Objective: This study examines how Business Intelligence (BI) tools enhance decision-making processes in fintech startups operating in Palu, Indonesia. As a developing city with unique socio-economic dynamics, Palu’s fintech sector faces challenges in data-driven competitiveness. This research aims to identify BI adoption levels, implementation barriers, and their impact on strategic decisions. Method: A mixed-methods approach was employed, combining surveys of 50 fintech startups in Palu with in-depth interviews of 10 key executives. Quantitative data analyzed BI usage patterns (e.g., dashboards, predictive analytics), while qualitative insights explored operational challenges and perceived benefits. Secondary data from local fintech reports supplemented the analysis. Results: Findings reveal that only 35% of fintech startups in Palu fully utilize BI tools, primarily due to limited technical expertise and budget constraints. However, adopters reported a 40% improvement in decision speed and accuracy, particularly in risk assessment and customer segmentation. The study also highlights Palu’s unique need for localized BI models to address informal economy data gaps. Novelty: This research contributes to the scarce literature on BI applications in emerging cities like Palu, emphasizing context-specific adaptations for fintech growth. It proposes a framework for BI integration tailored to small-scale fintech ecosystems in post-disaster recovery regions.