Opportunities and Challenges of Generative-AI in Finance
Desai, Akshar Prabhu, Mallya, Ganesh Satish, Luqman, Mohammad, Ravi, Tejasvi, Kota, Nithya, Yadav, Pranjul
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Nov-22-2024
- Country:
- Asia > Singapore (0.04)
- Europe (0.04)
- North America > United States
- New York
- New York County > New York City (0.04)
- Kings County > New York City (0.04)
- New York
- Genre:
- Overview (1.00)
- Research Report > Promising Solution (0.34)
- Industry:
- Information Technology > Security & Privacy (1.00)
- Banking & Finance > Trading (1.00)
- Technology: