Interaction between decentralized financial services and the traditional banking system: A comparative analysis
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DOIhttp://dx.doi.org/10.21511/bbs.19(2).2024.05
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Article InfoVolume 19 2024, Issue #2, pp. 53-74
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This paper investigates the interaction between decentralized financial services and the traditional banking system by building VAR models, conducting Granger causality tests, building impulse response functions, and performing variance analysis. To implement the model, banking indicators of the USA, India, and Great Britain were selected: the volume of commercial and industrial loans, interest rate, consumer price index, total liabilities and capital of banks, aggregate deposits, federal funds rate (for the USA), and repo rate (for India). The study examined central bank data of the specified countries from July 2018 to January 2024 with the TVL indicator, which measures the sum of all assets locked in DeFi protocols. The results of the impulse response function (IRF) for countries demonstrate different interactions between TVL and bank indicators. The US response to TVL shocks demonstrates a stimulative monetary policy, with significant Fed rate reductions and increased commercial lending to boost economic activity. In contrast, India’s monetary stimulus, marked by declining repo rates and growth in banking sector liabilities and deposits, aims to enhance economic resilience. The UK, however, adopts a conservative monetary approach, with sharp bank rate increases and mixed lending and deposit responses, prioritizing financial stability. Analysis across these nations highlights different impacts of financial indicators on TVL. In the US, the evolving relationship between TVL and bank indicators reflects the financial system’s complexity. India’s sensitivity to monetary policy, credit conditions, and inflation significantly influences TVL. In the UK, central bank decisions, particularly the bank rate, play a crucial role in financial market dynamics.
Acknowledgment
The authors appreciate the assistance in the preparation of the article provided by the University of Debrecen Program for Scientific Publication and the János Bolyai Research Scholarship of the Hungarian Academy of Sciences.
- Keywords
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JEL Classification (Paper profile tab)G15, G18, E42
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References52
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Tables13
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Figures12
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- Figure 1. Inverse roots of AR characteristic polynomial (USA)
- Figure 2. Partial display of residual cross-correlations of model variables
- Figure 3. Response to Cholesky one S.D. (d.f. adjusted) innovations ± 2 S.E. (USA)
- Figure 4. Analysis of variance distribution for VAR model variables (USA)
- Figure B1. Inverse roots of AR Characteristic polynomial (India)
- Figure B2. Inverse roots of AR Characteristic polynomial (UK)
- Figure C1. Partial display of residual cross-correlations of model variables for India
- Figure C2. Partial display of residual cross-correlations of model variables for Great Britain
- Figure F1. Response to Cholesky one S.D. (d.f. adjusted) innovations ± 2 S.E. (India)
- Figure F2. Response to Cholesky one S.D. (d.f. adjusted) innovations ± 2 S.E. (UK)
- Figure G1. Analysis of variance decomposition for VAR model variables (India)
- Figure G2. Analysis of variance decomposition for VAR model variables (the UK)
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- Table 1. Indicators of the traditional banking system used in the study
- Table 2. Descriptive statistics of incoming (raw) data for the US
- Table 3. Residual serial correlation LM tests for the USA
- Table 4. Results of the Granger causality test (dependent variable – TVL) for the USA
- Table 5. Granger causality test results (variable TVL affects other model variables) for the USA
- Table A1. Descriptive statistics of input (raw) data for India
- Table A2. Descriptive statistics of input (raw) data for Great Britain
- Table D1. Residual serial correlation LM tests (India)
- Table D2. Residual serial correlation LM tests (UK)
- Table E1. Granger causality test results (dependent variable – TVL) for India
- Table E2. Granger causality test results (TVL variable affects other model variables) for India
- Table E3. Granger causality test results (dependent variable – TVL) for the UK
- Table E4. Granger causality test results (variable TVL affects other model variables) for the UK
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- Ahmadpour, M., Meshkany, F., & Jamshidinavid, B. (2014). Considering E-Banking Costumers Satisfaction. IOSR Journal of Humanities and Social Science, 19(5), 66-68.
- Alhanatleh, H., Khaddam, A., Abudabaseh, F., Alghizzawi, M., & Alzghoul, M., (2024). Enhancing the public value of mobile fintech services through cybersecurity awareness antecedents: A novel framework in Jordan. Investment Management and Financial Innovations, 21(1), 417-430.
- Bank for International Settlements (BIS). (2020). Annual Economic Report 2020.
- Bank of England. (2024). Official site.
