This literature review examines the structural transformation of financial management driven by the integration of Artificial Intelligence (AI) and financial technology (fintech). Through a synthesis of recent scholarly findings, this study highlights that AI serves as a powerful catalyst for operational efficiency, significantly enhancing financial performance metrics such as Return on Assets (ROA) and Return on Equity (ROE) by optimizing cost structures and predictive decision-making processes. While these technologies facilitate broader financial inclusion by lowering entry barriers for unbanked populations, they also introduce systemic paradoxes, including algorithmic bias, data privacy concerns, and the challenges of "black-box" decision-making models. The analysis reveals that the effectiveness of these digital tools is heavily contingent upon organizational readiness, workforce digital literacy, and the alignment of AI deployment with long-term strategic business objectives. Furthermore, the review argues that traditional regulatory frameworks are increasingly inadequate for governing autonomous, self-learning AI systems. Consequently, it is recommended that regulators shift toward targeted, risk-based frameworks that standardize human-machine interaction while ensuring consumer protection. Ultimately, this study emphasizes that while AI reshapes the financial landscape, the synergy between computational intelligence and human oversight is essential to ensure sustainable, transparent, and ethical financial governance.
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