Artificial Intelligence and Data Science for Fintech

Dear Colleagues,

This Special Issue will focus on Artificial Intelligence in financial technology, with a particular emphasis on large language models (LLMs) as a core enabling technology. We welcome original research and authoritative reviews on AI methods, systems, and deployments that advance forecasting, risk management, trading and execution, compliance, fraud and AML, payments, and customer engagement. Topics of interest include, but are not limited to, the following: supervised, unsupervised, and reinforcement learning for asset pricing, credit and counterparty risk, portfolio optimization, and market microstructure; LLMs and generative AI for research and investment workflows, code and compliance automation, KYC/AML investigation, conversational advisory, document intelligence, and knowledge management; trustworthy and explainable AI, causal inference, robustness and uncertainty, and model governance and alignment with regulatory expectations; graph learning for financial networks; privacy-preserving analytics (federated learning, differential privacy), cybersecurity, and red-teaming; scalable data engineering, streaming inference, and ML operations; human-in-the-loop decision support and human–AI collaboration; and empirical studies, field deployments, or policy-aware evaluations demonstrating measurable gains in accuracy, efficiency, fairness, and safety. We particularly encourage benchmarks, datasets, and reproducible pipelines that are tailored to LLM-centric fintech applications.

Prof. Dr. Kani Chen
Guest Editor

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