Artificial Intelligence and the Fragile Fortress: Addressing the Security and Data Privacy Gaps in Indonesia’s Financial Sector Resilience - Maturbongs, Yoseph Hendrik (Otoritas Jasa Keuangan, 2025)
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.