On the Transposition of FAIR Data Principles to Financial Services: An Adapted FAAIR Guideline

Adopting a critical view on the governance and policymaking of artificial intelligence (AI), commercial entities in the financial services industry retain research knowledge and power, leading to policymaking challenges. This research critically analyses the FAIR (Findable, Accessible, Interoperable, Reusable) discourse on financial services research. Research reproducibility is assessed in peer-reviewed research articles that apply AI methods in finance, taxation, and insurance fields published between 2000 and 2023. A dataset of 126 articles (66 finance, 40 insurance, 20 tax) is analysed, measuring each article’s application of the FAIR Data Principles. Findings highlight that 50% of analysed articles comply with the FAIR Data Principles, indicating a reproducibility crisis in AI-applied financial services research.