- Buchak, G., Matvos, G., Piskorski, T., & Seru, A. (2018). Fintech, regulatory arbitrage, and the rise of shadow banks. Journal of Financial Economics130(3), 453-483.
- Caldarelli, G., & Ellul, J. (2021). The Blockchain Oracle Problem in Decentralized Finance – A Multivocal Approach. Applied Sciences, 11(16), 7572.
- Canales, R., & Nanda, R. (2011). A Darker Side to Decentralized Banks: Market Power and Credit Rationing in SME Lending (Working Paper No. 08-101). Harvard Business School Entrepreneurial Management.
- Carapella, F., Dumas, E., Gerszten, J., Swem, N., & Wall, L. (2022). Decentralized Finance (DeFi): Transformative Potential & Associated Risks. Finance and Economics Discussion Series.
- Carter, N., & Jeng, L. (2021). DeFi Protocol Risks: The Paradox of DeFi. PSN: Markets & Investment (Topic).
- Castro-Iragorri, C., Ramírez, J., & Vélez, S. (2021). Financial intermediation and risk in decentralized lending protocols. Banking & Insurance eJournal.
- Chainalysis. (2023). The 2023 Global Crypto Adoption Index: Central & Southern Asia Are Leading the Way in Grassroots Crypto Adoption.
- Chohan, U. (2021). Decentralized Finance (DeFi): An Emergent Alternative Financial Architecture. Econometric Modeling: International Financial Markets - Foreign Exchange eJournal.
- DefiLlama. (2024). DeFi (Decentralized Finance).
- Diep, N. T. N., & Canh, T. Q. (2022). Impact analysis of peer-to-peer Fintech in Vietnam’s banking industry. Journal of International Studies, 15(3), 173-185.
- Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error-correction: representation, estimation and testing. Econometrica, 55(2), 251-276.
- FRED. (2024). FRED data.
- Frolov, S., Ivasenko, M., Dykha, M., Heyenko, M., & Datsenko, V. (2023). Analysis of the impact of central bank digital currency on stock markets: Dynamics and implications. Banks and Bank Systems, 18(4), 149-168.
- Gaspareniene, L., Gagyte, G., Remeikiene, R., & Matuliene, S. (2022). Clustering of the European Union member states based on money laundering measuring indices. Economics and Sociology, 15(2), 153-171.
- Gudgeon, L., Werner, S., Perez, D., & Knottenbelt, W. J. (2020). DeFi Protocols for Loanable Funds: Interest Rates, Liquidity and Market Efficiency. In Proceedings of the 2nd ACM Conference on Advances in Financial Technologies (AFT ‘20) (pp. 92-112). New York, NY: Association for Computing Machinery.
- Harvey, C., Ramachandran, A., & Santoro, J. (2021). DeFi and the Future of Finance. Cambridge, MA: National Bureau of Economic Research.
- Islam, K. M. A., Hasan, Z., Tawfiq, T. T., Bhuiyan, A. B., & Faisal-E-Alam, Md. (2024). Bank becomes cashless: Determinants of acceptance of mobile banking (fintech) services among banking service users. Banks and Bank Systems, 19(2), 30-39.
- Iyer, R., Khwaja, A., Luttmer, E., & Shue, K. (2009). Screening in New Credit Markets: Can Individual Lenders Infer Borrower Creditworthiness in Peer-to-Peer Lending? AFA 2011 Denver Meetings.
- Jensen, J., Wachter, V., & Ross, O. (2021). An Introduction to Decentralized Finance (DeFi). Complex Systems Informatics and Modeling Quarterly, 26, 46-54.
- Johansen, S. (1988). Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254.
- Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration – with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169-210.
- Kaplan, B., Benli, V., & Alp, E. (2023). Decentralize finance and new lending protocols. Pressacademia, 16, 192-195.
- Khasawneh, O., & AlBahsh, R. (2024). Why do people use a mobile wallet? The case of fintech companies in Jordan. Investment Management and Financial Innovations, 21(2), 89-102.
- Kozmenko, S., & Korneev, M. (2014). Periodization of financialization process of economics: domestic and foreign contexts. Economic Annals-XXI, 9-10(1), 73-76.
- Kozmenko, S., & Savchenko, T. (2013). Development of an explicit rule of monetary policy for the economy of Ukraine. Investment Management and Financial Innovations, 10(1), 8-19.
