Transformasi Keuangan Digital Berbasis Artificial Intelligence dalam Meningkatkan Financial Inclusion dan Sustainable Finance
Keywords:
Artificial Intelligence, Keuangan Digital, Financial Inclusion, Sustainable Finance, FinTechAbstract
Transformasi keuangan digital berbasis Artificial Intelligence (AI) menjadi faktor kunci dalam meningkatkan financial inclusion dan memperkuat sustainable finance di era ekonomi digital. Meskipun adopsi teknologi keuangan terus meningkat, masih terdapat kesenjangan akses layanan keuangan serta tantangan dalam integrasi prinsip keberlanjutan. Penelitian ini bertujuan untuk menganalisis peran AI dalam mendorong inklusi keuangan dan mendukung praktik keuangan berkelanjutan melalui pendekatan konseptual. Metode penelitian menggunakan studi pustaka dan analisis konten terhadap literatur ilmiah, laporan kebijakan, serta publikasi terkait fintech, AI, dan sustainable finance. Hasil penelitian menunjukkan bahwa AI berkontribusi signifikan dalam memperluas akses layanan keuangan melalui alternative credit scoring, e-KYC, personalisasi layanan, serta penguatan manajemen risiko dan integrasi ESG dalam pembiayaan. Namun, optimalisasi manfaat AI memerlukan tata kelola yang kuat, perlindungan data, regulasi adaptif, serta peningkatan literasi keuangan dan digital. Artikel ini juga memberikan kontribusi teoretis melalui pengembangan sintesis konseptual yang mengintegrasikan hubungan antara AI, financial inclusion, dan sustainable finance dalam kerangka transformasi keuangan digital.
References
Cheng, L., Varshney, K. R., & Liu, H. (2021). Socially responsible AI algorithms: Issues, purposes, and challenges. Journal of Artificial Intelligence Research, 71, 1137–1181. https://doi.org/10.1613/JAIR.1.12814
Creswell, J. W., & Creswell, J. D. (2018). Mixed Methods Procedures. In Research Defign: Qualitative, Quantitative, and Mixed M ethods Approaches.
Creswell, J. W., & Creswell, J. D. (2023). Research Design : Qualitative, Quantitative, and A Mixed-Method Approach. In SAGE Publication. https://doi.org/10.4324/9780429469237-3
Devan, M., Krothapalli, B., Shanmugam, L., & Services, T. C. (2023). Advanced Machine Learning Algorithms for Real-Time Fraud Detection in Investment Banking : A Comprehensive Framework. Cybersecurity and Network Defense Research, 3(1), 57–94.
Fahlevi, M., Vional, & Pramesti, R. M. (2022). Blockchain technology in corporate governance and future potential solution for agency problems in Indonesia. International Journal of Data and Network Science, 6(3), 721–726. https://doi.org/10.5267/j.ijdns.2022.3.010
Hayati, M. S. U., & Hadiprajitno, P. B. (2021). Departemen Akuntansi Fakultas Ekonomika dan Bisnis Universitas Diponegoro. Diponegoro Journal of …, 1203011612(2022), 19840503. https://ejournal3.undip.ac.id/index.php/accounting/article/view/32979%0Ahttps://ejournal3.undip.ac.id/index.php/accounting/article/download/32979/26344
Ishtiaq, M. (2019). Book Review Creswell, J. W. (2014). Research Design: Qualitative, Quantitative and Mixed Methods Approaches (4th ed.). Thousand Oaks, CA: Sage. English Language Teaching, 12, 40. https://doi.org/10.5539/elt.v12n5p40
Kalu, K. Uk., & Mike, A. (2020). Exchange Rates Fluctuations and International Trade in a Mono-product Economy: Nigeria’s Experience, 1986-2018. South Asian Journal of Social Studies and Economics, 7(2), 21–48. https://doi.org/10.9734/sajsse/2020/v7i230187
Khan, M. S., Umer, H., & Faruqe, F. (2024). Artificial intelligence for low income countries. Humanities and Social Sciences Communications, 11(1), 1–13. https://doi.org/10.1057/s41599-024-03947-w
