Responsible Large Language Models in Finance: A Descriptive Bibliometric Overview and Taxonomy of Responsibility

Abstract

The rapid adoption of large language models (LLMs) in financial services has generated a growing literature on “responsible AI” in domains such as investment analysis, credit assessment, risk management, compliance, and financial advisory systems. Unlike earlier AI systems, LLMs introduce responsibility challenges that differ in important ways from those addressed by earlier responsible AI frameworks, including hallucinations, prompt injection and manipulation, generative opacity, instruction-fo

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@article{tan2026responsible,
  title = {{Responsible Large Language Models in Finance: A Descriptive Bibliometric Overview and Taxonomy of Responsibility}},
  author = {Chong-Hui Tan and Qinxu Ding},
  year = {2026},
  month = aug,
  journal = {FinTech},
  doi = {10.3390/fintech5030071},
  url = {https://www.semanticscholar.org/paper/ccc1f69bb0b261c2d590eaff0b8eee2ad42140cb}
}