- Kozmenko, S., Korneyev, M., & Makedon, V. (2014). Financialisation of economy and its influence on the indicators of countries’ socioeconomic development. Actual Problems of Economics, 161(11), 290-298.
- Kravitz, D., & Halverson, M. (2022). DeFi That Defies: Imported Off-Chain Metrics and Pseudonymous On-Chain Activity (Paper No. 2022/1424). IACR Cryptology ePrint Archive.
- Lumsden, E. (2017). The Future Is Mobile: Financial Inclusion and Technological Innovation in the Emerging World. Stanford Journal of Law, Business & Finance, 23(1).
- Maia, G., & Santos, J. (2021). MiCA and DeFi (‘Proposal for a Regulation on Market in Crypto-Assets’ and ‘Decentralised Finance’). Econometric Modeling: Financial Markets Regulation eJournal.
- Majumdar, S., & Gochhait, S. (2022). Risks and Solutions in Islamic Decentralised Finance. In 2022 International Conference on Sustainable Islamic Business and Finance (SIBF) (pp. 159-163). Sakhir, Bahrain.
- Makarov, I., & Schoar, A. (2022). Cryptocurrencies and Decentralized Finance (DeFi). (NBER Working Paper No. w30006).
- Morris, C. (2011). What Should Banks Be Allowed to Do. Econometric Reviews, 96(4), 55-80.
- Pakhnenko, O., Rubanov, P., Hacar, D., Yatsenko, V., & Vida, I. (2021). Digitalization of financial services in European countries: Evaluation and comparative analysis. Journal of International Studies, 14(2), 267-282.
- Prasad, A., Bhide, M., & Ghosh, S. (2002). Banking Sector Reforms: A Critical Overview. Economic and Political Weekly, 37(5), 399-408.
- Qin, K., Zhou, L., Afonin, Y., Lazzaretti, L., & Gervais, A. (2021). CeFi vs. DeFi – Comparing Centralized to Decentralized Finance. ArXiv.
- Reserve Bank of India (RBI). (2024). RBI data.
- Saengchote, K. (2021). Decentralized lending and its users: Insights from Compound. Cryptocurrency Research eJournal.
- Salami, I. (2021). Challenges and Approaches to Regulating Decentralized Finance. AJIL Unbound, 115, 425-429.
- Schär, F. (2020). Decentralized Finance: On Blockchain- and Smart Contract-based Financial Markets. SSRN.
- Schär, F. (2021). Decentralized Finance: On Blockchain- and Smart Contract-Based Financial Markets. Federal Reserve Bank of St. Louis Review, Second Quarter (pp. 153-174).
- Shkolnyk, L., Kozmenko, S., Kozmenko, O., Orlov, V., & Shukairi, F. (2021) Modeling of the financial system’s stability on the example of Ukraine. Equilibrium. Quarterly Journal of Economics and Economic Policy, 16(2), 377-411.
- Strilets, V., Frolov, S., Datsenko, V., Tymoshenk, O., & Yatsko, M. (2022). State support for the digitalization of SMEs in European countries. Problems and Perspectives in Management, 20(4), 290-305.
- Umarov, Ha., Umarov, Hu., & Umarov, T. (2022). The concept of decentralized finance (DeFi) as a current trend in the field of open decentralized protocols. Financial Analytics: Science and Experience, 15(1), 80-101.
- Wahyuni, S., Bustami, A., Fitriah, R. R. A., Fajri A. F., M. S., & Yudaruddin, R. (2024). The impact of fintech peer-to-peer lending and Islamic banks on bank performance during COVID-19. Banks and Bank Systems, 19(1), 195-207.
- Werner, S., Perez, D., Gudgeon, L., Klages-Mundt, A., Harz, D., & Knottenbelt, W. (2021). SoK: Decentralized Finance (DeFi). Proceedings of the 4th ACM Conference on Advances in Financial Technologies.
- Wronka, C. (2021). Financial crime in the decentralized finance ecosystem: new challenges for compliance. Journal of Financial Crime, 30(1), 97-113.
- Zetzsche, D., Arner, D., & Buckley, R. (2020). Decentralized Finance. Journal of Financial Regulation, 6(2), 172-203.
- Zhou, L., Xiong, X., Ernstberger, J., Chaliasos, S., Wang, Z., Wang, Y., Qin, K., Wattenhofer, R., Song, D., & Gervais, A. (2022). SoK: Decentralized Finance (DeFi) Attacks. 2023 IEEE Symposium on Security and Privacy (SP) (pp. 2444-2461).