人工智能和机器学习在金融服务行业中的应用:一篇文献统计综述
Debidutta Pattnaik1, Sougata Ray1, Raghu Raman2
1International Management Institute, Bhubaneswar, 751 003, India.
本文献统计综述绘制了银行,金融服务和保险 (BFSI) 部门的人工智能 (AI) 和机器学习 (ML) 研究的地图. 它确定了九个关键研究集群,指导未来的AI和ML在金融中的应用.
科学领域:
- 图书统计学 图书统计学
- 人工智能的人工智能
- 机器学习 机器学习
- 金融服务行业 金融服务行业
背景情况:
- 银行,金融服务和保险 (BFSI) 部门越来越多地采用AI和ML技术.
- 了解研究环境对于战略发展和识别创新机会至关重要.
研究的目的:
- 在BFSI部门内对AI和ML应用进行文献统计审查.
- 使用Scopus索引文章识别和绘制关键研究集群和趋势.
- 为决策者,研究人员和从业人员提供见解.
主要方法:
- 按照PRISMA协议进行的系统文献审查.
- 选了39498篇Scopus索引文章,其中1045篇符合纳入标准.
- 文章标题和摘要的n-gram和并发分析,以确定研究集群.
主要成果:
- 识别了177个独特的术语和9个不同的研究集群.
- 主要集群包括金融科技,风险管理,反洗钱和精算科学.
- 该审查提供了对多面研究环境的全面概述.
结论:
- 确定的研究集群为BFSI部门的未来研究和实际应用提供了路线图.
- 调查结果突出了研究的差距和机会,使学术界和行业利益相关者受益.
- 这项研究为AI和ML在BFSI领域的作用提供了有价值的参考资料.
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