Central Bank of Lithuania. (2021c). Consumer credit statistics.

The World Bank. (2019). Household overindebtedness in Russia.

The World Bank. (2020a). Bank non-performing loans to total gross loans (%) – Lithuania.

The World Bank. (2020b). Bank non-performing loans to total gross loans (%) – all countries and economies.

The World Bank. (2021). Domestic credit to private sector.

The World Economic Forum. (2017). Beyond FinTech: a pragmatic assessment of disruptive potential in financial service.

UK Parliament. (2021). Household debt: key economic indicators.

Valuates Reports. (2020). Peer to peer lending market by business model: global opportunity analysis and industry forecast, 2020–2027.

Vives, X. (2018). The impact of Fintech on banking. Fintech and banking: Friends of foes. In European economy: Banks, regulation and the real sector.

Wright, L., & Feng, A. (2020). COVID-19 and China’s household debt dilemma.

Yeo, E., & Jun, J. (2020). Peer-to-peer lending and bank risks: A closer look. Sustainability, 12(15), 1–17.

Zabai, A. (2017). Household debt: recent developments and challenges. BIS Quarterly Review, (December), 39–54.

Zagunis, V. (2018). Penki lietuvių skolinimosi ypatumai.

Zeng, X., Liu, L., Leung, S., Du, J., Wang, X., & Li, T. (2017). A decision support model for investment on P2P lending platform. PLoS ONE, 12(9), 1–18.