Kecerdasan Buatan dalam Efisiensi Operasional Perbankan Syariah: Studi Layanan Chatbot dan Credit Scoring Berbasis Machine Learning
Keywords:
Kecerdasan Buatan, Efisiensi Operasional, Chatbot, Machine LearningAbstract
Transformasi digital mendorong perbankan syariah untuk mengadopsi kecerdasan buatan atau artificial intelligence (AI) sebagai instrumen peningkatan efisiensi operasional, kualitas layanan, dan ketepatan pengambilan keputusan pembiayaan. Penelitian ini bertujuan menganalisis peran AI dalam efisiensi operasional perbankan syariah, khususnya pada layanan chatbot dan credit scoring berbasis machine learning. Artikel ini menggunakan pendekatan kualitatif dengan desain studi kasus konseptual yang dikembangkan melalui kajian literatur, telaah regulasi, dan rancangan wawancara semi-terstruktur terhadap pemangku kepentingan perbankan syariah, meliputi manajemen operasional, tim teknologi informasi, analis pembiayaan, Dewan Pengawas Syariah, petugas layanan nasabah, dan nasabah pengguna layanan digital. Hasil kajian menunjukkan bahwa chatbot dapat meningkatkan efisiensi layanan melalui ketersediaan layanan 24 jam, percepatan respons, pengurangan beban pertanyaan repetitif pada customer service, serta peningkatan konsistensi informasi. Sementara itu, credit scoring berbasis machine learning berpotensi mempercepat proses analisis pembiayaan, meningkatkan kemampuan prediksi risiko, dan memperluas akses pembiayaan bagi nasabah yang sebelumnya sulit dinilai melalui metode konvensional. Namun, penerapan AI dalam perbankan syariah menghadapi tantangan berupa bias algoritmik, keterbatasan transparansi model, risiko keamanan siber, perlindungan data pribadi, ketergantungan pada pihak ketiga, serta kebutuhan kesesuaian dengan prinsip syariah. Artikel ini menegaskan bahwa efisiensi operasional tidak boleh dimaknai sekadar penghematan biaya, tetapi harus ditempatkan dalam kerangka maqashid syariah, tata kelola AI yang bertanggung jawab, human-in-the-loop, perlindungan konsumen, dan keadilan akses pembiayaan.
References
Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31, 427–445. https://doi.org/10.1007/s12525-020-00414-7
Alam, N., Gupta, L., & Zameni, A. (2019). Fintech and Islamic finance: Digitalization, development and disruption. Springer. https://doi.org/10.1007/978-3-030-24666-2
Ali, H., Abdullah, R., & Zaini, M. Z. (2019). Fintech and its potential impact on Islamic banking and finance industry: A case study of Brunei Darussalam and Malaysia. International Journal of Islamic Economics and Finance, 2(1). https://doi.org/10.18196/ijief.2116
Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable artificial intelligence: Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012
Basel Committee on Banking Supervision. (2022). Newsletter on artificial intelligence and machine learning. Bank for International Settlements. https://www.bis.org/publ/bcbs_nl27.htm
Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance. MIS Quarterly, 24(1), 169–196. https://doi.org/10.2307/3250983
Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. SAGE Publications. https://uk.sagepub.com/en-gb/eur/thematic-analysis/book248481
Bücker, M., Szepannek, G., Gosiewska, A., & Biecek, P. (2020). Transparency, auditability and explainability of machine learning models in credit scoring. arXiv. https://arxiv.org/abs/2009.13384
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. https://us.sagepub.com/en-us/nam/research-design/book270550
Demajo, L. M., Vella, V., & Dingli, A. (2020). Explainable AI for interpretable credit scoring. arXiv. https://arxiv.org/abs/2012.03749
European Banking Authority. (2023). Follow-up report on machine learning for IRBmodels.https://www.eba.europa.eu/sites/default/files/document_library/Publications/Reports/2023/1061483/Followup%20report%20on%20machine%20learning%20for%20IRB%20models.pdf
Financial Stability Board. (2024). The financial stability implications of artificial intelligence. https://www.fsb.org/2024/11/the-financial-stability-implications-of-artificial-intelligence/
Følstad, A., & Brandtzæg, P. B. (2017). Chatbots and the new world of HCI. Interactions, 24(4), 38–42. https://doi.org/10.1145/3085558
Garbo, A., & Latifah, H. R. (2024). Optimasi pelayanan nasabah Bank Syariah Indonesia melalui penggunaan kecerdasan buatan. Jurnal Masharif al-Syariah: Jurnal Ekonomi dan Perbankan Syariah, 9(2). https://journal.um-surabaya.ac.id/Mas/article/download/22128/7571/56213
Hamadou, I. (2024). Unleashing the power of artificial intelligence in Islamic banking: A case study of Bank Syariah Indonesia (BSI). Modern Finance, 2(1), 131–144. https://mf-journal.com/article/view/116
Huang, M. H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30–50. https://doi.org/10.1007/s11747-020-00749-9
Kelly, S. (2021). Algorithmic bias, financial inclusion, and gender. Women’s World Banking. https://www.womensworldbanking.org/wp-content/uploads/2024/03/Algorithmic_Bias_Primer.pdf
