Artificial Intelligence and the Fragile Fortress
Addressing the Security and Data Privacy Gaps in Indonesia’s Financial Sector Resilience
DOI:
https://doi.org/10.61459/ijfs.v3i2.89Keywords:
Artificial Intelligence, Financial Sector Resilience, ADIFL Syndrome, Digital Vulnerability, Policy DesignAbstract
Indonesia’s financial sector embodies a paradox of a “fragile fortress”: while Artificial Intelligence (AI) accelerates innovation and strengthens external facades, it simultaneously embeds systemic vulnerabilities within its digital architecture. To address this dichotomy, this article introduces the Algorithmic Digital Integrity Fault Lines Syndrome (ADIFL Syndrome) as a novel theoretical framework. ADIFL conceptualises six interlinked algorithmic risks, cyber-privacy vulnerability, data abuse by design, erosion of social legitimacy, infrastructure fragility, regulatory asymmetry, and AI service unreliability that collectively erode digital integrity. Using a qualitative-constructive methodology grounded in systemic theories and strategic case studies, the study demonstrates that these risks are not isolated incidents but manifestations of deeper structural fault lines. Findings reveal how compounding vulnerabilities undermine resilience and legitimacy, offering actionable policy recommendations to strengthen adaptive governance. Furthermore, the article proposes the Digital Integrity Risk Index (DIRI) as a future evaluative tool, complete with measurable indicators for each ADIFL subset. By framing AI risks as emergent and interconnected phenomena, this research provides a conceptual foundation for building anticipatory digital resilience, relevant not only to finance but also to critical domains such as public services, healthcare, and education.
Downloads
References
Agudo, U., Liberal, K. G., Arrese, M., & Matute, H. (2024). The impact of AI errors in a humanin-the-loop process. Cognitive Research: Principles and Implications, 9(1), 1. https://doi.org/10.1186/s41235-023-00529-3
Akerlof, G. A. (1978). The market for “lemons”: Quality uncertainty and the market mechanism. In Uncertainty in economics (pp. 235–251). Elsevier. https://www.sciencedirect.com/science/article/pii/B978012214850750022X
Alfrink, K., Keller, I., Kortuem, G., & Doorn, N. (2022). Contestable AI by Design: Towards a framework. Minds and Machines, 33(4), 613–639. https://doi.org/10.1007/s11023-022-09611-z
Alrasheed, G., & Lim, M. (2021, May 16). Beyond a technical bug: Biased algorithms and moderation are censoring activists on social media. The Conversation. http://theconversation.com/beyond-a-technical-bug-biased-algorithms-and-moderation-are-censoring-activists-onsocial-media-160669
Bahoo, S., Cucculelli, M., Goga, X., & Mondolo, J. (2024). Artificial intelligence in Finance: A comprehensive review through bibliometric and content analysis. SN Business & Economics, 4(2), 23. https://doi.org/10.1007/s43546-023-00618-x
Bank for International Settlements, (BIS). (2023). A step toward new financial market infrastructure:Infrastructure: Bank of Korea’s initiative Bank of Korea’s initiative (p. 25). Bank of Korea.
Basak, A., & Tiwari, D. (2025). API security risk and resilience in financial institutions. https://www.theseus.fi/handle/10024/883344
Batool, A., Zowghi, D., & Bano, M. (2025). AI governance: A systematic literature review. AI and Ethics, 5(3), 3265–3279. https://doi.org/10.1007/s43681-024-00653-w
Bayamlıoğlu, E. (2022). The right to contest automated decisions under the general data protection regulation: Beyond the so-called “right to explanation.” Regulation & Governance, 16(4), 1058–1078. https://doi.org/10.1111/rego.12391
Boivin, J. (2025). The ecological catastrophe of algorithmic individuation: Technological mediation and its social implication in the age of the anthropocene. In D. Binns & R. Najdowski (Eds.), Confronting the Climate Crisis: Activism, Technology and Ecoaesthetics (pp. 293–311). https://doi.org/10.1007/978-3-031-89606-4_15
Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Conference on Fairness, Accountability and Transparency, 77–91.
Cahyani, F. D., & Maria, N. S. B. (2023). Analisis stabilitas sistem keuangan dan faktor-faktor yang mempengaruhinya. Diponegoro Journal of Economics, 12(3), 57–61.
Cate, M. (2025). Data privacy risks and vulnerabilities in API-driven financial ecosystems.
