Q1 (OPERATIONS RESEARCH & MANAGEMENT SCIENCE 22/106)
征稿主题
AI for Business and Finance Decisions
细分领域
Generative AI, large language models (LLMs), and other foundational models having impacts or applications in finance and related areas
Leveraging AI, machine learning, and agent-based models to study heterogeneity in the finance and business economics domain
AI/ML models for finance applications and econometrics, including time series predictions, causal inference, and managerial learning/optimization under uncertainty
Decision analytics and methods applied to financial management and decisions
Robust control, dynamic programming, and structural estimations using deep learning with applications in finance and related areas
Algorithmic transparency and interpretable AI in finance and related areas
Algorithmic fairness, bias, discrimination, and amplification in AI/ML/big data applications in finance and related business domains
Human-centered AI and human–machine interaction in finance and related areas
Security, systemic risk, and privacy issues concerning use of AI and ML in finance
Reinforcement learning, federated learning, and transfer learning in financial settings
Business fraud detection and AI/ML applications in financial regulation
AI-driven optimization techniques and applications or advanced methodologies for prescriptive decision making in finance and business economics domains
The use of AI in creating personalized financial advice and automated investment management services through, for example, robo-advisors or LLM-based apps
Alignment issues to deal with reward hacking, instrumental strategies (power seeking, survival), etc., and its relevance in financial and business settings
Multimodal systems and models with applications in finance and business decisions
Methods for machine unlearning, data selection, or data augmentation in the settings of finance and related business fields
