综述生成式AI在金融领域的应用前景与挑战
Opportunities and Challenges of Generative-AI in Finance
- 系统梳理生成式AI在金融中的多种应用场景
- 指出技术落地面临的数据、安全与合规难题
- 适合金融科技从业者与跨领域研究者参考
生成式AI技术具备理解语言上下文、处理海量数据、快速响应等优势，可针对不同任务和领域进行微调。本文全面综述了生成式AI在金融领域的应用现状，深入分析其带来的机遇与挑战，阐述多种训练方法，并展示其在金融生态中的多样化应用。本工作为目前金融领域最全面的生成式AI总结，旨在揭示重点发展方向，明确未来优先事项。同时期望促进金融与其他领域的创新融合，推动知识与实践的交叉传播。
原文摘要 · Abstract (English)
Gen-AI techniques are able to improve understanding of context and nuances in language modeling, translation between languages, handle large volumes of data, provide fast, low-latency responses and can be fine-tuned for various tasks and domains. In this manuscript, we present a comprehensive overview of the applications of Gen-AI techniques in the finance domain. In particular, we present the opportunities and challenges associated with the usage of Gen-AI techniques. We also illustrate the various methodologies which can be used to train Gen-AI techniques and present the various application areas of Gen-AI technologies in the finance ecosystem. To the best of our knowledge, this work represents the most comprehensive summarization of Gen-AI techniques within the financial domain. The analysis is designed for a deep overview of areas marked for substantial advancement while simultaneously pin-point those warranting future prioritization. We also hope that this work would serve as a conduit between finance and other domains, thus fostering the cross-pollination of innovative concepts and practices.
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