Kshetri, N. (2021). The Role of Artificial Intelligence in Promoting Financial Inclusion in Developing Countries. Journal of Global Information Technology Management, 24(1), 1–6. https://doi.org/10.1080/1097198X.2021.1871273
Kyrychenko, O. V., Soldatenko, O. A., Gorokhovska, O. V., Voloshyna, M. O., & Maksymova, L. O. (2021). Fraud in the banking system of Ukraine: ways to combat taking into account foreign experience. Revista Amazonia Investiga, 10(45), 208–220. https://doi.org/10.34069/ai/2021.45.09.21
Mubarok, Muhammad Umam and Santoso, Budi and Satoto, E. and N. (2025). Extending TOE With Scaffolding: Mixed-Methods Evidence on AI Adoption and Digital Marketing Performance in Indonesia. SSRN Electronic Journal, 1–34. https://doi.org/10.2139/ssrn.5563835
Mubarok, Sari, Wibowo, M. (2025). Comparative Study of Artificial Intelligence (AI) Utilization in Digital Marketing Strategies Between Developed and Developing Countries: A Systematic Literature Review. Ilomata International Journal of Management, 6(1), 156–173. https://doi.org/10.61194/ijjm.v6i1.1534
Okello Candiya Bongomin, G., Yourougou, P., Balinda, R., & Baleke Yiga Lubega, J. (2024). Customized financial literacy: a boon for universal financial inclusion of PWDs post COVID-19 pandemic in developing countries. Journal of Financial Regulation and Compliance. https://doi.org/10.1108/JFRC-07-2023-0109
Olateju, O. O., Okon, S. U., Igwenagu, U. T. I., Salami, A. A., Oladoyinbo, T. O., & Olaniyi, O. O. (2024). Combating the Challenges of False Positives in AI-Driven Anomaly Detection Systems and Enhancing Data Security in the Cloud. Asian Journal of Research in Computer Science, 17(6), 264–292. https://doi.org/10.9734/ajrcos/2024/v17i6472
Scheetz, A., Smalls, T. D. W., Wall, J., & Wilson, A. B. (2020). Do Employee Fraud Reporting Intentions Differ between For-Profit and Nonprofit Organizations? Journal of Governmental & Nonprofit Accounting, 9(1), 94–117. https://doi.org/10.2308/jogna-18-008
Setiana, D., & Gunawan, J. (2023). Pengaruh Kesadaran Anti-Fraud, Kesesuaian Kompensasi, Dan Moralitas Individu Terhadap Kecenderungan Kecurangan Akuntansi. EBID:Ekonomi Bisnis Digital, 1(2), 241–248. https://doi.org/10.37365/ebid.v1i2.229
Setyaningsih, P. R., & Nengzih, N. (2020). Internal control, organizational culture, and quality of information accounting to prevent fraud: Case study from Indonesia’s agriculture industry. International Journal of Financial Research, 11(4), 316–328. https://doi.org/10.5430/ijfr.v11n4p316
Sihombing, T., & Eirene Panggulu, G. (2022). Fraud Hexagon Theory And Fraudulent Financial Statement In IT Industry In Asean. Jurnal Reviu Akuntansi Dan Keuangan, 12(3), 524–544. https://doi.org/10.22219/jrak.v12i3.23334
Sugiyono. (2021). Metode Penelitian Kuantitaif, Kualitatif, R&D. Alfabeta.
Syahronny, M. R., & Dewayanto, T. (2024). Penerapan Teknologi Artificial Intelligence Dan Blockchain Dalam Mendeteksi Fraud Pada Proses Audit: Systematic Literature Review. Diponegoro Journal of Accounting, 13(3), 1–14. http://ejournal-s1.undip.ac.id/index.php/accounting
Truby, J., Brown, R., & Dahdal, A. (2020). Banking on AI: mandating a proactive approach to AI regulation in the financial sector. Law and Financial Markets Review, 14(2), 110–120. https://doi.org/10.1080/17521440.2020.1760454
Downloads
Published
License
Copyright (c) 2026 Tri Suris Lestari, Agatha Helena Deze

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.




