Assessing AI and data protection expertise in academia and the financial services sector: Insights and recommendations for AI skills development

Ioana - Florina Coita () and Maria Moloney ()
Additional contact information
Ioana - Florina Coita: University of Oradea, Postal: Str. Stefan Odobleja nr 72
Maria Moloney: UCD

Journal of Financial Transformation, 2024, vol. 58, 1-170

Abstract: The proliferation of artificial intelligence (AI) is reshaping modern life in many ways. This has prompted action from many governments globally. The European Union is in the process of drafting a new E.U. AI Act, modeled on GDPR. To navigate this evolving regulatory landscape, financial researchers and industry professionals will need comprehensive training. However, existing efforts seem limited. This paper puts forth the idea of tailored training to better understand the complex interaction of data protection and ethical AI. It uses case studies to highlight the challenges of AI and the GDPR in the financial services sector. We also put forth survey findings that suggest current programs inadequately prepare individuals for GDPR compliance in AI. Recommendations include an initial training framework for ethical and compliant AI engagement.

Keywords: data protection; data training; GDPR (search for similar items in EconPapers)
JEL-codes: G39 Q01 Z23 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.capco.com/Capco-Institute/Journal-58-Artificial-Intelligence Full text (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:jofitr:3477

Access Statistics for this article

Journal of Financial Transformation is currently edited by Prof. Shahin Shojai

More articles in Journal of Financial Transformation from Capco Institute 77 Water Street, 10th Floor, New York NY 10005.
Bibliographic data for series maintained by Prof. Shahin Shojai ( this e-mail address is bad, please contact ).