The rapid evolution of financial technology has significantly transformed traditional lending mechanisms, giving rise to digital lending platforms that provide faster, more accessible, and data-driven credit services. This study examines the impact of digital lending platforms on customer borrowing behavior, focusing on how technological features influence decision-making patterns. The research problem stems from the increasing reliance on digital platforms without a comprehensive understanding of their behavioral implications. The primary objectives of the study are to analyze the relationship between digital platform attributes and borrowing behavior, and to assess the influence of convenience, accessibility, and risk perception on customer decisions. The study adopts a quantitative research design using secondary data from financial reports, industry publications, and fintech databases. Statistical tools such as correlation and regression analysis are employed. The findings indicate that ease of access, quick approval processes, and personalized credit offerings significantly influence borrowing tendencies, often leading to increased borrowing frequency. However, concerns related to over-indebtedness and financial literacy persist. This study contributes to the literature by integrating behavioral finance perspectives with fintech adoption, offering insights for policymakers, financial institutions, and digital lenders in designing responsible lending frameworks.