Bridging the Agility Gap: A Strategic Framework for Commercial Banks to Enter the Un-Banked Lending Market
DOI:
https://doi.org/10.46799/adv.v4i9.637Keywords:
API-driven ecosystem financing model, information asymmetry, unbanked MSMEsAbstract
Extending sustainable finance to Indonesia’s unbanked Micro, Small, and Medium Enterprise (MSME) sector presents a structural paradox. Traditional commercial banks possess a significant competitive advantage through access to low-cost capital, yet they are consistently disintermediated by fintech disruptors that offer faster services despite charging higher interest rates. This research investigates the root causes of this market displacement based on the theories of Information Asymmetry and Transaction Cost Economics (TCE). By integrating empirical data from a Principal Component Analysis (PCA) of MSME market demands and an Analytic Hierarchy Process (AHP) of banking executive priorities, this study identifies the specific areas where conventional banking models fail to meet market expectations. It develops a 12-cell Strategic Alignment Matrix that reveals a critical agility gap. To address this challenge, this paper proposes a paradigm shift toward an API-driven, B2B2C (Business-to-Business-to-Customer) Ecosystem Financing Model. This redesigned business process leverages open banking, smart contract automation, and closed-loop disbursement mechanisms to achieve fintech-level service speed. By systematically reducing operational costs through technology integration, banks can accommodate a realistic 4.5% Non-Performing Loan (NPL) rate while maintaining the risk tolerance required for sustainable and accelerated financial inclusion.
References
Allen, F., Qian, M., & Xie, J. (2019). Understanding informal financing. Journal of Financial Intermediation, 39, 19–33. https://doi.org/10.1016/j.jfi.2018.06.001
Aulia, R. N., & Murwaningsari, E. (2024). A comparative study of sustainable finance regulation and implementation: Indonesia vs. global practice. Journal of Finance and Business Digital, 3(2), 129–142. https://journal.formosapublisher.org/index.php/jfbd/article/view/12986
Boot, A. W. A., Hoffmann, P., Laeven, L., & Ratnovski, L. (2021). Fintech: What's old, what's new? Journal of Financial Stability, 53, 100836. https://doi.org/10.1016/j.jfs.2020.100836
Chen, X. (2022). Credit risk assessment of small and medium-sized enterprises under the financial model of online supply chain. Discrete Dynamics in Nature and Society, 2022, Article 7733395. https://doi.org/10.1155/2022/7733395
Cornelli, G., Frost, J., Gambacorta, L., Rau, P. R., Wardrop, R., & Ziegler, T. (2023). Fintech and big tech credit: Drivers of the growth of digital lending. Journal of Banking & Finance, 148, 106742. https://doi.org/10.1016/j.jbankfin.2022.106742
Djeundje, V. B., Crook, J., Calabrese, R., & Hamid, M. (2021). Enhancing credit scoring with alternative data. Expert Systems with Applications, 163, 113766. https://doi.org/10.1016/j.eswa.2020.113766
Gambacorta, L., Huang, Y., Li, Z., Qiu, H., & Chen, S. (2023). Data versus collateral. Review of Finance, 27(2), 369–398. https://doi.org/10.1093/rof/rfac051
Gopal, M., & Schnabl, P. (2022). The rise of finance companies and FinTech lenders in small business lending. The Review of Financial Studies, 35(11), 4859–4901. https://doi.org/10.1093/rfs/hhab126
Huang, Y., Li, Z., Qiu, H., Tao, S., Wang, X., & Zhang, L. (2023). BigTech credit risk assessment for SMEs. China Economic Review, 81, 102016. https://doi.org/10.1016/j.chieco.2023.102016
Khan, S. U. (2022). Financing constraints and firm-level responses to the COVID-19 pandemic: International evidence. Research in International Business and Finance, 59, 101545. https://doi.org/10.1016/j.ribaf.2021.101545
Mittal, V., & Raman, T. V. (2022). Financing woes: Estimating the impact of MSME financing gap on financial structure practices of firm owners. South Asian Journal of Business Studies, 11(3), 316–340.
Naeve, K. (2022). How impact-linked finance incentivizes high-impact investment in agricultural SMEs: A case study of Root Capital's Social Impact Incentives (SIINC) project [Case study].
Pereira, A. D. S. (2023). SME lending-asymmetries and opportunities in the Brazilian market [Master's thesis, Massachusetts Institute of Technology].
Saifurrahman, A., & Kassim, S. H. (2024). Regulatory issues inhibiting the financial inclusion: A case study among Islamic banks and MSMEs in Indonesia. Qualitative Research in Financial Markets, 16(4), 589–617.
Singh, A. (2024). Information asymmetry and high transaction costs: Challenges for MSMEs in securing financial support. GNLU Journal of Law and Economics, 7(2).
Tigges, M., Mestwerdt, S., Tschirner, S., & Mauer, R. (2024). Who gets the money? A qualitative analysis of fintech lending and credit scoring through the adoption of AI and alternative data. Technological Forecasting and Social Change, 205, 123491. https://doi.org/10.1016/j.techfore.2024.123491
Vives, X., & Ye, Z. (2025). Fintech entry, lending market competition, and welfare. Journal of Financial Economics, 168, 104040. https://doi.org/10.1016/j.jfineco.2025.104040
Wahlstrøm, R. R., Becker, L.-K., & Fornes, T. N. (2024). Enhancing credit risk assessments of SMEs with non-financial information. Cogent Economics & Finance, 12(1), 2418910. https://doi.org/10.1080/23322039.2024.2418910
Wansi, T., & Burrell, D. N. (2023). Financing challenges of Cameroon's small and medium enterprises (SMEs). Financial Markets, Institutions and Risks, 7(4), 88–104.
Williamson, O. E. (1981). The economics of organization: The transaction cost approach. American Journal of Sociology, 87(3), 548–577. https://doi.org/10.1086/227496
Yue, P., Korkmaz, A. G., Yin, Z., & Zhou, H. (2022). The rise of digital finance: Financial inclusion or debt trap? Finance Research Letters, 47, 102604. https://doi.org/10.1016/j.frl.2021.102604
