<p>The evolution of financial technology has been marked by successive waves of innovation, from rule-based systems to the widespread adoption of machine learning methods, including deep learning approaches, which have delivered remarkable performance in a range of financial tasks. Recently, the emergence of generative AI (GenAI) has marked a new era in financial evolution, fundamentally reshaping the industry by enabling the creation of data, content, and solutions. Unlike conventional discriminative AI models that primarily focus on prediction and classification, generative models—such as Variational Autoencoders, Generative Adversarial Networks, Normalizing Flow, Diffusion Models, and Large Language Models—offer broader capabilities, enhanced user interaction, and improved interpretability. These advances are driving a new wave of innovative applications across diverse financial domains. Despite the growing literature on GenAI, there remains a lack of comprehensive surveys dedicated to its applications and sectoral impact in finance. This paper systematically reviews the deployment of GenAI techniques across key financial sectors. In particular, we highlight representative applications in securities, investment, banking, accounting, and regulatory compliance, illustrating how GenAI is transforming financial services and operations. Furthermore, we discuss the challenges associated with integrating GenAI into financial applications. This work aspires to be a reference for researchers and practitioners navigating the new era of generative AI in finance.</p>