Chang, X. (2023). Gender bias in hiring: An analysis of the impact of amazon’s recruiting algorithm. Advances in Economics Management and Political Sciences, 23(1), 134–140.
Cristine, M. A., Risakota, F. M. A., & Sirait, S. R. C. (2025). Perlindungan data pribadi dalam sistem skoring kredit otomatis oleh fintech di Indonesia: Analisis yuridis normatif berdasarkan undang- undang nomor 27 tahun 2022. Jurnal Studi Hukum Modern, 7(3), Article 3. https://journalversa.com/s/index.php/jshm/article/view/860
Cypriva. (2025, March 8). Kebocoran data pribadi di indonesia: ancaman, kasus, dan sol. https://www.cypriva.id/articles/kebocoran-data-pribadi-di-indonesia-ancaman-nyata-kasus-terkinidan-solusi-pencegahannya-
Dellaert, B. G. C., Baker, T., & Johnson, E. J. (2024). Regulating robo-advice for consumers’ financial decisions: The interplay between algorithm quality & digital choice architecture. Behavioral Science & Policy, 10(2), 1–7. https://doi.org/10.1177/23794607241296686
Detiknet, T. (2021, July 28). Kominfo investigasi dugaan kebocoran data 2 juta pengguna BRI Life [News]. detikinet. https://inet.detik.com/security/d-5659592/kominfo-investigasi-dugaankebocoran-data-2-juta-pengguna-bri-life
Dorochowicz, A., Jankowski, D., Ksieniewicz, P., Topolska, K., Topolski, M., & Zyblewski, P.(2025). A prototype of an ai-driven operational security system for fintechs: A faas-based approach to fraud detection, Progress in Pattern Classification and Machine Learning (pp. 103–112). https://doi.org/10.1007/978-3-032-01773-4_11
Eschenbach, W. J. V. (2021). Transparency and the black box problem: Why we do not trust AI. Philosophy & Technology, 34(4), 1607–1622. https://doi.org/10.1007/s13347-021-00477-0
EU. (2016, April 27). Regulation, 2016/679, EN - gdpr, EUR-Lex [Official Journal of the European Union]. European Union. https://eur-lex.europa.eu/eli/reg/2016/679/oj/eng
Eubanks, V. (2018). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.
Fitriyanti, F., Devty, S., Putri, S., & Thora, R. E. (2024). Securing personal data in e-kyc: vital for digital economy growth. Diponegoro Law Review, 9(1), 104–120.
Fredrikson, M., Jha, S., & Ristenpart, T. (2015). Model inversion attacks that exploit confidence information and basic countermeasures. Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 1322–1333. https://doi.org/10.1145/2810103.2813677
FSB. (2024). The Financial stability implications of artificial intelligence.
Fursov, I., Morozov, M., Kaploukhaya, N., Kovtun, E., Rivera-Castro, R., Gusev, G., Babaev, D., Kireev, I., Zaytsev, A., & Burnaev, E. (2021). Adversarial attacks on deep models for financial transaction records. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2868–2878. https://doi.org/10.1145/3447548.3467145
Grennan, J. (2022). FinTech regulation in the united states: Past, present, and future. Present, and Future (August 31, 2022). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4045057
Gupta, M., Akiri, C., Aryal, K., Parker, E., & Praharaj, L. (2023). From ChatGPT to threatgpt: Impact of generative ai in cybersecurity and privacy. IEEE Access, 11, 80218–80245.
Hidayanti, N. F., Ariani, Z., & Syaharuddin, S. (2025). The integration of artificial intelligence in islamic financial services: A review on digital innovation for sharia financial inclusion.
Integrating Religion, Social Economy, and Law: Conference Series, 1(1), 8–17. https://journal.ummat.ac.id/index.php/ics/article/view/32559
Holland, J. H. (1992). Complex adaptive systems. Daedalus, 121(1), 17–30.
Hughes, H. P. N., Clegg, C. W., Bolton, L. E., & Machon, L. C. (2017). Systems scenarios: A tool for facilitating the socio-technical design of work systems. Ergonomics, 60(10), 1319–1335. https://doi.org/10.1080/00140139.2017.1288272
Iqbar, M. D., Darrel, M., & Akilah, U. I. (2024). Analisis politik luar negeri indonesia dinamika dan tantangan lima tahun terakhir. https://doi.org/10.13140/RG.2.2.34325.95203
Iyer, S. (2022). Operational Resilience for Financial Institutions [PhD Thesis, Trident University International].
