{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T10:11:03Z","timestamp":1764238263153,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T00:00:00Z","timestamp":1704931200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Access Publication Funds\/transformative agreements of the G\u00f6ttingen University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MAKE"],"abstract":"<jats:p>The intended automation in the financial industry creates a proper area for artificial intelligence usage. However, complex and high regulatory standards and rapid technological developments pose significant challenges in developing and deploying AI-based services in the finance industry. The regulatory principles defined by financial authorities in Europe need to be structured in a fine-granular way to promote understanding and ensure customer safety and the quality of AI-based services in the financial industry. This will lead to a better understanding of regulators\u2019 priorities and guide how AI-based services are built. This paper provides a classification pattern with a taxonomy that clarifies the existing European regulatory principles for researchers, regulatory authorities, and financial services companies. Our study can pave the way for developing compliant AI-based services by bringing out the thematic focus of regulatory principles.<\/jats:p>","DOI":"10.3390\/make6010008","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T06:52:14Z","timestamp":1704955934000},"page":"143-155","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["What Do the Regulators Mean? A Taxonomy of Regulatory Principles for the Use of AI in Financial Services"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4416-9284","authenticated-orcid":false,"given":"Mustafa","family":"Pamuk","sequence":"first","affiliation":[{"name":"Faculty of Business and Economics, University of Goettingen, 37073 Goettingen, Germany"}]},{"given":"Matthias","family":"Schumann","sequence":"additional","affiliation":[{"name":"Faculty of Business and Economics, University of Goettingen, 37073 Goettingen, Germany"}]},{"given":"Robert C.","family":"Nickerson","sequence":"additional","affiliation":[{"name":"Department of Information Systems, College of Business, San Francisco State University, San Francisco, CA 94132, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"ref_1","unstructured":"OECD (2022, October 05). Artificial Intelligence, Machine Learning and Big Data in Finance\u2014OECD. 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