Machine Learning in Finance


연구 분야: Artificial Intelligence



학회: KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining


초록

This workshop aims to explore the intersection of Generative AI with the rich tapestry of financial data types, seeking to uncover new methodologies and techniques that can enhance predictive analytics, fraud detection, and customer insights across the sector. By harnessing these advancements in AI, we can pave the way to not only understand customer behavior but also anticipate their needs more effectively, leading to superior customer outcomes and more personalized services. Our objective is to shed light on the challenges and opportunities presented by the diverse data formats in finance. We aim to bridge the gap between the dominance of traditional models for tabular data analysis and the emerging potential of Generative AI to revolutionize the treatment of time series, click streams, and other unstructured data forms.


Author Profile
Leman Akoglu

Carnegie Mellon University Pittsburgh PA USA

Panama
Author Profile
Nitesh Vijay Chawla

University of Notre Dame Notre Dame IN USA

India
Author Profile
Josep Domingo-Ferrer

Universitat Rovira i Virgili Tarragona Catalonia Spain

Spain

📄 논문 정보

발행 연도 2024년
인용수 0
출판 국가 India, Panama, United States, Spain, Canada
사이트 ACM
좋아요 수 0

연관 논문 목록 (33건)