Insurtech Asia. (2023). InsureTech Connect Asia 2023 Summary Report. Abeam Consulting. https://www.abeam.com/id/en/insights/insure_tech_2023/
Jaakkola, E. (2020). Designing conceptual articles: Four approaches. AMS Review, 10(1–2), 18–26. https://doi.org/10.1007/s13162-020-00161-0
James, U. U., Idika, C. N., Enyejo, L. A., Abiodun, K., & Enyejo, J. O. (2024). Adversarial attack detection using explainable AI and generative models in real-time financial fraud monitoring systems. International Journal of Scientific Research and Modern Technology, 3(12), 142–157.
Javia, S. (2025, March 27). Kesenjangan besar dalam AI: pemimpin di sektor jasa keuangan hadapi tantangan tata kelola data dan tuntutan infrastruktur. IndonesiaSatu.co. https://indonesiasatu.co/detail/kesenjangan-besar-dalam-ai--pemimpin-di-sektor-jasa-keuangan-hadapi-tantangantata-kelola-data-dan-tuntutan-infrastruktur
Kandpal, V., Ozili, P. K., Jeyanthi, P. M., Ranjan, D., & Chandra, D. (2025). Regulation of the fintech industry. in digital finance and metaverse in banking: decoding a virtual reality towards financial inclusion and sustainable development (pp. 181–198). Emerald Publishing Limited. https://www.emerald.com/insight/content/doi/10.1108/978-1-83662-088-420251009/full/html
Karakasilioti, G. M. (2024). Supporting the digital operational resilience of the financial sector: The EU’s DORA Digital Operational Resilience Act [Master’s Thesis,
Lachmann, N. (2025). Chasing the elusive bird?: The technological development of the digital economy and international trade law’s susceptibility to a pacing problem. The Journal of World Investment & Trade, 26(3), 479–511.
Lewis, J. D., & Weigert, A. (1985). Trust as a social reality. Social Forces, 63(4), 967–985.
Li, Q. (2025). Research on consumer data sovereignty and algorithmic fairness. International Journal of Management Science Research, 8(4), 6–10.
Lim, T. (2024). Environmental, social, and governance (ESG) and artificial intelligence in finance: State-of-the-art and research takeaways. Artifcial Intelligence Review, 57(76), 1–64. https://doi.org/10.1007/s10462-024-10708-3
Lu, S. (2022). Data privacy, human rights, and algorithmic opacity. Cal. L. Rev., 110, 2087.
Luhmann, N. (1979). Trust and Power. Chichester: Jhon Wiley and Son Inc.
Luthfah, D. (2024). Penguatan keamanan siber pada sektor jasa keuangan Indonesia. Jurnal Penelitian dan Karya Ilmiah Lembaga Penelitian Universitas Trisakti, 9(1), 259–267. https://doi.org/10.25105/pdk.v9i1.18643
MacInnis, D. J. (2011). A framework for conceptual contributions in marketing. Journal of Marketing, 75(4), 136–154. https://doi.org/10.1509/jmkg.75.4.136
Malatji, M., & Tolah, A. (2025). Artificial intelligence (AI) cybersecurity dimensions: A comprehensive framework for understanding adversarial and offensive AI. AI and Ethics, 5(2), 883–910. https://doi.org/10.1007/s43681-024-00427-4
MAS. (2018). Principles to promote fairness, ethics, accountability and transparency (feat) in the use of artificial intelligence and data analytics in singapore’s financial sector (p. 15). Monetary Authority of Singapore.
MAS. (2024). Artificial intelligence model risk management: observations from a thematic review (Artificial Intellegent Model Risk Management, pp. 1–50) [Information Paper]. Monetary Authority of Singapore.
Minkkinen, M., Laine, J., & Mäntymäki, M. (2022). Continuous auditing of artificial intelligence: a conceptualization and assessment of tools and frameworks. Digital Society, 1(3), 21. https://doi.org/10.1007/s44206-022-00022-2
Neumannová, A., Bernroider, E. W. N., & Elshuber, C. (2023). The digital operational resilience act for financial services: a comparative gap analysis and literature review, Information Systems (Vol. 464, pp. 570–585). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-30694-5_40
Nguyen, V.-L., Lin, P.-C., Cheng, B.-C., Hwang, R.-H., & Lin, Y.-D. (2021). Security and privacy for 6G: A survey on prospective technologies and challenges. IEEE Communications Surveys & Tutorials, 23(4), 2384–2428.
