The growing dependency of algorithmic tools in digital financial environments such as FinTech has considerably transformed the making and governance of financial choices. Automated credit scoring and algorithmic risk assessment; robo-advisors, and data-based compliance tools are now commonly used by financial institutions and fintech companies. Although these systems increase efficiency, speed and standardisation, they also generate important regulatory and ethical questions for which existing financial governance frameworks are only now responding to. This paper investigates the regulatory and ethical boundaries of algorithmic governance on digital financial systems. The study analyses important regulatory obstacles, such as low explaining ability of algorithmic decisions, weaknesses in the supervisory mechanisms and challenges authorities encounter in overseeing fast changing technologies. The paper also explores ethical consequences from increased automation in finance, including possible biases in data, decreased human judgment and exclusion of certain groups from accessing financial services. It profess too much reliance on automated systems without the necessary safeguards may erode confidence in financial institutions and financial regulation. The study ends by emphasizing the need for balanced governance approaches, which needs to achieve excellent technologies in pair beyond ethical and human safeguards. It emphasises the importance of flexible regulations that enable responsible use of algorithmic systems, fairness, accountability and long-term stability in digital financial markets.