Leo, M., Sharma, S., & Maddulety, K. (2019). Machine learning in banking risk management: A literature review. Risks, 7(1), 29. https://doi.org/10.3390/risks7010029
Lessmann, S., Baesens, B., Seow, H. V., & Thomas, L. C. (2015). Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research. European Journal of Operational Research, 247(1), 124–136. https://doi.org/10.1016/j.ejor.2015.05.030
Louzada, F., Ara, A., & Fernandes, G. B. (2016). Classification methods applied to credit scoring: A systematic review and overall comparison. Surveys in Operations Research and Management Science, 21(2), 117–134. https://doi.org/10.1016/j.sorms.2016.10.001
Lundberg, S. M., & Lee, S. I. (2017). A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems, 30. https://papers.nips.cc/paper_files/paper/2017/hash/8a20a8621978632d76c43dfd28b67767-Abstract.html
Manneh, K. (2025). Artificial intelligence (AI) in Islamic finance: A PRISMA-guided systematic review. Equilibrium: Jurnal Ekonomi Syariah. https://journal.iainkudus.ac.id/index.php/equilibrium/article/view/33951
Miles, M. B., Huberman, A. M., & Saldaña, J. (2019). Qualitative data analysis: A methods sourcebook (4th ed.). SAGE Publications. https://us.sagepub.com/en-us/nam/qualitative-data-analysis/book246128
Nallakaruppan, M. K., et al. (2024). An explainable AI framework for credit evaluation and analysis. Applied Soft Computing, 153, 111281. https://doi.org/10.1016/j.asoc.2024.111281
OECD. (2024). OECD AI principles. https://www.oecd.org/en/topics/sub-issues/ai-principles.html
Otoritas Jasa Keuangan. (2022). Peraturan OJK Nomor 11/POJK.03/2022 tentang Penyelenggaraan Teknologi Informasi oleh Bank Umum. https://ojk.go.id/id/regulasi/Documents/Pages/Penyelenggaraan-Teknologi-Informasi-Oleh-Bank-Umum/POJK%2011%20-%2003%20-%202022.pdf
Otoritas Jasa Keuangan. (2022). SEOJK Nomor 29/SEOJK.03/2022 tentang Ketahanan dan Keamanan Siber bagi Bank Umum. https://www.ojk.go.id/id/regulasi/Documents/Pages/Ketahanan-dan-Keamanan-Siber-Bagi-Bank-Umum/SEOJK%2029%20SEOJK.03%202022.pdf
Otoritas Jasa Keuangan. (2023). Roadmap Pengembangan dan Penguatan Perbankan Syariah Indonesia 2023–2027. https://ojk.go.id/id/Publikasi/Roadmap-dan-Pedoman/Syariah/Perbankan-Syariah-Indonesia/Pages/Roadmap-Pengembangan-dan-Penguatan-Perbankan-Syariah-Indonesia-2023-2027.aspx
Otoritas Jasa Keuangan. (2023). Peraturan OJK Nomor 22 Tahun 2023 tentang Pelindungan Konsumen dan Masyarakat di Sektor Jasa Keuangan. https://www.ojk.go.id/id/regulasi/Documents/Pages/Pelindungan-Konsumen-dan-Masyarakat-di-Sektor-Jasa-Keuangan/POJK%2022%20Tahun%202023%20Pelindungan%20Konsumen%20dan%20Masyarakat%20di%20Sektor%20Jasa%20Keuangan.pdf
Otoritas Jasa Keuangan. (2024). Peraturan OJK Nomor 3 Tahun 2024 tentang Penyelenggaraan Inovasi Teknologi Sektor Keuangan. https://www.ojk.go.id/id/regulasi/Documents/Pages/POJK-2-2024-Penyelenggaraan-Inovasi-Teknologi-Sektor-Keuangan/POJK%203%20Tahun%202024%20Penyelenggaraan%20Inovasi%20Teknologi%20Sektor%20Keuangan.pdf
Otoritas Jasa Keuangan. (2025). Tata Kelola Kecerdasan Artifisial Perbankan Indonesia. https://www.ojk.go.id/id/Publikasi/Roadmap-dan-Pedoman/Perbankan/Pages/Tata-Kelola-Kecerdasan-Artifisial-Perbankan-Indonesia.aspx
Otoritas Jasa Keuangan. (2025). POJK Nomor 29 Tahun 2024 tentang Pemeringkat Kredit Alternatif. https://ojk.go.id/en/berita-dan-kegiatan/siaran-pers/Documents/Pages/OJK-Issues-Regulation-on-AlternativeCreditRating/13%20%5BPress%20Release%5D%20OJK%20Terbitkan%20Peraturan%20Pemeringkat%20Kredit%20Alternatif_EN.pdf
Otoritas Jasa Keuangan. (2026). Snapshot Perbankan Syariah Indonesia Desember 2025. https://ojk.go.id/id/berita-dan-kegiatan/publikasi/Pages/Snapshot-Perbankan-Syariah-Indonesia-Des-2025.aspx
Otoritas Jasa Keuangan. (2026). Perbankan Syariah. https://ojk.go.id/id/kanal/syariah/Pages/Perbankan-Syariah.aspx
Prentice, C., Dominique Lopes, S., & Wang, X. (2023). Conversational artificial intelligence and bank operational efficiency. International Journal of Accounting and Management Information Systems. https://goodwoodpub.com/index.php/ijamis/article/view/1915
Republik Indonesia. (2022). Undang-Undang Nomor 27 Tahun 2022 tentang Pelindungan Data Pribadi. https://peraturan.bpk.go.id/Details/229798/uu-no-27-tahun-2022
Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). “Why should I trust you?” Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1135–1144. https://doi.org/10.1145/2939672.2939778
Shah, I. H. (2025). Investigating the risks of algorithmic bias and explainability failures in AI-driven credit scoring. SSRN Electronic Journal. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5361937
Wahyuni, E. S. (2025). Managing customer service through artificial intelligence-driven chatbot systems in Islamic banking institutions. Al-Uqud: Journal of IslamicEconomics.https://journal.unesa.ac.id/index.php/jie/article/view/40020
Downloads
Published
Versions
- 2026-06-30 (2)
- 2026-07-03 (1)
Issue
Section
License
Copyright (c) 2026 Ainun Putri Kumalasari (Author)

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