Novelli, C., Hacker, P., McDougall, S., Morley, J., Rotolo, A., & Floridi, L. (2025). Getting regulatory sandboxes right: Design and governance under the AI act. Available at SSRN 5332161.
OJK. (2025). Tata kelola kecerdasan artifisial perbankan Indonesia. Otoritas Jasa Keuangan (OJK).
Panarese, P., Grasso, M. M., & Solinas, C. (2025). Algorithmic bias, fairness, and inclusivity: A multilevel framework for justice-oriented AI. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02451-2
Parisot, M. P. M., Pejo, B., & Spagnuelo, D. (2021). Property inference attacks on convolutional neural networks: Influence and implications of target model’s complexity (No. arXiv:2104.13061).arXiv. https://doi.org/10.48550/arXiv.2104.13061
Power, M. (2022). Theorizing the economy of traces: from audit society to surveillance capitalism. Organization Theory, 3(3), 26317877211052296. https://doi.org/10.1177/26317877211052296
Pradana, A. E., Herawati, A. R., & Dwimawanti, I. H. (2025). Tantangan kecerdasan buatan dalam implikasi kebijakan pemerintah di indonesia: Studi Literatur. Jurnal Good Governance, 51–66.
Puannandini, D. A., Fabian, R., Firdaus, R. A. P., Mustopa, M. Z., & Herdiyana, I. (2025). Liabilitas produk AI dalam sistem hukum Indonesia: Implikasi bagi pengembang, pengguna, dan penyedia layanan. Iuris Studia: Jurnal Kajian Hukum, 6(1), 24–33.
Purba, D. S., Permatasari, P. D., Tanjung, N., Rahayu, P., Fitriani, R., & Wulandari, S. (2025). Analisis perkembangan ekonomi digital dalam meningkatkan pertumbuhan ekonomi di indonesia. Jurnal Masharif Al-Syariah: Jurnal Ekonomi dan Perbankan Syariah, 10(1). https://journal.um-surabaya.ac.id/Mas/article/view/25367
Rafael, E. F. (2013). Technology as a social system: A systems theoretical conceptualization. Philippine Sociological Review, 319–347.
Rakovic, I. (2022). Dark finance: Exploring deceptive design in investment apps [Master’s Thesis,NTNU]. https://ntnuopen.ntnu.no/ntnu-xmlui/handle/11250/3005227
Rakovic, I., & Inal, Y. (2023). Dark finance: Exploring deceptive design in investment apps, Human-Computer Interaction–Interact 2023. 14142 (pp. 339–348). https://doi.org/10.1007/978-3-031-42280-5_20
Ravshan, K. (2025). Risks and regulatory challenges associated with fintech technologies. International Conference on Interdisciplinary Science, 2(6), 282–284.
Respati, A. R., & Sukmana, Y. (2023, December 7). Evaluasi penyaluran KUR, dari debitur tak punya NPWP sampai Biaya “siluman” [News]. KOMPAS.com. https://money.kompas.com/read/2023/12/07/194311126/evaluasi-penyaluran-kur-dari-debitur-tak-punya-npwp-sampaibiaya-siluman
Romeo, G., & Conti, D. (2025). Exploring automation bias in human–AI collaboration: A review and implications for explainable AI. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02422-7
Ryan, M., Withers, G., & Den Hartog, F. (2024). The cloud conundrum: Are financial institutions heading for a catastrophic disruption event? IEEE Transactions on Technology and Society. https://ieeexplore.ieee.org/abstract/document/10706249/
Sandy, K. F. (2025, February 9). Begini strategi OJK hadapi serangan siber perbankan [IDX Channel]. https://www.idxchannel.com/. https://www.idxchannel.com/banking/begini-strategiojk-hadapi-serangan-siber-perbankan
Sankalp, M. R., Lokapal, G., Mohan, B. A., & Basavaraj, G. N. (2025). Addressing cybersecurity challenges in 6g networks through ai-driven adaptive defense mechanisms and quantum-resilient protocols. 2025 International Conference on Computing for Sustainability and Intelligent Future (COMP-SIF), 1–12. https://ieeexplore.ieee.org/abstract/document/10969886/
Setyowati, D. (2025, April 10). Kronologi sistem Bank DKI eror, data dan dana nasabah aman?- Teknologi Katadata.co.id. https://katadata.co.id/digital/teknologi/67f74c66822b5/kronologisistem-bank-dki-eror-data-dan-dana-nasabah-aman
Shahnaz, K. (2021, Agustus). BTPN soal pembobolan nasabah jenius: Itu ulah social engineering [Financial News]. Bisnis.Com. https://finansial.bisnis.com/read/20210826/90/1434378/btpnsoal-pembobolan-nasabah-jenius-itu-ulah-social-engineering
Singh, S., Rahman, A., & Kaur Johl, S. (2025). The looming labyrinth: Risks of artificial intelligence in financial sector. In (Eds) Green Horizons: Role of AI in Sustainable Finance (pp. 215–235). Springer, Singapore. https://doi.org/10.1007/978-981-96-6495-5_12
Stiglitz, J. E., & Weiss, A. (1981). Credit rationing in markets with imperfect information. The American Economic Review, 71(3), 393–410.
