Generative artificial intelligence (AI), particularly large language models (LLMs), shows significant potential for transforming financial translation—a highly specialised field of language services that presents ongoing challenges for professional translators. Financial translation plays a crucial role in Hong Kong, an international financial centre where English and Chinese are official languages. This chapter demonstrates how LLMs may be employed as translation assistants at various stages of the translation process and how they can enhance existing tools, such as bilingual term extraction applications and translation memories. The discussion also addresses the limitations of LLMs and explains key issues such as hallucinations, context window constraints, and limited reasoning capacity in complex cases, with an emphasis on the continuing need for human oversight and intervention. It further explores strategies for optimising the performance of LLMs in financial translation, including prompt engineering, model fine-tuning, and agent-based systems. For clarity and accessibility, the content is structured into two main parts. The first part provides a hands-on guide to technical capabilities and applications, while the second delves into critical issues of governance, risk, and professional development. To support both practitioners and learners, explanatory sidebars introduce technical concepts, and a companion online repository provides the full inputs and outputs for key examples discussed. Finally, the analysis calls for targeted professional development in generative AI for financial translators, including AI literacy and collaborative learning.