Alex Xie¹ and Yu Sun², ¹USA, ²California State Polytechnic University, USA

This paper presents a comprehensive survey and review of financial prompt patterns, exploring the innovative integration of ChatGPT in finance-related tasks. With the rapid evolution of AI and its increasing application in various sectors, the finance industry stands at the forefront of this technological revolution. Our research delves into the myriad ways in which prompt engineering with ChatGPT can enhance financial analyses, risk assessment, investment strategy formulation, and customer service in the finance sector. We systematically categorize and evaluate a wide array of prompt patterns, drawing insights from real-world applications and theoretical frameworks. This survey not only identifies the current state of prompt engineering in finance but also forecasts future trends, challenges, and opportunities. By providing a detailed examination of various prompt designs and their outcomes, this paper aims to serve as a foundational guide for practitioners and researchers seeking to leverage ChatGPT's capabilities for optimized financial decision-making and innovation. The findings underscore the transformative potential of tailored prompts in elevating the accuracy, efficiency, and scope of financial services and strategies

Large Language Model, ChatGPT, Finance, Prompt Patterns