Sun, J., Zhao, M., & Lei, C. (2024). Class-imbalanced dynamic financial distress prediction based on random forest from the perspective of concept drift. Risk Management, 26(4), 19. https://doi.org/10.1057/s41283-024-00150-8
Susilo, A. (2023). regulatory technology untuk digitalisasi proses kepatuhan (Studi kasus bank swasta di Indonesia). Infotech Journal, 9(1), 252–258. https://doi.org/10.31949/infotech.v9i1.5460
Tempo.com. (2025, February 12). Sempat error berhari-hari, sistem IT pada aplikasi byond dari bsi kini diklaim sudah stabil | tempo.co. Tempo. https://www.tempo.co/ekonomi/sempat-errorberhari-hari-sistem-it-pada-aplikasi-byond-dari-bsi-kini-diklaim-sudah-stabil-1205998
Thalpage, N. (2023). Unlocking the black box: Explainable artificial intelligence (XAI) for trust and transparency in ai systems. J. Digit. Art Humanit, 4(1), 31–36.
Trinh, T. K., & Zhang, D. (2024). Algorithmic fairness in financial decision-making: Detection and mitigation of bias in credit scoring applications. Journal of Advanced Computing Systems, 4(2),36–49.
Trisnawati. (2024). Artificial intelligence governance and regulation: A roadmap to developing legal policies for artificial intelligence deployment. Journal of Governance and Administrative Reform (JGAR), 5(2), 185–194.
Trist, E. L. (1981). The evolution of socio-technical systems (Vol. 2). Ontario quality of working life Centre Toronto. https://www.lmmiller.com/blog/wp-content/uploads/2013/06/The-Evolutionof-Socio-Technical-Systems-Trist.pdf
Veale, M., Binns, R., & Edwards, L. (2018). Algorithms that remember: Model inversion attacks and data protection law. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376(2133), 20180083. https://doi.org/10.1098/rsta.2018.0083
Verbeek, P.-P. (2023). Postphenomenology and ethics. In Technology Ethics (pp. 42–51). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9781003189466-8/postphenomenologyethics-peter-paul-verbeek
Walter, Y. (2024). Managing the race to the moon: Global policy and governance in Artificial Intelligence regulation, A contemporary overview and an analysis of socioeconomic consequences. Discover Artificial Intelligence, 4(1). https://doi.org/10.1007/s44163-024-00109-4
Yaksan, S. (2024). Regulating AI with a legal policy fuelled by innovation and accountability: Regulatory sandboxes as the way forward. Available at SSRN 5068132. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5068132
Zhang, X., Wang, T., Ma, L., & Mahadevan, S. (2025). Reliability engineering, risk management, and trustworthiness assurance for AI systems. Journal of Reliability Science and Engineering, 1(2), 022001.
Zhang, Y., & Wildemuth, B. M. (2009). Qualitative analysis of content. Applications of Social Research Methods to Questions in Information and Library Science, 308(319), 1–12.
Zhang, Z., Ning, H., Shi, F., Farha, F., Xu, Y., Xu, J., Zhang, F., & Choo, K.-K. R. (2022). Artificial intelligence in cyber security: Research advances, challenges, and opportunities. Artificial Intelligence Review, 55(2), 1029–1053. https://doi.org/10.1007/s10462-021-09976-0
Zuboff, S. (2023). The age of surveillance capitalism. In Social theory re-wired (pp. 203–213). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9781003320609-27/agesurveillance-capitalism-shoshana-zuboff
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 The International Journal of Financial Systems
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJFS article's license is CC-BY-NC. Authors grant the journal/publisher publishing rights with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.