QRIS and MSME Financial Inclusion in Indonesia's Digital Economy: Opportunities, Risks, and Transaction Trust Strategies

Abdul Wahid Matdoan; Zainudin Matdoan

Authors

Abdul Wahid Matdoan Universitas Pattimura, Indonesia Author
Zainudin Matdoan Author

Keywords:

Digital economy, Digital payments, Financial inclusion, QRIS.

Abstract

This article discusses the role of the Quick Response Code Indonesian Standard (QRIS) in expanding the financial inclusion of MSMEs in Indonesia. The research uses a structured literature study and secondary data analysis from APJII, Bank Indonesia, BPS, OJK, Google-Temasek-Bain, as well as academic literature on technology adoption, digital payments, and consumer trust. The results of the study show that QRIS accelerates the digitization of transactions, lowers the barrier to receiving payments, and opens up better business recording opportunities. However, these benefits do not automatically result in quality financial inclusion if they are not accompanied by financial literacy, consumer protection, transaction security, and integration with other business services. This article proposes a framework for the MSME Digital Transaction Readiness Index which consists of six dimensions: payment access, financial literacy, transaction security, digital record-keeping, online reputation, and service integration. The novelty of the article lies in the incorporation of digital economy perspectives, MSME behavior, transaction risk, and consumer trust into an evaluation framework that can be used for empirical research, literacy programs, and policies to strengthen digital MSMEs.

References

[1] Indonesian Internet Service Providers Association, Indonesian Internet Penetration Survey 2024. Jakarta, Indonesia: APJII, 2024. [Online]. Available: https://apjii.or.id/

[2] Google, Temasek, and Bain & Company, e-Conomy SEA 2025: From Digital Decade to AI Reality. Singapore: Google, Temasek, Bain & Company, 2025.

[3] Central Statistics Agency, E-Commerce Statistics 2024. Jakarta, Indonesia: BPS, 2025. [Online]. Available: https://www.bps.go.id/

[4] Bank Indonesia, QRIS Jelajah Indonesia 2025 Encourages Digitalization in an Exciting and Educational Way. Jakarta, Indonesia: Bank Indonesia, 2025. [Online]. Available: https://www.bi.go.id/

[5] Bank Indonesia, Indonesia's Payment System Blueprint 2030: Accelerating the National Digital Economy for Future Generations. Jakarta, Indonesia: Bank Indonesia, 2025.

[6] Financial Services Authority, National Survey of Financial Literacy and Inclusion 2024. Jakarta, Indonesia: OJK, 2024.

[7] Coordinating Ministry for Economic Affairs of the Republic of Indonesia, Government Encourages MSMEs to Upgrade, Increase Contribution to Indonesian Exports. Jakarta, Indonesia, 2025.

[8] World Bank, World Development Report 2016: Digital Dividends. Washington, DC, USA: World Bank, 2016, doi: 10.1596/978-1-4648-0671-1.

[9] F. D. Davis, “Perceived usefulness, perceived ease of use, and user acceptance of information technology,” MIS Quarterly, vol. 13, no. 3, pp. 319-340, 1989, doi: 10.2307/249008.

[10] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, “User acceptance of information technology: Toward a unified view,” MIS Quarterly, vol. 27, no. 3, pp. 425-478, 2003, doi: 10.2307/30036540.

[11] P. A. Pavlou, “Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model,” Int. J. Electron. Commerce, vol. 7, no. 3, pp. 101-134, 2003, doi: 10.1080/10864415.2003.11044275.

[12] D. Gefen, E. Karahanna, and D. W. Straub, “Trust and TAM in online shopping: An integrated model,” MIS Quarterly, vol. 27, no. 1, pp. 51-90, 2003, doi: 10.2307/30036519.

[13] D. J. Kim, D. L. Ferrin, and H. R. Rao, “A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents,” Decision Support Systems, vol. 44, no. 2, pp. 544-564, 2008, doi: 10.1016/j.dss.2007.07.001.

[14] E. M. Rogers, Diffusion of Innovations, 5th ed. New York, NY, USA: Free Press, 2003.

[15] D. H. McKnight, V. Choudhury, and C. Kacmar, “Developing and validating trust measures for e-commerce: An integrative typology,” Information Systems Research, vol. 13, no. 3, pp. 334-359, 2002, doi: 10.1287/isre.13.3.334.81.

[16] R. C. Mayer, J. H. Davis, and F. D. Schoorman, “An integrative model of organizational trust,” Academy of Management Review, vol. 20, no. 3, pp. 709-734, 1995, doi: 10.5465/amr.1995.9508080335.

[17] A. Beldad, M. de Jong, and M. Steehouder, “How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust,” Computers in Human Behavior, vol. 26, no. 5, pp. 857-869, 2010, doi: 10.1016/j.chb.2010.03.013.

[18] A. Acquisti, C. Taylor, and L. Wagman, “The economics of privacy,” Journal of Economic Literature, vol. 54, no. 2, pp. 442-492, 2016, doi: 10.1257/jel.54.2.442.

[19] K. Martin, “The penalty for privacy violations: How privacy violations impact trust online,” Journal of Business Research, vol. 82, pp. 103-116, 2018, doi: 10.1016/j.jbusres.2017.08.034.

[20] OECD, Consumer Policy in the Digital Age. Paris, France: OECD Publishing, 2020.

[21] OECD, Digital Security Risk Management for Economic and Social Prosperity. Paris, France: OECD Publishing, 2015.

[22] UNCTAD, Digital Economy Report 2021: Cross-border Data Flows and Development. Geneva, Switzerland: United Nations, 2021.

[23] National Institute of Standards and Technology, The NIST Cybersecurity Framework (CSF) 2.0. Gaithersburg, MD, USA: NIST, 2024, doi: 10.6028/NIST. CSWP.29.

[24] International Organization for Standardization, ISO/IEC 27001:2022 Information Security, Cybersecurity and Privacy Protection. Geneva, Switzerland: ISO, 2022.

[25] Republic of Indonesia, Law Number 27 of 2022 concerning Personal Data Protection. Jakarta, Indonesia: State Secretariat, 2022.

[26] State Cyber and Cryptography Agency, Indonesian Cybersecurity Landscape 2023. Jakarta, Indonesia: BSSN, 2024.

[27] N. Kshetri, “The evolution of the internet of things industry and market in China: An interplay of institutions, demands and supply,” Telecommunications Policy, vol. 41, no. 1, pp. 49-67, 2017, doi: 10.1016/j.telpol.2016.11.002.

[28] R. Thaler and C. Sunstein, Nudge: Improving Decisions about Health, Wealth, and Happiness. New Haven, CT, USA: Yale University Press, 2008.

[29] M. Fishbein and I. Ajzen, Predicting and Changing Behavior: The Reasoned Action Approach. New York, NY, USA: Psychology Press, 2010.

[30] G. Shmueli and O. R. Koppius, “Predictive analytics in information systems research,” MIS Quarterly, vol. 35, no. 3, pp. 553-572, 2011.