Ethics and Algorithmic Governance in the Financial Sector: A Systematic Review of Principles, Governance, and Implementation Gaps
DOI:
https://doi.org/10.26439/interfases2025.n022.8230Keywords:
norms , regulations, machine learning, predictive models, adaptive algorithmsAbstract
This article aims to identify the fundamental ethical principles, implemented governance mechanisms, and gaps between theory and practice in the use of algorithms within the banking sector. To this end, a systematic literature review was conducted following the protocol established by Kitchenham and Charters (2007), through searches in four academic databases (IEEE Xplore, ACM Digital Library, SpringerLink, and Scopus) using structured search strings in English and Spanish. After applying rigorous inclusion and exclusion criteria, 28 primary studies published between 2020 and 2025 were selected and analyzed. The findings reveal fundamental tensions between social justice and technical efficiency, as well as persistent challenges in terms of transparency, fairness, and privacy. Regulatory, institutional, and technological strategies are proposed to strengthen the ethical deployment of algorithmic systems, emphasizing human oversight, traceability, and user experience. This research contributes to establishing a framework for advancing toward more responsible, legitimate, and inclusive artificial intelligence in banking.
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