Suppr超能文献

银行系统中人工智能和机器学习的应用:对董事会的定性调查

Adoption of artificial intelligence and machine learning in banking systems: a qualitative survey of board of directors.

作者信息

Eskandarany Abdullah

机构信息

College of Business, University of Jeddah, Jeddah, Saudi Arabia.

出版信息

Front Artif Intell. 2024 Nov 27;7:1440051. doi: 10.3389/frai.2024.1440051. eCollection 2024.

Abstract

The aim of the paper is twofold. First to examine the role of the board of directors in facilitating the adoption of AI and ML in Saudi Arabian banking sector. Second, to explore the effectiveness of artificial intelligence and machine learning in protection of Saudi Arabian banking sector from cyberattacks. A qualitative research approach was applied using in-depth interviews with 17 board of directors from prominent Saudi Arabian banks. The present study highlights both the opportunities and challenges of integrating artificial intelligence and machine learning advanced technologies in this highly regulated industry. Findings reveal that advanced artificial intelligence and machine learning technologies offer substantial benefits, particularly in areas like threat detection, fraud prevention, and process automation, enabling banks to meet regulatory standards and mitigate cyber threats efficiently. However, the research also identifies significant barriers, including limited technological infrastructure, a lack of cohesive artificial intelligence strategies, and ethical concerns around data privacy and algorithmic bias. Interviewees emphasized the board of directors' critical role in providing strategic direction, securing resources, and fostering partnerships with artificial intelligence technology providers. The study further highlights the importance of aligning artificial intelligence and machine learning initiatives with national development goals, such as Saudi Vision 2030, to ensure sustained growth and competitiveness. The findings from the present study offer valuable implications for policymakers in banking in navigating the complexities of artificial intelligence and machine learning adoption in financial services, particularly in emerging markets.

摘要

本文的目的有两个。一是研究董事会在促进沙特阿拉伯银行业采用人工智能和机器学习方面的作用。二是探讨人工智能和机器学习在保护沙特阿拉伯银行业免受网络攻击方面的有效性。采用定性研究方法,对沙特阿拉伯主要银行的17名董事会成员进行了深入访谈。本研究突出了在这个高度监管的行业中整合人工智能和机器学习先进技术的机遇与挑战。研究结果表明,先进的人工智能和机器学习技术带来了巨大的好处,特别是在威胁检测、欺诈预防和流程自动化等领域,使银行能够有效满足监管标准并减轻网络威胁。然而,研究也发现了重大障碍,包括有限的技术基础设施、缺乏连贯的人工智能战略以及围绕数据隐私和算法偏差的伦理问题。受访者强调了董事会在提供战略方向、获取资源以及促进与人工智能技术供应商建立伙伴关系方面的关键作用。该研究进一步强调了使人工智能和机器学习计划与国家发展目标(如沙特2030愿景)保持一致的重要性,以确保持续增长和竞争力。本研究的结果为银行业的政策制定者在应对金融服务中采用人工智能和机器学习的复杂性方面提供了宝贵的启示,特别是在新兴市场。

相似文献

5
Artificial Intelligence and Human Psychology in Online Transaction Fraud.在线交易欺诈中的人工智能与人类心理
Front Psychol. 2022 Oct 11;13:947234. doi: 10.3389/fpsyg.2022.947234. eCollection 2022.
6
Integrating machine learning for sustaining cybersecurity in digital banks.整合机器学习以维持数字银行的网络安全。
Heliyon. 2024 Sep 6;10(17):e37571. doi: 10.1016/j.heliyon.2024.e37571. eCollection 2024 Sep 15.
7
Artificial intelligence in hospital infection prevention: an integrative review.医院感染预防中的人工智能:一项综合综述。
Front Public Health. 2025 Apr 2;13:1547450. doi: 10.3389/fpubh.2025.1547450. eCollection 2025.

本文引用的文献

1
Deep treasury management for banks.银行的深度资金管理。
Front Artif Intell. 2023 Mar 22;6:1120297. doi: 10.3389/frai.2023.1120297. eCollection 2023.
2
Assessing Banks' Distress Using News and Regular Financial Data.利用新闻和常规财务数据评估银行的困境
Front Artif Intell. 2022 Jun 2;5:871863. doi: 10.3389/frai.2022.871863. eCollection 2022.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验