PENGATURAN AI AGENTIK DALAM BANK SENTRAL: ARSITEKTUR KETAHANAN INSTITUSIONAL MULTI-LAPIS
DOI:
https://doi.org/10.31539/wd3qa649Keywords:
Kecerdasan buatan agen; bank sentral; penelitian ilmu desain; tata kelola AI; ketahanan kelembagaan; risiko sistemik; regulasi makroprudensial; penularan algoritmik; teknologi pengawasan (suptech)Abstract
Kecerdasan buatan berbasis agen bukan lagi sekadar wacana bagi bank sentral. Sistem ini telah diterapkan secara nyata dalam pengawasan makroprudensial, pemantauan sistem pembayaran, dan analitik prediktif, membawa manfaat pengawasan yang signifikan sekaligus risiko tata kelola yang belum sepenuhnya diantisipasi oleh kerangka regulasi yang ada. Penalaran otonom, pengambilan keputusan berlapis, dan pembelajaran adaptif memunculkan tantangan yang melampaui risiko model konvensional, mencakup penularan algoritmik, pergeseran delegasi, dan celah akuntabilitas yang sulit dilacak setelah sistem bertindak. Studi ini mengangkat persoalan tersebut secara serius. Dengan menggunakan metodologi Riset Ilmu Desain (DSR), studi ini mengembangkan dan memvalidasi Arsitektur Ketahanan Kelembagaan Berlapis untuk AI Berbasis Agen (LIRAA), sebuah kerangka tata kelola empat lapis yang dibangun di atas domain mandat inti bank sentral, yaitu kebijakan moneter, kebijakan sistem pembayaran, dan kebijakan stabilitas keuangan, dengan pengawasan perbankan yang turut diintegrasikan pada yurisdiksi yang relevan. LIRAA memadukan penguatan otoritas kelembagaan, akuntabilitas algoritmik, eskalasi pengawasan adaptif, dan penahanan risiko sistemik ke dalam satu struktur tata kelola yang koheren. Evaluasi melalui penilaian ahli terstruktur dan pengujian stres berbasis skenario menunjukkan kelayakan kelembagaan yang kuat serta kapasitas mitigasi risiko yang bermakna, meskipun para ahli secara konsisten mencatat perlunya ambang batas eskalasi yang lebih jelas dan kodifikasi hukum yang lebih kuat. Yang lebih penting dari temuan ini adalah bahwa stabilitas keuangan dalam sistem pengawasan berbasis AI tidak semata-mata bergantung pada tingkat kecanggihan komputasi. Stabilitas tersebut sangat ditentukan oleh seberapa kuat desain kelembagaan mampu mencegah terjadinya amplifikasi keputusan algoritmik secara serentak yang dapat berlangsung tanpa disadari dalam skala besar. Studi ini berkontribusi pada literatur tata kelola AI dengan memperluas teori risiko sistemik ke ranah tata kelola penularan algoritmik, sekaligus memposisikan arsitektur kelembagaan, bukan sekadar kinerja algoritma, sebagai penentu utama stabilitas di era kecerdasan keuangan yang semakin otonom.
References
Akoka, J., Comyn-Wattiau, I., Prat, N., & Storey, V. C. (2023). Knowledge contributions in design science research: Paths of knowledge types. Decision Support Systems, 166, 113898. https://doi.org/10.1016/j.dss.2022.113898
Auer, R., Cornelli, G., & Frost, J. (2022). Artificial Intelligence in Central Bank (Issue 1044).
Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial Intelligence, firm growth, and product innovation. Journal of Financial Economics, 151(January), 103745. https://doi.org/10.1016/j.jfineco.2024.103916
Bagherifam, N., Naghdi, S., Ahmadian, V., Fazlzadeh, A., & Shishehgarkhaneh, M. B. (2025). Digital regulatory governance: The role of RegTech and SupTech in transforming financial oversight and administrative capacity. International Journal of Financial Studies, 13(4), 217. https://doi.org/10.3390/ijfs13040217
Bank for International Settlements. (2025). Financial stability implications of artificial intelligence - Executive summary. https://www.bis.org/fsi/fsisummaries/exsum_23904.htm
Bank Indonesia. (2019). Blueprint sistem pembayaran Indonesia 2025.
Bank Indonesia. (2021). Regulation No. 23/11/PBI/2021 on National Payment System Standards.
Bholat, D. (2020). Big Data and Central Banks.
