The complexity of financial decision-making has intensified in the digital era due to data saturation, market volatility, and the inability of conventional models to respond to real-time and non-linear dynamics. Addressing these challenges requires the integration of intelligent systems capable of adapting to evolving financial environments. Smart finance, which combines artificial intelligence, machine learning, big data analytics, blockchain, and automation, offers transformative potential across financial services. This study synthesizes scholarly findings from 2019 to 2024 across five domains: AI-based modeling, robo-advisory applications, behavioral finance integration, decentralized finance (DeFi), and real-time risk analytics. Results indicate substantial gains in efficiency, accuracy, and personalization, yet also reveal persistent challenges, including algorithmic opacity, ethical concerns in data use, and regulatory ambiguity. Advancing smart finance demands development in explainable AI, hybrid advisory systems, and inclusive, adaptive regulation for decentralized infrastructures. The scope of the analysis is limited to peer-reviewed academic literature published in English, excluding industry reports and grey literature.