<![CDATA[The rapid integration of big data and artificial intelligence (AI) is fundamentally reshaping Indonesia’s financial sector, driving unprecedented efficiency, innovation, and financial inclusion. As Southeast Asia’s largest digital economy, Indonesia has embraced fintech solutions that leverage predictive analytics, machine learning, and automation to enhance risk management, streamline transactions, and expand financial services to previously underserved populations. This transformation aligns with global financial trends, yet it presents distinct regulatory, infrastructural, and ethical challenges. Drawing from Schumpeter’s Innovation Theory, Information Asymmetry Theory, and Transaction Cost Economics, this study explores how big data and AI redefine financial operations, improve decision-making, and reduce market inefficiencies in the Indonesian banking ecosystem. Utilizing a qualitative phenomenological approach, this research synthesizes insights from industry experts, regulatory bodies, and financial analysts to assess the implications of data-driven strategies. Findings reveal that while big data optimizes risk assessment, fraud detection, and customer segmentation, regulatory hurdles, cybersecurity risks, and digital literacy gaps remain key barriers to sustainable adoption. As Indonesia continues its trajectory toward a data-centric financial infrastructure, balancing technological advancement with regulatory prudence will be critical in shaping an inclusive and resilient financial future. This study contributes to ongoing discourse on the intersection of financial digitalization, economic policy, and ethical AI deployment in emerging markets.]]>
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