Brendel, A. B., Lembcke, T.-B., Muntermann, J., & Kolbe, L. M. (2021). Toward replication study types for design science research. Journal of Information Technology, 36(3), 198–215. https://doi.org/10.1177/02683962211006429
Cao, L. (2022). AI in finance: Challenges, techniques, and opportunities. ACM Computing Surveys, 55(3), Article 64. https://doi.org/10.1145/3502289
Chen, Y. (2022). Bank interconnectedness and financial stability: The role of bank capital. Journal of Financial Stability, 61, 101019. https://doi.org/10.1016/j.jfs.2022.101019
Chen, Z., Pelger, M., & Zhu, J. (2023). Deep learning in asset pricing. Management Science, 70(2). https://doi.org/10.1287/mnsc.2022.4417
Damaris, R., Rosadi, S. D., & Bratadana, I. M. D. (2025). Data governance for Artificial Intelligence implementation in the financial sector: An Indonesian perspective. Journal of Central Bank Law and Institutions, 4(3). https://doi.org/10.21098/jcli.v4i3.430
Daníelsson, J., Macrae, R., & Uthemann, A. (2022). Artificial Intelligence and systemic risk. Journal of Banking & Finance, 140(July), 106290. https://doi.org/10.1016/j.jbankfin.2021.106290
Das, S., Stanton, R., & Wallace, N. (2023). Algorithmic fairness. Annual Review of Financial Economics, 15, 565–593. https://doi.org/10.1146/annurev-financial-110921-125930
de Haan, J., Eijffinger, S., & Waller, C. (2020). The European Central Bank: Credibility, transparency, and governance. Oxford University Press. https://doi.org/10.1093/oso/9780190628211.001.0001
Goodhart, C., & Lastra, R. (2018). Populism and central bank independence. Open Economies Review, 29, 49–68. https://doi.org/10.1007/s11079-017-9447-y
Gregor, S., & Zwikael, O. (2024). Design science research and the co-creation of project management knowledge. International Journal of Project Management, 42(3), 102584. https://doi.org/10.1016/j.ijproman.2024.102584
Hevner, A. R., Parsons, J., Brendel, A. B., Lukyanenko, R., Tiefenbeck, V., Tremblay, M. C., & vom Brocke, J. (2024). Transparency in design science research. Decision Support Systems, 182, 114236. https://doi.org/10.1016/j.dss.2024.114236
International Monetary Fund. (2024). Artificial Intelligence and the future of financial supervision. September 6, 2024. https://www.imf.org/en/news/articles/2024/09/06/sp090624-artificial-intelligence-and-its-impact-on-financial-markets-and-financial-stability
Kerry, C. F. (2020). Protecting privacy in an AI-driven world. https://www.brookings.edu/articles/protecting-privacy-in-an-ai-driven-world/
Larsen, K. R., Lukyanenko, R., Mueller, R. M., Storey, V. C., Parsons, J., VanderMeer, D., & Hovorka, D. S. (2025). Validity in Design Science. MIS Quarterly, 49(4), 1267–1294. https://doi.org/10.25300/MISQ/2024/18064
Matheus, R., Janssen, M., & Janowski, T. (2021). Design principles for creating digital transparency in government. Government Information Quarterly, 38(1), 101550. https://doi.org/10.1016/j.giq.2020.101550
McNulty, D., Miglionico, A., & Milne, A. (2023). Data access technologies and the “new governance” techniques of financial regulation. Journal of Financial Regulation, 9(2), 225–248. https://doi.org/10.1093/jfr/fjad008
Mo, H. (2025). (Generative) AI in financial Economics. Review of Behavioral Economics, 23(4), 509–587. https://doi.org/10.1080/14765284.2025.2569006
Nguyen, H., & Pham, X. (2024). AI and organizational governance in financial services. Information Systems Research, 35(1). https://doi.org/10.1287/isre.2023.1147
POJK No. 19 of 2024 concerning the Implementation of Information Technology and Digital Risk Management 2024, (2024). https://jdih.ojk.go.id/
Rai, A., Constantinides, P., & Sarker, S. (2019). Next-generation digital platforms: Toward human-AI hybrids. MIS Quarterly, 43(1). https://doi.org/10.25300/MISQ/2019/14117
Tuunanen, T., Winter, R., & vom Brocke, J. (2024). Dealing with complexity in design science research: A methodology using design echelons. MIS Quarterly, 48(2), 427–458. https://doi.org/10.25300/MISQ/2023/16700
Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., Lin, Y., Zhao, W. X., Wei, Z., & Wen, J. (2024). A survey on large language model based autonomous agents. Frontiers of Computer Science, 18, 186345. https://doi.org/10.1007/s11704-024-40231-1
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