# AI in Money Matters

arXiv: https://arxiv.org/abs/2505.07393 · HTML: https://mlsanity.com/paper/2505.07393/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 65 references that are in the map.
- First posted on arXiv 12 May 2025.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [A Survey Of Methods For Explaining Black Box Models](https://mlsanity.com/paper/1802.01933/) (2018)
- [Using an LLM to Help With Code Understanding](https://mlsanity.com/paper/2307.08177/) (2023)
- [Generative AI](https://mlsanity.com/paper/2309.07930/) (2023)
- [LLMs Accelerate Annotation for Medical Information Extraction](https://mlsanity.com/paper/2312.02296/) (2023)
- [How Knowledge Workers Think Generative AI Will (Not) Transform Their Industries](https://mlsanity.com/paper/2310.06778/) (2023)
- [LLM for SoC Security: A Paradigm Shift](https://mlsanity.com/paper/2310.06046/) (2023)
- [Using LLMs in Software Requirements Specifications: An Empirical Evaluation](https://mlsanity.com/paper/2404.17842/) (2024)
- [The Impact of ChatGPT and LLMs on Medical Imaging Stakeholders: Perspectives and Use Cases](https://mlsanity.com/paper/2306.06767/) (2023)
- [The Singularity May Never Be Near](https://mlsanity.com/paper/1602.06462/) (2016)
- [The Users' Perspective on the Privacy-Utility Trade-offs in Health Recommender Systems](https://mlsanity.com/paper/1804.04868/) (2018)

## Abstract (arXiv)

In November 2022, Europe and the world by and large were stunned by the birth of a new large language model : ChatGPT. Ever since then, both academic and populist discussions have taken place in various public spheres such as LinkedIn and X(formerly known as Twitter) with the view to both understand the tool and its benefits for the society. The views of real actors in professional spaces, especially in regulated industries such as finance and law have been largely missing. We aim to begin to close this gap by presenting results from an empirical investigation conducted through interviews with professional actors in the Fintech industry. The paper asks the question, how and to what extent are large language models in general and ChatGPT in particular being adopted and used in the Fintech industry? The results show that while the fintech experts we spoke with see a potential in using large language models in the future, a lot of questions marks remain concerning how they are policed and therefore might be adopted in a regulated industry such as Fintech. This paper aims to add to the existing academic discussing around large language models, with a contribution to our understanding of professional viewpoints.