Your mention Saisuman Singamsetty of cross-domain projects underscores a crucial trend: integrating insights from economics, finance, computer science, and other fields. This interdisciplinary approach is essential for developing models that are not only technically sound but also grounded in economic theory and practical relevance, ultimately leading to more reliable and trustworthy AI-driven financial tools.

As AI models become more sophisticated, transparent, and integrated with domain expertise, they will continue to reshape how financial institutions approach forecasting and risk management. Future developments may include explainable AI, real-time adaptive models, and more robust frameworks for managing uncertainty—elements that will further enhance their utility.

Thanks a lot, Stephen I. Ternyik . I completely agree—without grounding in domain knowledge, even the best AI models can miss the bigger picture. That’s actually what motivated me to explore a hybrid setup. Explainability and adaptability are definitely the next frontiers, especially if we want these tools to be trusted in real-world finance. Appreciate your thoughts!